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; Copyright (C) 2015, ForrestHunt, Inc.
; Written by J Strother Moore, December, 2012
; License: A 3-clause BSD license. See the LICENSE file distributed with ACL2.
; (certify-book "elementary-bounders")
; Tau Interval Functions for Basic Arithmetic
; and Proofs of Their Correctness
; J Strother Moore
; Edinburgh, December, 2012
; Acknowledgements: Since its release some additions and improvements were made
; to this book by Dmitry Nadezhin. Thanks!
; Abstract
; Consider (+ x y) and suppose we know that the inputs, x and y, are contained
; in two intervals, int1 and int2. We wish to compute from int1 and int2 an
; interval containing (+ x y). For example, if x is known to be an INTEGERP
; such that 1 <= x <= 16 and y is a RATIONALP such that 0 < y (with no known
; upper bound), then (+ x y) is known to be in the RATIONALP interval such that
; 1 < (+ x y) (with no known upper bound). I call the function that takes two
; intervals containing x and y respectively and that returns an interval
; containing (fn x y) a ``bounder'' for fn.
;
; I have developed a book that defines bounders for +, *, -, /, FLOOR, MOD,
; LOGAND, LOGNOT, LOGIOR, LOGORC1, LOGEQV, LOGXOR, EXPT2, and ASH. The book
; proves the correctness of each bounder. In future work I hope to extend ACL2
; so that users can define and verify bounders to improve the tau system. The
; present work is an exploration of the shape and content of such bounder
; theorems. Ideally, the present book would just become part of an arithmetic
; package and not be built into ACL2.
; Our bounder definitions (and hence their correctness proofs) fall into one of
; two different styles. The first definitional style is just straightforward
; case analysis and arithmetic and so the proof follows the usual ACL2 style of
; definitional expansion and use of the arithmetic-5 library. This first style
; of proof can generate a lot of cases. For example, the proof that the
; bounder for products is correct generates over 40,000 subgoals. This is due
; to a variety of issues including the myriad combinations of choices for the
; intervals containing the inputs x and y (e.g., are they open or closed,
; finite or not, over what domains?), as well as the case analysis necessary to
; compute the bounds. See the definition of tau-bounder-* below.
; In the second style, the bounders are defined in terms of previously verified
; bounders. For example,
; (LOGIOR X Y) = (LOGNOT (LOGAND (LOGNOT X) (LOGNOT Y)))
; Thus, we can bound LOGIOR by composing already verified bounders and we can
; verify the LOGIOR bounder by exploiting the proved properties of those
; earlier bounders. However, making this second proof style work imposes
; additional constraints on the correctness theorems and how they are stored as
; rules.
; The book concludes with an essay On the Accuracy of the LOGAND Bounder.
; Some Technical Details
; In this work, an interval is a data structure, constructed by make-tau-interval,
; containing five fields that are named the ``domain,'' the ``lower bound
; relation,'' the ``lower bound,'' the ``upper bound relation,'' and the
; ``upper bound.'' These fields are accessed by interval-dom, interval-lo-rel,
; interval-lo, interval-hi-rel, and interval-hi. The actual shape of the data
; structure is the same as for a tau-interval in the ACL2 source code:
; (defrec tau-interval (domain (lo-rel . lo) . (hi-rel . hi)) t).
; However, in the source code tau-intervals are constructed by the macro make
; and accessed by the macro access, which expand to raw conses, cars, and cdrs
; for efficiency. I chose to introduce a named constructor and accessors to
; make it easier to hang lemmas on them during correctness proofs for bounders.
; But the named functions work on exactly the same data structures and can be
; applied to build and access ACL2's tau-intervals.
; An interval domain must be one of INTEGERP, RATIONALP, ACL2-NUMBERP, or nil,
; the last indicating that there is no restriction. An interval relation is a
; Boolean, where nil means the relation is ``<='' and t means the relation is
; ``<.'' That is, nil means ``weak inequality'' and t means ``strong
; inequality.'' The upper and lower bounds are either nil, meaning no such
; bound is known, or an explicit rational. Symbolic bounds are not allowed.
; For example,
; (make-tau-interval 'RATIONALP t -1/2 nil 1)
; denotes the interval containing x such that
; (rationalp x) & -1/2 < x <= 1.
; There are two other constraints on well-formed interval. First, if the two
; bounds, lo and hi, of an interval are non-nil, then lo <= hi. Second, if the
; domain of an interval is INTEGERP then the relations must be weak and the
; bounds must be integers. That is, if x is known to be an INTEGERP such that
; 1/2 < x < 11/2 then instead of creating the (illegal) interval
; (make-tau-interval 'INTEGERP T 1/2 T 11/2)
; one must create
; (make-tau-interval 'INTEGERP NIL 1 NIL 5)
; Of course, (make-tau-interval 'RATIONALP T 1/2 T 11/2) is a perfectly legal
; interval.
; These constraints are formalized in the predicate intervalp below.
; To say that x is ``in'' an interval, int, is (in-tau-intervalp x int), formalized
; below.
; The correctness theorem for the bounder function for addition, which is
; called tau-bounder-+, is given below and suggests the shape of all bounder
; correctness theorems here.
; (implies (and (tau-intervalp int1)
; (tau-intervalp int2)
; (or (equal (tau-interval-dom int1) 'integerp)
; (equal (tau-interval-dom int1) 'rationalp))
; (or (equal (tau-interval-dom int2) 'integerp)
; (equal (tau-interval-dom int2) 'rationalp))
; (in-tau-intervalp x int1)
; (in-tau-intervalp y int2))
; (and (tau-intervalp (tau-bounder-+ int1 int2))
; (in-tau-intervalp (+ x y) (tau-bounder-+ int1 int2))
; ))
; We envision this being used as follows: when ACL2 is asked to compute the tau
; of (+ x y) it first computes the tau of x and the tau of y. These tau will
; include (possibly trivially unrestrictive) intervals, say int1 and int2. An
; invariant of the ACL2 code is that the computed int1 and int2 are well-formed
; intervals that contain the values of x and y respectively. Thus, the first
; two and last two hypotheses of the correctness theorem are assured. Next,
; ACL2 should check that the domains of the two computed intervals are each
; either INTEGERP or RATIONALP, which if true satisfies the middle two
; hypotheses. Thus, ACL2 can then run (tau-bounder-+ int1 int2) and know that
; it returns a well-formed interval that contains the value of (+ x y). This
; allows it to include that newly computed interval into the tau being computed
; for (+ x y).
; In order to use such correctness theorems in the proofs of other such correctness
; theorems, it is necessary (a) to code the theorems (mainly) as :forward-chaining
; rules, and (b) include in the correctness theorem one additional conclusion, namely
; (implies (not (equal (tau-interval-dom (tau-bounder-+ int1 int2)) 'integerp))
; (equal (tau-interval-dom (tau-bounder-+ int1 int2)) 'rationalp)).
; This additional conclusion, which is not necessary for the imagined use of
; TAU-BOUNDER-+, allows the facts proved about TAU-BOUNDER-+ to be sufficient
; to relieve the hypotheses of other correctness results.
; The reason we code these correctness results mainly as :forward-chaining
; rules has to do with free variables. The bounder for LOGIOR is
; a composition of the bounders for LOGNOT and LOGAND because:
; (LOGIOR X Y) = (LOGNOT (LOGAND (LOGNOT X) (LOGNOT Y)))
; The correctness of the LOGIOR bounder will introduce:
; (TAU-BOUNDER-LOGNOT
; (TAU-BOUNDER-LOGAND
; (TAU-BOUNDER-LOGNOT INT1)
; (TAU-BOUNDER-LOGNOT INT2)))
; and all we will know is that X is in INT1 and Y is INT2. By forward chaining
; from those two facts, triggered by the presence in the goal of the trigger
; terms (TAU-BOUNDER-LOGNOT INT2) and (TAU-BOUNDER-LOGAND ...) we can infer:
; (IN-TAU-INTERVALP (LOGNOT X) (TAU-BOUNDER-LOGNOT INT1))
; (IN-TAU-INTERVALP (LOGNOT Y) (TAU-BOUNDER-LOGNOT INT2))
; from one round of forward chaining, and then:
; (IN-TAU-INTERVALP (LOGAND (LOGNOT X) (LOGNOT Y))
; (TAU-BOUNDER-LOGAND
; (TAU-BOUNDER-LOGNOT INT1)
; (TAU-BOUNDER-LOGNOT INT2)))
; from a second and then
; (IN-TAU-INTERVALP (LOGNOT (LOGAND (LOGNOT X) (LOGNOT Y)))
; (TAU-BOUNDER-LOGNOT
; (TAU-BOUNDER-LOGAND
; (TAU-BOUNDER-LOGNOT INT1)
; (TAU-BOUNDER-LOGNOT INT2))))
; from a third. We discuss the decision to use forward-chaining further in the
; proof of tau-bounder-floor-correct.
; -----------------------------------------------------------------
(in-package "ACL2")
(local (include-book "arithmetic-5/top" :dir :system))
(local (deftheory jared-disables
'(;; Things I think are slow in arith-5
|(equal (if a b c) x)|
|(equal x (if a b c))|
|(+ x (if a b c))|
SIMPLIFY-PRODUCTS-GATHER-EXPONENTS-<
(:T EXPT-TYPE-PRESCRIPTION-INTEGERP-BASE)
(:T EXPT-TYPE-PRESCRIPTION-INTEGERP-BASE-A)
(:T EXPT-TYPE-PRESCRIPTION-NONPOSITIVE-BASE-ODD-EXPONENT)
(:T EXPT-TYPE-PRESCRIPTION-NONPOSITIVE-BASE-EVEN-EXPONENT)
(:T EXPT-TYPE-PRESCRIPTION-NEGATIVE-BASE-ODD-EXPONENT)
(:T EXPT-TYPE-PRESCRIPTION-NEGATIVE-BASE-EVEN-EXPONENT)
(:T EXPT-TYPE-PRESCRIPTION-INTEGERP-BASE-B)
(:T EXPT-TYPE-PRESCRIPTION-RATIONALP-BASE)
(:T EXPT-TYPE-PRESCRIPTION-NON-0-BASE)
(:T NOT-INTEGERP-3B)
(:T NOT-INTEGERP-1B)
(:T NOT-INTEGERP-2B)
(:T NOT-INTEGERP-4E)
(:T NOT-INTEGERP-4B)
(:T NOT-INTEGERP-4B-EXPT)
(:T NOT-INTEGERP-3B-EXPT)
(:T NOT-INTEGERP-2B-EXPT)
(:T NOT-INTEGERP-1B-EXPT)
(:T RATIONALP-EXPT-TYPE-PRESCRIPTION)
RATIONALP-X
acl2-numberp-x
not-integerp-1a
not-integerp-2a
not-integerp-3a
not-integerp-4a
not-integerp-1d
not-integerp-2d
not-integerp-3d
not-integerp-4d
not-integerp-1f
not-integerp-2f
not-integerp-3f
not-integerp-4f
default-times-1
default-times-2
default-less-than-1
default-less-than-2
default-car
default-cdr
)))
(local (in-theory (disable jared-disables)))
(local (SET-DEFAULT-HINTS
'((NONLINEARP-DEFAULT-HINT++ ID
STABLE-UNDER-SIMPLIFICATIONP HIST NIL)
(and stable-under-simplificationp
(not (cw "Jared-hint: re-enabling slow rules.~%"))
'(:in-theory (enable jared-disables))))))
; Note: I tried the simpler nonlinear hint:
; (set-default-hints '((nonlinearp-default-hint
; stable-under-simplificationp
; hist
; pspv)))
; but it didn't suffice for the tau-bounder-floor-correct theorem.
; -----------------------------------------------------------------
; Basic Abstract Properties of the Interval Functions
(local
(defthm abstract-def-<?
(implies (implies (and x y)
(or (real/rationalp x)
(real/rationalp y)))
(iff (<? rel x y)
(if (or (null x)
(null y))
t
(if rel (< x y) (<= x y)))))
:hints
(("Goal"
:use ((:instance completion-of-< (x x) (y y))
(:instance completion-of-< (x y) (y x)))))
:rule-classes
((:rewrite :corollary
(implies (real/rationalp x)
(iff (<? rel x y)
(if (or (null x)
(null y))
t
(if rel (< x y) (<= x y))))))
(:rewrite :corollary
(implies (real/rationalp y)
(iff (<? rel x y)
(if (or (null x)
(null y))
t
(if rel (< x y) (<= x y))))))
(:rewrite :corollary
(implies (null x)
(iff (<? rel x y)
(if (or (null x)
(null y))
t
(if rel (< x y) (<= x y))))))
(:rewrite :corollary
(implies (null y)
(iff (<? rel x y)
(if (or (null x)
(null y))
t
(if rel (< x y) (<= x y)))))))))
(local
(in-theory (disable <?)))
(local
(defthm interval-accessors
(and (equal (tau-interval-dom (make-tau-interval dom lo-rel lo hi-rel hi))
dom)
(equal (tau-interval-lo-rel (make-tau-interval dom lo-rel lo hi-rel hi))
lo-rel)
(equal (tau-interval-lo (make-tau-interval dom lo-rel lo hi-rel hi))
lo)
(equal (tau-interval-hi-rel (make-tau-interval dom lo-rel lo hi-rel hi))
hi-rel)
(equal (tau-interval-hi (make-tau-interval dom lo-rel lo hi-rel hi))
hi))))
(local
(defthm intervalp-rules
(implies (tau-intervalp int)
(and
(implies (equal (tau-interval-dom int) 'integerp)
(and (equal (tau-interval-lo-rel int) nil)
(equal (tau-interval-hi-rel int) nil)
(equal (integerp (tau-interval-lo int))
(if (tau-interval-lo int) t nil))
(equal (integerp (tau-interval-hi int))
(if (tau-interval-hi int) t nil))
))
(booleanp (tau-interval-lo-rel int))
(booleanp (tau-interval-hi-rel int))
;;(implies (tau-interval-lo int) (rationalp (tau-interval-lo int)))
(equal (rationalp (tau-interval-lo int))
(if (tau-interval-lo int) t nil))
;; (implies (tau-interval-hi int) (rationalp (tau-interval-hi int)))
(equal (rationalp (tau-interval-hi int))
(if (tau-interval-hi int) t nil))
(implies (and (tau-interval-lo int)
(tau-interval-hi int))
(<= (tau-interval-lo int)
(tau-interval-hi int)))))
:rule-classes
((:rewrite
:corollary
(implies (tau-intervalp int)
(and (equal (rationalp (tau-interval-lo int))
(if (tau-interval-lo int) t nil))
(equal (rationalp (tau-interval-hi int))
(if (tau-interval-hi int) t nil)))))
(:rewrite
:corollary
(implies (and (equal (tau-interval-dom int) 'integerp)
(tau-intervalp int))
(and (equal (tau-interval-lo-rel int) nil)
(equal (tau-interval-hi-rel int) nil)
(equal (integerp (tau-interval-lo int))
(if (tau-interval-lo int) t nil))
(equal (integerp (tau-interval-hi int))
(if (tau-interval-hi int) t nil)))))
(:forward-chaining
:corollary
(implies (and (tau-intervalp int)
(equal (tau-interval-dom int) 'integerp)
(tau-interval-lo int))
(integerp (tau-interval-lo int))))
(:forward-chaining
:corollary
(implies (and (tau-intervalp int)
(equal (tau-interval-dom int) 'integerp)
(tau-interval-hi int))
(integerp (tau-interval-hi int))))
(:forward-chaining
:corollary
(implies (and (tau-intervalp int)
(tau-interval-lo int))
(rationalp (tau-interval-lo int))))
(:forward-chaining
:corollary
(implies (and (tau-intervalp int)
(tau-interval-hi int))
(rationalp (tau-interval-hi int))))
;; Jared: removing these since they seem expensive and bad
;; (:type-prescription
;; :corollary
;; (implies (tau-intervalp int) (booleanp (tau-interval-lo-rel int))))
;; (:type-prescription
;; :corollary
;; (implies (tau-intervalp int) (booleanp (tau-interval-hi-rel int))))
(:linear
:corollary
(implies (and (tau-intervalp int)
(tau-interval-lo int)
(tau-interval-hi int))
(<= (tau-interval-lo int)
(tau-interval-hi int)))))))
(local
(defthm in-tau-intervalp-rules
(and
(implies (and (tau-intervalp int)
(in-tau-intervalp x int)
(eq (tau-interval-dom int) 'integerp))
(integerp x))
(implies (and (tau-intervalp int)
(in-tau-intervalp x int)
(eq (tau-interval-dom int) 'rationalp))
(rationalp x))
(implies (and (tau-intervalp int)
(in-tau-intervalp x int)
(eq (tau-interval-dom int) 'acl2-numberp))
(acl2-numberp x))
(implies (and (tau-intervalp int)
(in-tau-intervalp x int)
x
(tau-interval-lo-rel int)
(tau-interval-lo int))
(< (tau-interval-lo int) x))
(implies (and (tau-intervalp int)
(in-tau-intervalp x int)
x
(not (tau-interval-lo-rel int))
(tau-interval-lo int))
(<= (tau-interval-lo int) x))
(implies (and (tau-intervalp int)
(in-tau-intervalp x int)
x
(tau-interval-hi-rel int)
(tau-interval-hi int))
(< x (tau-interval-hi int)))
(implies (and (tau-intervalp int)
(in-tau-intervalp x int)
(not (tau-interval-hi-rel int))
x
(tau-interval-hi int))
(<= x (tau-interval-hi int))))
:rule-classes
((:forward-chaining
:corollary
(implies (and (in-tau-intervalp x int)
(tau-intervalp int)
(eq (tau-interval-dom int) 'integerp))
(integerp x)))
(:forward-chaining
:corollary
(implies (and (in-tau-intervalp x int)
(tau-intervalp int)
(eq (tau-interval-dom int) 'rationalp))
(rationalp x)))
(:forward-chaining
:corollary
(implies (and (in-tau-intervalp x int)
(tau-intervalp int)
(eq (tau-interval-dom int) 'acl2-numberp))
(acl2-numberp x)))
(:linear
:corollary
(implies (and (in-tau-intervalp x int)
x
(tau-intervalp int)
(tau-interval-lo-rel int)
(tau-interval-lo int))
(< (tau-interval-lo int) x)))
(:linear ; forward-chaining
:corollary
(implies (and (in-tau-intervalp x int)
x
(tau-intervalp int)
(tau-interval-lo int))
(<= (tau-interval-lo int) x)))
(:linear ; forward-chaining
:corollary
(implies (and (in-tau-intervalp x int)
x
(tau-intervalp int)
(tau-interval-hi-rel int)
(tau-interval-hi int))
(< x (tau-interval-hi int))))
(:linear ; forward-chaining
:corollary
(implies (and (in-tau-intervalp x int)
x
(tau-intervalp int)
(tau-interval-hi int))
(<= x (tau-interval-hi int)))))))
(local
(defthm intervalp-make-tau-interval
(equal (tau-intervalp (make-tau-interval dom lo-rel lo hi-rel hi))
(cond ((eq dom 'integerp)
(and (null lo-rel)
(null hi-rel)
(if lo
(and (integerp lo)
(if hi (and (integerp hi) (<= lo hi))
t))
(if hi (integerp hi) t))))
(t (and (member dom '(rationalp acl2-numberp nil))
(booleanp lo-rel)
(booleanp hi-rel)
(if lo
(and (rationalp lo)
(if hi (and (rationalp hi) (<= lo hi))
t))
(if hi (rationalp hi) t))))))))
(local
(defthm in-tau-intervalp-make-tau-interval
(equal (in-tau-intervalp x (make-tau-interval dom lo-rel lo hi-rel hi))
(and (tau-interval-domainp dom x)
(<? lo-rel lo (fix x))
(<? hi-rel (fix x) hi)))))
(local
(in-theory (disable make-tau-interval
tau-interval-dom tau-interval-lo-rel tau-interval-lo
tau-interval-hi-rel tau-interval-hi)))
; -----------------------------------------------------------------
; BINARY-+
(defun domain-of-binary-arithmetic-function (domx domy)
(declare (xargs :guard (and (symbolp domx) (symbolp domy))))
; In this function, domx and domy are domain names as found in tau-bounders,
; e.g., INTEGERP, RATIONALP, ACL2-NUMBERP, or NIL. The function returns the
; the domain of such generic binary arithmetic functions as sum, product, or
; mod. Note that arithmetic functions always return (at least) ACL2-NUMBERPs.
; So we never return NIL.
(cond ((eq domx 'integerp)
(cond ((eq domy 'integerp) 'integerp)
((eq domy 'rationalp) 'rationalp)
(t 'acl2-numberp)))
((eq domx 'rationalp)
(cond ((or (eq domy 'integerp)
(eq domy 'rationalp))
'rationalp)
(t 'acl2-numberp)))
(t 'acl2-numberp)))
(defun bounds-of-sum (lo-rel1 lo1 hi-rel1 hi1 lo-rel2 lo2 hi-rel2 hi2)
(declare (xargs :guard (and (booleanp lo-rel1)
(or (null lo1) (rationalp lo1))
(booleanp hi-rel1)
(or (null hi1) (rationalp hi1))
(booleanp lo-rel2)
(or (null lo2) (rationalp lo2))
(booleanp hi-rel2)
(or (null hi2) (rationalp hi2)))))
; Suppose x and y are terms and that it is known that lo1 <? x <? hi1 and lo2
; <? y <? hi2, where the relations denoted by ``<?'' are controlled by the four
; respective ``rel'' flags. We seek bounds (mv lo lo-rel hi hi-rel) on the sum
; (+ x y). In the ideal case where all the intervals are bounded by finite
; rationals, the answer would be:
; (mv (or lo-rel1 lo-rel2) (+ lo1 lo2) (or hi-rel1 hi-rel2) (+ hi1 hi2)).
; In the case of sum, the upper and lower bounds can be computed independently.
; But to make this function similar to the function for computing the bounds of
; a product -- where, for example, the lower bounds of the factors can
; influence the upper bound of the product -- we take all eight parameters and
; compute all four results in one function.
; Complicating this function is the requirement that we must allow for
; infinities. Thus, for example, if lo2 is nil, we have ``-infinity <= y''.
; With no lower bound on y, there can be no lower bound on (+ x y). Finally,
; recall our convention that when the bound is infinite, we use the weak
; relation (rel = nil) by default.
(mv-let
(lo-rel lo)
(if (and lo1 lo2)
(mv (or lo-rel1 lo-rel2) (+ lo1 lo2))
(mv nil nil))
(mv-let
(hi-rel hi)
(if (and hi1 hi2)
(mv (or hi-rel1 hi-rel2) (+ hi1 hi2))
(mv nil nil))
(mv lo-rel lo hi-rel hi))))
(defun tau-bounder-+ (int1 int2)
(declare (xargs :guard (and (tau-intervalp int1) (tau-intervalp int2))))
(let ((dom (domain-of-binary-arithmetic-function
(tau-interval-dom int1)
(tau-interval-dom int2))))
(mv-let (lo-rel lo hi-rel hi)
(bounds-of-sum (tau-interval-lo-rel int1)
(tau-interval-lo int1)
(tau-interval-hi-rel int1)
(tau-interval-hi int1)
(tau-interval-lo-rel int2)
(tau-interval-lo int2)
(tau-interval-hi-rel int2)
(tau-interval-hi int2))
(make-tau-interval dom lo-rel lo hi-rel hi))))
(defthm tau-bounder-+-correct
(implies (and (tau-intervalp int1)
(tau-intervalp int2)
(in-tau-intervalp x int1)
(in-tau-intervalp y int2))
(and (tau-intervalp (tau-bounder-+ int1 int2))
(in-tau-intervalp (+ x y) (tau-bounder-+ int1 int2))
))
:rule-classes
((:rewrite)
(:forward-chaining
:corollary
(implies (and (tau-intervalp int1)
(tau-intervalp int2)
(in-tau-intervalp x int1)
(in-tau-intervalp y int2))
(and (tau-intervalp (tau-bounder-+ int1 int2))
(in-tau-intervalp (+ x y) (tau-bounder-+ int1 int2))))
:trigger-terms ((tau-bounder-+ int1 int2)))
))
; -----------------------------------------------------------------
; BINARY-*
(defund extended-rationalp (x)
(declare (xargs :guard t))
(or (equal x nil)
(equal x t)
(real/rationalp x)))
(local (defthm |extended-rationalp is rationalp when not nil or t|
(implies
(and (extended-rationalp x) (not (equal x nil)) (not (equal x t)))
(real/rationalp x))
:hints (("Goal" :in-theory (enable extended-rationalp)))))
(local (defthm |rationalp is extended-rationalp|
(implies (real/rationalp x) (extended-rationalp x))
:hints (("Goal" :in-theory (enable extended-rationalp)))))
(local (defthm |rationalp when acl2-numberp and extended-rationalp|
(implies
(and (acl2-numberp x) (extended-rationalp x))
(real/rationalp x))))
; I now implement ``the bounds of the product are the products of the bounds.''
; But this is INSANELY more complicated and depends on the signs of the
; intervals, whether they are strict or non-strict, and whether they contain
; zero. For example, if both intervals are strictly negative (the upper bounds
; are negative), then the product of their lower bounds is the upper bound of
; their product, and vice versa. And if one of the intervals is negative and
; the other is positive, the product of the positive upper bound and the
; negative lower bound is the lower bound of the product, and vice versa.
; After working out a few cases, we asked Robert Krug for an exhaustive case
; analysis which he provided in the form of a theorem for products akin to that
; shown above for sums, except instead of dealing with intervals as objects it
; just returned the two bounding rationals and the two relations. I believe
; Robert worked most of this out while developing the non-linear features of
; the community books in arithmetic-5/. Thank you Robert!
(defun bounds-of-product-< (x y)
(declare (xargs :guard (and (extended-rationalp x) (extended-rationalp y))))
; X and y are either rationals or nil or t, where nil represents negative
; infinity and t represents positive infinity. We determine whether x < y, and
; we (rather oddly) say that x < x, when x is either infinity.
(if (null x)
t
(if (eq x t)
(if (eq y t)
t
nil)
(if (null y)
nil
(if (eq y t)
t
(< x y))))))
(defun bounds-of-product-<= (x y)
(declare (xargs :guard (and (extended-rationalp x) (extended-rationalp y))))
; X and y are either rationals or nil or t, where nil represents negative
; infinity and t represents positive infinity. We determine whether x <= y.
(if (null x)
t
(if (eq x t)
(if (eq y t)
t
nil)
(if (null y)
nil
(if (eq y t)
t
(<= x y))))))
(defun bounds-of-product-* (x y)
(declare (xargs :guard (and (extended-rationalp x) (extended-rationalp y))))
; X and y are either rationals or nil or t, where nil represents negative
; infinity and t represents positive infinity. We compute (* x y).
(if (or (eql x 0)
(eql y 0))
0
(if (or (null x)
(eq x t)
(null y)
(eq y t))
(let ((signx (cond ((null x) nil)
((eq x t) t)
((< x 0) nil)
(t t)))
(signy (cond ((null y) nil)
((eq y t) t)
((< y 0) nil)
(t t))))
(eq signx signy))
(* x y))))
(defun bounds-of-product1 (lo-rel1 lo1 hi-rel1 hi1 lo-rel2 lo2 hi-rel2 hi2)
(declare (xargs :guard (and (booleanp lo-rel1)
(extended-rationalp lo1)
(booleanp hi-rel1)
(extended-rationalp hi1)
(booleanp lo-rel2)
(extended-rationalp lo2)
(booleanp hi-rel2)
(extended-rationalp hi2))))
; Warning: This function uses nil and t respectively to represent negative and
; positive infinity. Except for this function and the three extended
; arithmetic operators above, all other functions in the tau system obey the
; convention that both infinities are represented by nil.
; Given the different representations of the infinities, assume that lo1 <? x
; <? hi1 and lo2 <? y <? hi2, where the ``<?'' relations are controlled,
; respectively, by lo-rel1, hi-rel1, lo-rel2, and hi-rel2. We wish to
; determine bounds on (* x y). We return (mv lo-rel lo hi-rel hi).
; If you replace bounds-of-product-<, bounds-of-product-<=, and
; bounds-of-product-* by <, <=, and * respectively below, you get a version of
; this function that works when all the bounds are finite. Inspection shows
; that this is still a very messy function! Trying to handle the infinities by
; case splitting is daunting. (Abstractly, one could specialize the code below
; for each of the 2^8 cases -- each bound is either a finite rational or is
; infinite and each relation is either strict or not -- although one can cut it
; in half by exploiting the commutativity of multiplication.) That's why we
; extended the basic operations to handle infinities.
; The intellectual bulk of the following definition was derived by Robert
; Krug's, who worked out and verified an exhaustive case analysis. The proof
; of correctness of his original involved only about 5,000 subgoals whereas the
; proof of correctness of the full-fledged interval-based version involves
; about 40,000. But the case analysis and bounds is due to Robert. Thank you
; Robert!
(cond
((equal lo1 hi1)
(cond ((bounds-of-product-< 0 lo1)
(mv lo-rel2
(bounds-of-product-* lo1 lo2)
hi-rel2
(bounds-of-product-* lo1 hi2)))
((equal lo1 0)
(mv nil
0
nil
0))
(t
;; (bounds-of-product-< lo1 0)
(mv hi-rel2
(bounds-of-product-* lo1 hi2)
lo-rel2
(bounds-of-product-* lo1 lo2)))))
((equal lo2 hi2)
(cond ((bounds-of-product-< 0 lo2)
(mv lo-rel1
(bounds-of-product-* lo1 lo2)
hi-rel1
(bounds-of-product-* hi1 hi2)))
((equal lo2 0)
(mv nil
0
nil
0))
(t
;; (bounds-of-product-< lo2 0)
(mv hi-rel1
(bounds-of-product-* hi1 lo2)
lo-rel1
(bounds-of-product-* lo1 lo2)))))
((and (bounds-of-product-<= 0 lo1)
(bounds-of-product-<= 0 lo2))
(mv (and (or lo-rel1 lo-rel2)
(or lo-rel1 (not (equal lo1 0)))
(or lo-rel2 (not (equal lo2 0))))
(bounds-of-product-* lo1 lo2)
(or hi-rel1 hi-rel2)
(bounds-of-product-* hi1 hi2)
))
((and (bounds-of-product-<= hi1 0)
(bounds-of-product-<= hi2 0))
(mv (and (or hi-rel1 hi-rel2)
(or hi-rel1 (not (equal hi1 0)))
(or hi-rel2 (not (equal hi2 0))))
(bounds-of-product-* hi1 hi2)
(or lo-rel1 lo-rel2)
(bounds-of-product-* lo1 lo2)
))
((and (bounds-of-product-<= 0 lo1)
(bounds-of-product-<= hi2 0))
(mv (or hi-rel1 lo-rel2)
(bounds-of-product-* hi1 lo2)
(and (or lo-rel1 hi-rel2)
(or lo-rel1 (not (equal lo1 0)))
(or hi-rel2 (not (equal hi2 0))))
(bounds-of-product-* lo1 hi2)
))
((and (bounds-of-product-<= hi1 0)
(bounds-of-product-<= 0 lo2))
(mv (or lo-rel1 hi-rel2)
(bounds-of-product-* lo1 hi2)
(and (or hi-rel1 lo-rel2)
(or hi-rel1 (not (equal hi1 0)))
(or lo-rel2 (not (equal lo2 0))))
(bounds-of-product-* hi1 lo2)
))
((and (bounds-of-product-< lo1 0)
(bounds-of-product-< 0 hi1)
(bounds-of-product-<= 0 lo2))
(mv (or lo-rel1 hi-rel2)
(bounds-of-product-* lo1 hi2)
(or hi-rel1 hi-rel2)
(bounds-of-product-* hi1 hi2)
))
((and (bounds-of-product-< lo1 0)
(bounds-of-product-< 0 hi1)
(bounds-of-product-<= hi2 0))
(mv (or hi-rel1 lo-rel2)
(bounds-of-product-* hi1 lo2)
(or lo-rel1 lo-rel2)
(bounds-of-product-* lo1 lo2)
))
((and (bounds-of-product-<= 0 lo1)
(bounds-of-product-< lo2 0)
(bounds-of-product-< 0 hi2))
(mv (or hi-rel1 lo-rel2)
(bounds-of-product-* hi1 lo2)
(or hi-rel1 hi-rel2)
(bounds-of-product-* hi1 hi2)
))
((and (bounds-of-product-<= hi1 0)
(bounds-of-product-< lo2 0)
(bounds-of-product-< 0 hi2))
(mv (or lo-rel1 hi-rel2)
(bounds-of-product-* lo1 hi2)
(or lo-rel1 lo-rel2)
(bounds-of-product-* lo1 lo2)
))
(t
(cond ((and (bounds-of-product-< (bounds-of-product-* lo1 hi2)
(bounds-of-product-* hi1 lo2))
(bounds-of-product-< (bounds-of-product-* lo1 lo2)
(bounds-of-product-* hi1 hi2)))
(mv (or lo-rel1 hi-rel2)
(bounds-of-product-* lo1 hi2)
(or hi-rel1 hi-rel2)
(bounds-of-product-* hi1 hi2)
))
((and (bounds-of-product-< (bounds-of-product-* lo1 hi2)
(bounds-of-product-* hi1 lo2))
(equal (bounds-of-product-* lo1 lo2)
(bounds-of-product-* hi1 hi2)))
(mv (or lo-rel1 hi-rel2)
(bounds-of-product-* lo1 hi2)
(and (or lo-rel1 lo-rel2)
(or hi-rel1 hi-rel2))
(bounds-of-product-* lo1 lo2)
))
((and (bounds-of-product-< (bounds-of-product-* lo1 hi2)
(bounds-of-product-* hi1 lo2))
(bounds-of-product-< (bounds-of-product-* hi1 hi2)
(bounds-of-product-* lo1 lo2)))
(mv (or lo-rel1 hi-rel2)
(bounds-of-product-* lo1 hi2)
(or lo-rel1 lo-rel2)
(bounds-of-product-* lo1 lo2)
))
((and (equal (bounds-of-product-* lo1 hi2)
(bounds-of-product-* hi1 lo2))
(bounds-of-product-< (bounds-of-product-* lo1 lo2)
(bounds-of-product-* hi1 hi2)))
(mv (and (or lo-rel1 hi-rel2)
(or hi-rel1 lo-rel2))
(bounds-of-product-* lo1 hi2)
(or hi-rel1 hi-rel2)
(bounds-of-product-* hi1 hi2)
))
((and (equal (bounds-of-product-* lo1 hi2)
(bounds-of-product-* hi1 lo2))
(equal (bounds-of-product-* lo1 lo2)
(bounds-of-product-* hi1 hi2)))
(mv (and (or lo-rel1 hi-rel2)
(or hi-rel1 lo-rel2))
(bounds-of-product-* lo1 hi2)
(and (or lo-rel1 lo-rel2)
(or hi-rel1 hi-rel2))
(bounds-of-product-* lo1 lo2)
))
((and (equal (bounds-of-product-* lo1 hi2)
(bounds-of-product-* hi1 lo2))
(bounds-of-product-< (bounds-of-product-* hi1 hi2)
(bounds-of-product-* lo1 lo2)))
(mv (and (or lo-rel1 hi-rel2)
(or hi-rel1 lo-rel2))
(bounds-of-product-* lo1 hi2)
(or lo-rel1 lo-rel2)
(bounds-of-product-* lo1 lo2)
))
((and (bounds-of-product-< (bounds-of-product-* hi1 lo2)
(bounds-of-product-* lo1 hi2))
(bounds-of-product-< (bounds-of-product-* lo1 lo2)
(bounds-of-product-* hi1 hi2)))
(mv (or hi-rel1 lo-rel2)
(bounds-of-product-* hi1 lo2)
(or hi-rel1 hi-rel2)
(bounds-of-product-* hi1 hi2)
))
((and (bounds-of-product-< (bounds-of-product-* hi1 lo2)
(bounds-of-product-* lo1 hi2))
(equal (bounds-of-product-* lo1 lo2)
(bounds-of-product-* hi1 hi2)))
(mv (or hi-rel1 lo-rel2)
(bounds-of-product-* hi1 lo2)
(and (or lo-rel1 lo-rel2)
(or hi-rel1 hi-rel2))
(bounds-of-product-* lo1 lo2)
))
(t
;; (and (bounds-of-product-< (bounds-of-product-* hi1 lo2)
;; (bounds-of-product-* lo1 hi2))
;; (bounds-of-product-< (bounds-of-product-* hi1 hi2)
;; (bounds-of-product-* lo1 lo2)))
(mv (or hi-rel1 lo-rel2)
(bounds-of-product-* hi1 lo2)
(or lo-rel1 lo-rel2)
(bounds-of-product-* lo1 lo2)
))))))
(defun bounds-of-product (lo-rel1 lo1 hi-rel1 hi1 lo-rel2 lo2 hi-rel2 hi2)
(declare (xargs :guard (and (booleanp lo-rel1)
(or (null lo1) (real/rationalp lo1))
(booleanp hi-rel1)
(or (null hi1) (real/rationalp hi1))
(booleanp lo-rel2)
(or (null lo2) (real/rationalp lo2))
(booleanp hi-rel2)
(or (null hi2) (real/rationalp hi2)))))
; We coerce positive infinities to t, use the workhorse function, and then
; coerce positive infinities back to nil. We also insure that weak
; inequalities are used with the infinities. (The workhorse can return a
; strong inequality with an infinity, as happens with: (bounds-of-product1 10
; t nil nil 100 t 100 t) where we get back the lower bound of nil with the
; relation t.)
(let ((hi1 (if (null hi1) t hi1))
(hi2 (if (null hi2) t hi2)))
(mv-let (lo-rel lo hi-rel hi)
(bounds-of-product1 lo-rel1 lo1 hi-rel1 hi1
lo-rel2 lo2 hi-rel2 hi2)
(mv (if (null lo) nil lo-rel)
lo
(if (eq hi t) nil hi-rel)
(if (eq hi t) nil hi)))))
; Here is a theorem (and proof hint) establishing the correctness of the
; bounds-of-product function. The version of this theorem in which all bounds
; are finite is due to Robert Krug although we have changed some function names
; and introduced our conventional rel flag (of opposite parity than Robert's
; closedp).
; This theorem is a good application for ACL2(p). If you are running ACL2(p) the
; following two commands are helpful (and are no-ops in ordinary ACL2).
; (set-waterfall-parallelism t)
; (set-waterfall-printing :limited)
; We break the usual theorem into two parts: one theorem about the domain and
; the other about the bounds. The reason is that the bounds theorem breaks in
; the special cases that x and/or y is INTEGERP instead of just RATIONALP.
; This is because of some idiosyncracies of arithmetic-5's handling of
; non-linear.
(defun tau-bounder-* (int1 int2)
(declare (xargs :guard (and (tau-intervalp int1) (tau-intervalp int2))))
(let ((dom (domain-of-binary-arithmetic-function
(tau-interval-dom int1)
(tau-interval-dom int2))))
(mv-let (lo-rel lo hi-rel hi)
(bounds-of-product (tau-interval-lo-rel int1)
(tau-interval-lo int1)
(tau-interval-hi-rel int1)
(tau-interval-hi int1)
(tau-interval-lo-rel int2)
(tau-interval-lo int2)
(tau-interval-hi-rel int2)
(tau-interval-hi int2))
(make-tau-interval dom lo-rel lo hi-rel hi))))
(local (defthm |tau-intervalp tau-bounder-*|
(implies (and (tau-intervalp int1)
(tau-intervalp int2))
(tau-intervalp (tau-bounder-* int1 int2)))))
(local (defthm |tau-interval-dom tau-bounder-*|
(implies (and (tau-intervalp int1)
(tau-intervalp int2)
(or (equal (tau-interval-dom int1) 'integerp)
(equal (tau-interval-dom int1) 'rationalp))
(or (equal (tau-interval-dom int2) 'integerp)
(equal (tau-interval-dom int2) 'rationalp))
(not (equal (tau-interval-dom (tau-bounder-* int1 int2)) 'integerp)))
(equal (tau-interval-dom (tau-bounder-* int1 int2)) 'rationalp))
:hints (("Goal" :in-theory (disable bounds-of-product)))))
; Weakness: The following theorem could be strengthened by concluding, in
; addition, that if int1 and int2 have INTEGERP domains then the tau-bounder-*
; has an INTEGERP domain. As it stands below, we do not break out the cases
; and concluded only that if both int1 and int2 are either INTEGERP or
; RATIONALP then so is the product.
(local (encapsulate
()
(local (in-theory (disable
;; Horrible godawful hack.
the-floor-below
the-floor-above
REDUCE-RATIONAL-MULTIPLICATIVE-CONSTANT-<
REDUCE-MULTIPLICATIVE-CONSTANT-<
REDUCE-ADDITIVE-CONSTANT-<
INTEGERP-<-CONSTANT
CONSTANT-<-INTEGERP
remove-strict-inequalities
remove-weak-inequalities
prefer-positive-addends-<
|(< c (/ x)) positive c --- present in goal|
|(< c (/ x)) positive c --- obj t or nil|
|(< c (/ x)) negative c --- present in goal|
|(< c (/ x)) negative c --- obj t or nil|
|(< c (- x))|
|(< (/ x) c) positive c --- present in goal|
|(< (/ x) c) positive c --- obj t or nil|
|(< (/ x) c) negative c --- present in goal|
|(< (/ x) c) negative c --- obj t or nil|
|(< (/ x) (/ y))|
|(< (- x) c)|
|(< (- x) (- y))|
intervalp-rules
REDUCE-RATIONALP-+
REDUCE-RATIONALP-*
RATIONALP-MINUS-X
META-RATIONALP-CORRECT
SIMPLIFY-PRODUCTS-GATHER-EXPONENTS-EQUAL
REDUCE-MULTIPLICATIVE-CONSTANT-EQUAL
REDUCE-ADDITIVE-CONSTANT-EQUAL
PREFER-POSITIVE-ADDENDS-EQUAL
EQUAL-OF-PREDICATES-REWRITE
|(equal c (/ x))|
|(equal c (- x))|
|(equal (/ x) c)|
|(equal (/ x) (/ y))|
|(equal (- x) c)|
|(equal (- x) (- y))|
|(< (/ x) 0)|
|(< (* x y) 0)|
(:TYPE-PRESCRIPTION IN-TAU-INTERVALP)
(:TYPE-PRESCRIPTION TAU-INTERVALP)
(:TYPE-PRESCRIPTION TAU-INTERVAL-DOMAINP)
NORMALIZE-FACTORS-GATHER-EXPONENTS
SIMPLIFY-TERMS-SUCH-AS-AX+BX-<-0-RATIONAL-REMAINDER
SIMPLIFY-TERMS-SUCH-AS-AX+BX-<-0-RATIONAL-COMMON
SIMPLIFY-SUMS-EQUAL
|(< 0 (/ x))|
|(< 0 (* x y))|
INTEGERP-MINUS-X
(:TYPE-PRESCRIPTION BOOLEANP)
|(< 0 (* x y)) rationalp (* x y)|
META-INTEGERP-CORRECT
default-plus-1
default-plus-2
default-divide
member
)))
(local (SET-DEFAULT-HINTS
'((and stable-under-simplificationp
'(:nonlinearp t))
(and stable-under-simplificationp
(not (cw "Jared-hint: re-enabling slow rules.~%"))
'(:in-theory (enable jared-disables)))
(and stable-under-simplificationp
(not (cw "Jared-hint: splitting into cases.~%"))
'(:cases ((and (< 0 x) (< 0 y))
(and (< 0 x) (equal 0 y))
(and (< 0 x) (< y 0))
(and (equal 0 x) (< 0 y))
(and (equal 0 x) (equal 0 y))
(and (equal 0 x) (< y 0))
(and (< x 0) (< 0 y))
(and (< x 0) (equal 0 y))
(and (< x 0) (< y 0)))))
(and stable-under-simplificationp
(NONLINEARP-DEFAULT-HINT++
ID STABLE-UNDER-SIMPLIFICATIONP HIST NIL)))))
(defthm |in-tau-intervalp tau-bounder-*|
(implies (and (tau-intervalp int1)
(tau-intervalp int2)
(or (equal (tau-interval-dom int1) 'integerp)
(equal (tau-interval-dom int1) 'rationalp))
(or (equal (tau-interval-dom int2) 'integerp)
(equal (tau-interval-dom int2) 'rationalp))
(in-tau-intervalp x int1)
(in-tau-intervalp y int2))
(in-tau-intervalp (* x y) (tau-bounder-* int1 int2))))))
(encapsulate ()
(local (in-theory (disable tau-bounder-*)))
(defthm tau-bounder-*-correct
(implies (and (tau-intervalp int1)
(tau-intervalp int2)
(or (equal (tau-interval-dom int1) 'integerp)
(equal (tau-interval-dom int1) 'rationalp))
(or (equal (tau-interval-dom int2) 'integerp)
(equal (tau-interval-dom int2) 'rationalp))
(in-tau-intervalp x int1)
(in-tau-intervalp y int2))
(and (tau-intervalp (tau-bounder-* int1 int2))
(in-tau-intervalp (* x y) (tau-bounder-* int1 int2))
(implies (not (equal (tau-interval-dom (tau-bounder-* int1 int2)) 'integerp))
(equal (tau-interval-dom (tau-bounder-* int1 int2)) 'rationalp))))
; Robert Krug first defined the function (akin to our tau-bounder-*) that
; computed the upper and lower bounds on a product given the bounds on the two
; factors. He proved it correct and used the hint below, which he said was
; necessary only for some of the cases but which he said was more convenient to
; provide at the top. Robert also points out that tau-bounder-*-correct
; theorem is a good example for David Rager's work on parallelism. One might
; try it with:
; (set-waterfall-parallelism t)
; (set-waterfall-printing :limited)
:rule-classes
((:rewrite)
(:forward-chaining
:corollary
(implies (and (tau-intervalp int1)
(tau-intervalp int2)
(equal (tau-interval-dom int1) 'integerp)
(equal (tau-interval-dom int2) 'integerp)
(in-tau-intervalp x int1)
(in-tau-intervalp y int2))
(and (tau-intervalp (tau-bounder-* int1 int2))
(implies (not (equal (tau-interval-dom (tau-bounder-* int1 int2)) 'integerp))
(equal (tau-interval-dom (tau-bounder-* int1 int2)) 'rationalp))
(in-tau-intervalp (* x y) (tau-bounder-* int1 int2))))
:trigger-terms ((tau-bounder-* int1 int2)))
(:forward-chaining
:corollary
(implies (and (tau-intervalp int1)
(tau-intervalp int2)
(equal (tau-interval-dom int1) 'integerp)
(equal (tau-interval-dom int2) 'rationalp)
(in-tau-intervalp x int1)
(in-tau-intervalp y int2))
(and (tau-intervalp (tau-bounder-* int1 int2))
(implies (not (equal (tau-interval-dom (tau-bounder-* int1 int2)) 'integerp))
(equal (tau-interval-dom (tau-bounder-* int1 int2)) 'rationalp))
(in-tau-intervalp (* x y) (tau-bounder-* int1 int2))))
:trigger-terms ((tau-bounder-* int1 int2)))
(:forward-chaining
:corollary
(implies (and (tau-intervalp int1)
(tau-intervalp int2)
(equal (tau-interval-dom int1) 'rationalp)
(equal (tau-interval-dom int2) 'integerp)
(in-tau-intervalp x int1)
(in-tau-intervalp y int2))
(and (tau-intervalp (tau-bounder-* int1 int2))
(implies (not (equal (tau-interval-dom (tau-bounder-* int1 int2)) 'integerp))
(equal (tau-interval-dom (tau-bounder-* int1 int2)) 'rationalp))
(in-tau-intervalp (* x y) (tau-bounder-* int1 int2))))
:trigger-terms ((tau-bounder-* int1 int2)))
(:forward-chaining
:corollary
(implies (and (tau-intervalp int1)
(tau-intervalp int2)
(equal (tau-interval-dom int1) 'rationalp)
(equal (tau-interval-dom int2) 'rationalp)
(in-tau-intervalp x int1)
(in-tau-intervalp y int2))
(and (tau-intervalp (tau-bounder-* int1 int2))
(implies (not (equal (tau-interval-dom (tau-bounder-* int1 int2)) 'integerp))
(equal (tau-interval-dom (tau-bounder-* int1 int2)) 'rationalp))
(in-tau-intervalp (* x y) (tau-bounder-* int1 int2))))
:trigger-terms ((tau-bounder-* int1 int2)))
)))
; The proof above takes 15 minutes and generates a lot of subgoals.
; [Jared]: I got it down to 180 seconds with stupid AP hacking. (I think this
; could be significantly improved by not just brute forcing the proof,
; eventually).
; Subgoals: 40,661
; Time: 920.78 seconds (prove: 917.26, print: 3.49, other: 0.02)
; Prover steps counted: 53057929
; The restrictions on the domains of int1 and int2 are necessary. The theorem
; does not hold for complex numbers. The imaginary number i, i.e., #c(0 1), is
; in the interval beteen 0 and 10 shown for int1 and int2 below, but (* i i) =
; -1 is not in the product interval, 0 to 100.
; (set-guard-checking :none)
;
; (let ((int1 (make-tau-interval 'acl2-numberp nil 0 nil 10))
; (int2 (make-tau-interval 'acl2-numberp nil 0 nil 10))
; (x #c(0 1))
; (y #c(0 1)))
; (implies (and (tau-intervalp int1)
; (tau-intervalp int2)
; ; (or (equal (tau-interval-dom int1) 'integerp) ; delete these hyps
; ; (equal (tau-interval-dom int1) 'rationalp))
; ; (or (equal (tau-interval-dom int2) 'integerp)
; ; (equal (tau-interval-dom int2) 'rationalp))
; (in-tau-intervalp x int1)
; (in-tau-intervalp y int2))
; (in-tau-intervalp (* x y) (tau-bounder-* int1 int2))))
; NIL
; -----------------------------------------------------------------
; - - the unary minus operator
; Since (- x) = (* -1 x), we can define:
(defconst *tau-interval-for--1*
(make-tau-interval 'integerp nil -1 nil -1))
(defun tau-bounder-- (int)
(declare (xargs :guard (tau-intervalp int)))
(tau-bounder-* *tau-interval-for--1* int))
(defthm tau-bounder---correct
(implies (and (tau-intervalp int1)
(or (equal (tau-interval-dom int1) 'integerp)
(equal (tau-interval-dom int1) 'rationalp))
(in-tau-intervalp x int1))
(and (tau-intervalp (tau-bounder-- int1))
(in-tau-intervalp (unary-- x) (tau-bounder-- int1))
(implies (not (equal (tau-interval-dom (tau-bounder-- int1)) 'integerp))
(equal (tau-interval-dom (tau-bounder-- int1)) 'rationalp))))
:rule-classes
((:rewrite)
(:forward-chaining
:corollary
(implies (and (tau-intervalp int1)
(equal (tau-interval-dom int1) 'integerp)
(in-tau-intervalp x int1))
(and (tau-intervalp (tau-bounder-- int1))
(in-tau-intervalp (unary-- x) (tau-bounder-- int1))
(equal (tau-interval-dom (tau-bounder-- int1)) 'integerp)))
:trigger-terms ((tau-bounder-- int1)))
(:forward-chaining
:corollary
(implies (and (tau-intervalp int1)
(equal (tau-interval-dom int1) 'rationalp)
(in-tau-intervalp x int1))
(and (tau-intervalp (tau-bounder-- int1))
(in-tau-intervalp (unary-- x) (tau-bounder-- int1))
(equal (tau-interval-dom (tau-bounder-- int1)) 'rationalp)))
:trigger-terms ((tau-bounder-* int1 int2)))
))
; -----------------------------------------------------------------
; / -- the reciprocal operator
; The reason we care about this case is that we wish to bound (floor x y). We
; know (floor x y) <= x/y which is (* x (/ y)), and we know how to bound a
; product. So what remains is how to bound the reciprocal of y given the
; bounds on y.
; If x occupies a finite rational interval that lies STRICTLY above or below 0,
; e.g.,
; 0 < lo <? x <? hi
; or
; lo <? x <? hi < 0
; then we can bound (/ x) by inverting and switching the bounds of x:
; (/ hi) <? (/ x) <? (/ lo)
; However, things are more complicated if x can take on the value 0, either
; because it is bounded weakly above or below 0 or because the interval spans
; 0. If a rational interval includes 0 then (/ x) cannot be bounded in either
; direction: as x approaches 0 from above, (/ x) becomes infinitely positive;
; as x approaches 0 from below, (/ x) becomes infinitely negative. (These
; observations depend on x being allowed to take on any rational value.) What
; happens if one of the endpoints of the interval is 0? For example what is
; the range of (/ x) if 0 <= x <= 7? One might think it is 1/7 <= (/ x) <=
; infinity. But in fact it is 0 <= (/ x) <= infinity because when x = 0, (/ x)
; is (unfortunately) 0 rather than infinity.
; If x is limited to the integers, the situation is more interesting:
; -1 <= (/ x) <= 1 for integral values of x.
(defun bounds-of-reciprocal (x dom lo-rel lo hi-rel hi)
(declare (ignore x))
(declare (xargs :guard (and (symbolp dom)
(booleanp lo-rel)
(or (null lo) (real/rationalp lo))
(booleanp hi-rel)
(or (null hi) (real/rationalp hi))
(or (null lo) (null hi) (<= lo hi)))))
; This function returns the bounds on (/ x) given bounds on x. It is assumed x
; and the bounds, lo and hi, are in the domain specified by dom, which is
; either INTEGERP or RATIONALP. Furthermore, when dom is INTEGERP, the two
; relations are weak (nil).
; The following table summarizes this definition. We use -oo and +oo for the
; two infinities. However, when dom is INTEGERP we can't get an infinity out of
; reciprocal. That is, the biggest thing we can get is 1, because (/ 1) = 1,
; and the smallest is -1.
; Lines [2,5,8,11] are irrelevant when dom is INTEGERP because the relations
; are weak and those lines involve strong relations.
; [1] -oo <= x <= 0 -oo <= (/ x) <= 0
; [2] -oo <= x < 0 -oo <= (/ x) < 0
; [3] -oo <= x <? hi < 0 (/ hi) <? (/ x) < 0
; [4] lo <? x <? hi < 0 (/ hi) <? (/ x) <? (/ lo)
; [5] lo <? x < 0 -oo <= (/ x) <? (/ lo)
; [6] lo <? x <= 0 -oo <= (/ x) <= 0
; [7] 0 <= x <= +oo 0 <= (/ x) <= +oo
; [8] 0 < x <= +oo 0 < (/ x) <= +oo
; [9] 0 < lo <? x <= +oo 0 < (/ x) <? (/ lo)
;[10] 0 < lo <? x <? hi (/ hi) <? (/ x) <? (/ lo)
;[11] 0 < x <? hi (/ hi) <? (/ x) <= +oo
;[12] 0 <= x <? hi 0 <= (/ x) <= +oo
; [*] all other cases -oo <= (/ x) <= +oo
(let ((-oo (if (eq dom 'integerp) -1 nil))
(+oo (if (eq dom 'integerp) +1 nil)))
(cond
((null lo)
(cond ((null hi)
(mv nil -oo nil +oo)) ; [*]
((< hi 0)
(mv hi-rel (/ hi) t 0)) ; [3]
((equal hi 0)
(mv nil -oo hi-rel 0)) ; [1,2]
(t
(mv nil -oo nil +oo)))) ; [*]
((< 0 lo)
(cond
((null hi)
(mv t 0 lo-rel (/ lo))) ; [9]
(t
(mv hi-rel (/ hi) lo-rel (/ lo))))) ; [10]
((equal 0 lo)
(cond ((null hi)
(mv lo-rel 0 nil +oo)) ; [7,8]
((equal 0 hi)
(mv nil 0 nil 0))
(lo-rel
(mv hi-rel (/ hi) nil +oo)) ; [11]
(t
(mv nil 0 nil +oo)))) ; [12]
((or (null hi)
(< 0 hi))
(mv nil -oo nil +oo)) ; [*]
((equal 0 hi)
(cond
(hi-rel
(mv nil -oo lo-rel (/ lo))) ; [5]
(t
(mv nil -oo nil 0)))) ; [6]
(t
(mv hi-rel (/ hi) lo-rel (/ lo)))))) ; [4]
(defun tau-bounder-/ (int)
(declare (xargs :guard (tau-intervalp int)))
(mv-let (lo-rel lo hi-rel hi)
(bounds-of-reciprocal 0
(tau-interval-dom int)
(tau-interval-lo-rel int)
(tau-interval-lo int)
(tau-interval-hi-rel int)
(tau-interval-hi int))
(make-tau-interval 'rationalp lo-rel lo hi-rel hi)))
(local (defthm |tau-intervalp tau-bounder-/|
(implies (tau-intervalp int1)
(tau-intervalp (tau-bounder-/ int1)))))
(local (defthm |tau-interval-dom tau-bounder-/|
(equal (tau-interval-dom (tau-bounder-/ int1)) 'rationalp)
:hints (("Goal" :in-theory (disable bounds-of-reciprocal)))))
(local (defthm |in-tau-intervalp tau-bounder-/|
(implies (and (tau-intervalp int1)
(or (equal (tau-interval-dom int1) 'integerp)
(equal (tau-interval-dom int1) 'rationalp))
(in-tau-intervalp x int1))
(in-tau-intervalp (/ x) (tau-bounder-/ int1)))))
(defthm tau-bounder-/-correct
(implies (and (tau-intervalp int1)
(or (equal (tau-interval-dom int1) 'integerp)
(equal (tau-interval-dom int1) 'rationalp))
(in-tau-intervalp x int1))
(and (tau-intervalp (tau-bounder-/ int1))
(in-tau-intervalp (/ x) (tau-bounder-/ int1))
(equal (tau-interval-dom (tau-bounder-/ int1)) 'rationalp)))
:hints (("Goal" :in-theory (disable tau-bounder-/)))
:rule-classes
((:rewrite)
(:forward-chaining
:corollary
(implies (and (tau-intervalp int1)
(equal (tau-interval-dom int1) 'integerp)
(in-tau-intervalp x int1))
(and (tau-intervalp (tau-bounder-/ int1))
(equal (tau-interval-dom (tau-bounder-/ int1)) 'rationalp)
(in-tau-intervalp (/ x) (tau-bounder-/ int1))))
:trigger-terms ((tau-bounder-/ int1)))
(:forward-chaining
:corollary
(implies (and (tau-intervalp int1)
(equal (tau-interval-dom int1) 'rationalp)
(in-tau-intervalp x int1))
(and (tau-intervalp (tau-bounder-/ int1))
(equal (tau-interval-dom (tau-bounder-/ int1)) 'rationalp)
(in-tau-intervalp (/ x) (tau-bounder-/ int1))))
:trigger-terms ((tau-bounder-/ int1)))
))
; -----------------------------------------------------------------
; FLOOR
; Intuitively the smallest value of (floor x y) is gotten by taking the
; smallest value of x and flooring it with the biggest value of y, and the
; biggest value of floor is gotten by taking the biggest value of x and
; flooring it with the smallest value of y. But what about signs, 0, etc?
; Certainly the naive idea above is wrong: suppose 2 <= x <= 25 and -3 <= y <=
; 7, then the actual range of (floor x y) is -25 <= (floor x y) <= +25. But
; the naive idea says that the smallest value of (floor x y) is (floor 2 25),
; which is 0. Wrong. Rather than think it through, we just use the fact that
; (floor x y) is the integer under (/ x y) = (* x (/ y)) and compute the
; integer bounds on the latter expression.
(local
(defthm floor-tau-bounder-domain
(integerp (floor x y))))
(defun tau-bounder-floor (int1 int2)
(declare (xargs :guard (and (tau-intervalp int1) (tau-intervalp int2))
:guard-hints (("Goal" :cases ((tau-intervalp (tau-bounder-* int1 (tau-bounder-/ int2))))
:in-theory (disable tau-bounder-* tau-bounder-/))
("Subgoal 2" :use (
(:instance |tau-intervalp tau-bounder-*|
(int1 int1)
(int2 (tau-bounder-/ int2)))
(:instance |tau-intervalp tau-bounder-/|
(int1 int2))))
)
))
(let ((int
(tau-bounder-* int1 (tau-bounder-/ int2))))
(make-tau-interval 'integerp
nil
(if (tau-interval-lo int)
(floor (tau-interval-lo int) 1)
nil)
nil
(if (tau-interval-hi int)
(floor (tau-interval-hi int) 1)
nil))))
; This is the first of our proofs in the ``second style.'' The idea is not to
; re-expose the (horrendous) details of tau-bounder-* or any of the other
; pre-verified bounders. We want the proof to appeal to their correctness
; proofs. With that in mind, we disable the functions concerned (see the e/d
; below). We disable the executable-counterpart of make-tau-interval so that
; constant intervals, like (make-tau-interval 'integerp nil nil nil nil) which
; arises in one case above), don't block our use of the intervalp-make-tau-interval
; and in-tau-intervalp-make-tau-interval rules.
; The idea in these second style proofs is that the new bounder,
; tau-bounder-floor expands to expose a composition of old bounders and/or
; make-tau-intervals. Then the previously proved results apply to the resulting
; intervalp, in-tau-intervalp, and interval-dom expressions which are now applied
; to previously verified bounders.
; However, there is a problem. The (in-tau-intervalp (make-tau-interval ...))
; exposed by the expansion of tau-bounder-floor below will lead us to the
; goal (among others):
; (FLOOR X Y) <= (TAU-INTERVAL-LO (TAU-BOUNDER-* INT1 (TAU-BOUNDER-/ INT2))).
; This particular goal is a bit tricky because it involves an ``extra step,'' namely
; knowing that (floor x y) <= (* x (/ y)), which is known to arithmetic-5. So let's
; simplify the discussion by assuming that step is taken care of. How do we prove
; the resulting:
; (* X (/ Y)) <= (TAU-INTERVAL-LO (TAU-BOUNDER-* INT1 (TAU-BOUNDER-/ INT2))).
; where we know that X is in INT1 and Y is in INT2.
; The relevant lemma about tau-bounder-* concludes with:
; (in-tau-intervalp (* x y) (tau-bounder-* int1 int2))
; From this fact we could conclude
; (IN-TAU-INTERVALP (* X (/ Y)) (TAU-BOUNDER-* INT1 (TAU-BOUNDER-/ INT2))) [1]
; and from there we could get an inequality relating (* X (/ Y)) to the
; INTERVAL-LO of the TAU-BOUNDER-*. But since [1] isn't in the theorem
; and isn't a subgoal, we have to somehow create it and the only way I can
; think of to do that is forward-chain triggered by a term that will be in
; the problem, namely:
; (TAU-BOUNDER-* INT1 (TAU-BOUNDER-/ INT2)).
; But that requires finding choices for the free variables x and y.
; So the general strategy of the ``second style'' of proof is to do everything
; by forward chaining. From the presence of (TAU-BOUNDER-/ INT2) we forward
; chain to (IN-TAU-INTERVALP (/ Y) (TAU-BOUNDER-/ INT2)), guessing Y by the presence
; of (IN-TAU-INTERVALP Y INT2) given in the problem. From the presence of
; (TAU-BOUNDER-* INT1 (TAU-BOUNDER-/ INT2)) we forward chain to
; (IN-TAU-INTERVALP (* X (/ Y)) INT1 (TAU-BOUNDER-/ INT2)), guessing X from
; (IN-TAU-INTERVALP X INT1) given in the problem and guessing (/ Y) from the just
; derived IN-TAU-INTERVALP.
; Once these basic IN-TAU-INTERVALP conditions are derived, we can use :LINEAR lemmas
; like that in IN-TAU-INTERVALP-RULES:
; (implies (and (in-tau-intervalp x int)
; x
; (tau-intervalp int)
; (tau-interval-lo int))
; (<= (tau-interval-lo int) x))
; which, note, have a free x in them. That free x is selected via the first
; hyp above, which is present because of forward-chaining.
(defthm tau-bounder-floor-correct
(implies (and (tau-intervalp int1)
(tau-intervalp int2)
(or (equal (tau-interval-dom int1) 'integerp)
(equal (tau-interval-dom int1) 'rationalp))
(or (equal (tau-interval-dom int2) 'integerp)
(equal (tau-interval-dom int2) 'rationalp))
(in-tau-intervalp x int1)
(in-tau-intervalp y int2))
(and (tau-intervalp (tau-bounder-floor int1 int2))
(in-tau-intervalp (floor x y) (tau-bounder-floor int1 int2))
(equal (tau-interval-dom (tau-bounder-floor int1 int2)) 'integerp)
))
:hints (("Goal"
:in-theory
(disable tau-intervalp
in-tau-intervalp
tau-bounder-*
tau-bounder-/
(:executable-counterpart make-tau-interval))))
:rule-classes
((:rewrite)
(:forward-chaining
:corollary
(implies (and (tau-intervalp int1)
(tau-intervalp int2)
(equal (tau-interval-dom int1) 'integerp)
(equal (tau-interval-dom int2) 'integerp)
(in-tau-intervalp x int1)
(in-tau-intervalp y int2))
(and (tau-intervalp (tau-bounder-floor int1 int2))
(equal (tau-interval-dom (tau-bounder-floor int1 int2)) 'integerp)
(in-tau-intervalp (floor x y) (tau-bounder-floor int1 int2))
))
:trigger-terms ((tau-bounder-floor int1 int2)))
(:forward-chaining
:corollary
(implies (and (tau-intervalp int1)
(tau-intervalp int2)
(equal (tau-interval-dom int1) 'integerp)
(equal (tau-interval-dom int2) 'rationalp)
(in-tau-intervalp x int1)
(in-tau-intervalp y int2))
(and (tau-intervalp (tau-bounder-floor int1 int2))
(equal (tau-interval-dom (tau-bounder-floor int1 int2)) 'integerp)
(in-tau-intervalp (floor x y) (tau-bounder-floor int1 int2))
))
:trigger-terms ((tau-bounder-floor int1 int2)))
(:forward-chaining
:corollary
(implies (and (tau-intervalp int1)
(tau-intervalp int2)
(equal (tau-interval-dom int1) 'rationalp)
(equal (tau-interval-dom int2) 'integerp)
(in-tau-intervalp x int1)
(in-tau-intervalp y int2))
(and (tau-intervalp (tau-bounder-floor int1 int2))
(equal (tau-interval-dom (tau-bounder-floor int1 int2)) 'integerp)
(in-tau-intervalp (floor x y) (tau-bounder-floor int1 int2))
))
:trigger-terms ((tau-bounder-floor int1 int2)))
(:forward-chaining
:corollary
(implies (and (tau-intervalp int1)
(tau-intervalp int2)
(equal (tau-interval-dom int1) 'rationalp)
(equal (tau-interval-dom int2) 'rationalp)
(in-tau-intervalp x int1)
(in-tau-intervalp y int2))
(and (tau-intervalp (tau-bounder-floor int1 int2))
(equal (tau-interval-dom (tau-bounder-floor int1 int2)) 'integerp)
(in-tau-intervalp (floor x y) (tau-bounder-floor int1 int2))
))
:trigger-terms ((tau-bounder-floor int1 int2)))
))
; -----------------------------------------------------------------
; MOD
; Since (mod x y) = (- x (* (floor x y) y)), the domain of MOD is given
; by domain-of-binary-arithmetic-function:
(defun lower-bound-> (a-rel a b-rel b)
(declare (xargs :guard (and (booleanp a-rel)
(or (null a) (rationalp a))
(booleanp b-rel)
(or (null b) (rationalp b)))))
; See Specification of Bound Comparisons, above.
(if (null a)
nil
(if (null b)
t
(if (and a-rel (not b-rel))
(>= a b)
(> a b)))))
(defun upper-bound-< (a-rel a b-rel b)
(declare (xargs :guard (and (booleanp a-rel)
(or (null a) (rationalp a))
(booleanp b-rel)
(or (null b) (rationalp b)))))
; See Specification of Bound Comparisons, above.
(if (null a)
nil
(if (null b)
t
(if (and a-rel (not b-rel))
(<= a b)
(< a b)))))
(defun combine-intervals1 (dom1 lo-rel1 lo1 hi-rel1 hi1
dom2 lo-rel2 lo2 hi-rel2 hi2)
(declare (xargs :guard (and (symbolp dom1)
(booleanp lo-rel1)
(or (null lo1) (rationalp lo1))
(booleanp hi-rel1)
(or (null hi1) (rationalp hi1))
(symbolp dom2)
(booleanp lo-rel2)
(or (null lo2) (rationalp lo2))
(booleanp hi-rel2)
(or (null hi2) (rationalp hi2)))))
(mv-let
(lo-rel lo)
(if (lower-bound-> lo-rel1 lo1 lo-rel2 lo2)
(mv lo-rel2 lo2)
(mv lo-rel1 lo1))
(mv-let
(hi-rel hi)
(if (upper-bound-< hi-rel1 hi1 hi-rel2 hi2)
(mv hi-rel2 hi2)
(mv hi-rel1 hi1))
(make-tau-interval (domain-of-binary-arithmetic-function dom1 dom2)
lo-rel lo hi-rel hi))))
(defun squeeze-k (upper-boundp rel k)
(declare (xargs :guard (and (booleanp upper-boundp)
(booleanp rel)
(or (null k) (rationalp k)))))
; K is either NIL (the appopriate infinity) or a rational. Consider some
; interval with INTEGERP domain bounded (above or below as per upper-boundp) by
; rel and k. If k is non-nil, we squeeze the given bound as per:
; Table A:
; upper-boundp rel meaning squeezed k'
; t t (< x k) (<= x k') (- (ceiling k 1) 1)
; t nil (<= x k) (<= x k') (floor k 1)
; nil t (< k x) (<= k' x) (+ (floor k 1) 1)
; nil nil (<= k x) (<= k' x) (ceiling k 1)
; Programming Note: When k is a non-integer rational,
; (- (ceiling k 1) 1) = (floor k 1), and thus
; (+ (floor k 1) 1) = (ceiling k 1)
; so the table would be:
; Table B: Non-Integer Rational k:
; upper-boundp rel meaning squeezed k'
; t t (< x k) (<= x k') (floor k 1)
; t nil (<= x k) (<= x k') (floor k 1)
; nil t (< k x) (<= k' x) (ceiling k 1)
; nil nil (<= k x) (<= k' x) (ceiling k 1)
; But when k is an integer, the table is:
; Table C: Integer k:
; upper-boundp rel meaning squeezed k'
; t t (< x k) (<= x k') (- k 1)
; t nil (<= x k) (<= x k') k
; nil t (< k x) (<= k' x) (+ k 1)
; nil nil (<= k x) (<= k' x) k
; We actually code Tables B and C and test which to use with (integerp k),
; because we believe it is faster than Table A because whenever k is an integer
; we avoid calls of floor or ceiling.
(if k
(if (integerp k)
(if rel
(if upper-boundp (- k 1) (+ k 1))
k)
(if upper-boundp
(floor k 1)
(ceiling k 1)))
nil))
(defun make-tau-interval-with-integerp-fix (dom lo-rel lo hi-rel hi)
(declare (xargs :guard (and (symbolp dom)
(booleanp lo-rel)
(or (null lo) (rationalp lo))
(booleanp hi-rel)
(or (null hi) (rationalp hi)))))
(cond ((eq dom 'integerp)
(cond ((and (null lo-rel)
(or (null lo) (integerp lo))
(null hi-rel)
(or (null hi) (integerp hi)))
(make-tau-interval 'integerp nil lo nil hi))
(t (let ((lo (squeeze-k nil lo-rel lo))
(hi (squeeze-k t hi-rel hi)))
(make-tau-interval 'integerp nil lo nil hi)))))
(t (make-tau-interval dom lo-rel lo hi-rel hi))))
(defun tau-bounder-mod (int1 int2)
(declare (xargs :guard (and (tau-intervalp int1)
(tau-intervalp int2))))
(let ((domx (tau-interval-dom int1))
(lo-relx (tau-interval-lo-rel int1))
(lox (tau-interval-lo int1))
(hi-relx (tau-interval-hi-rel int1))
(hix (tau-interval-hi int1))
(domy (tau-interval-dom int2))
(lo-rely (tau-interval-lo-rel int2))
(loy (tau-interval-lo int2))
(hi-rely (tau-interval-hi-rel int2))
(hiy (tau-interval-hi int2)))
(cond
((and (rationalp loy)
(if lo-rely
(<= 0 loy)
(< 0 loy)))
; If y is strictly positive, then (mod x y) lies in the interval between 0 and
; y, which means it is bound above (strictly) by hiy.
(make-tau-interval-with-integerp-fix (domain-of-binary-arithmetic-function domx domy)
nil 0 t hiy))
((and (rationalp hiy)
(if hi-rely
(<= hiy 0)
(< hiy 0)))
; If y is strictly negative, then (mod x y) lies in the interval
; between y and 0 which means it is bound below (strictly) by loy.
(make-tau-interval-with-integerp-fix (domain-of-binary-arithmetic-function domx domy)
t loy nil 0))
(t
; Otherwise, y is not strictly positive and it is not strictly negative, which
; means that y is sometimes 0. Thus, (mod x y) might return x and hence the
; bounds must include those for the interval containing x, and y might be
; negative or positive, in which case (mod x y) is bound below (strictly) by
; loy and above (strictly) by hiy. So we combine the two intervals.
(combine-intervals1 domx lo-relx lox hi-relx hix
domy lo-rely loy hi-rely hiy)))))
; Note that (mod x y) can return a complex-rational when its arguments are
; complex-rationals. The conclusion of the theorem would compare that
; complex-rational to two rationals. But I don't want to think about that!
; So, we restrict our attention to intervals over the rationals (or integers).
; As a result of this restriction, the domain returned by the general purpose
; bounds-of-mod is the same as that computed by domain-of-sum-or-product, as
; noted in our theorem below.
(encapsulate
()
(local (in-theory (disable jared-disables)))
(local (in-theory (disable (:t not-integerp-4b)
(:t not-integerp-3b)
(:t not-integerp-2b)
(:t not-integerp-1b)
;; integerp-mod-1
;; integerp-mod-2
;; rationalp-mod
mod-nonnegative
mod-nonpositive
mod-zero
mod-positive
mod-negative
MOD-X-Y-=-X
MOD-X-Y-=-X+Y
MOD-X-Y-=-X-Y
;; mod-bounds-1
;; mod-bounds-2
the-floor-below
the-floor-above
default-times-1
default-times-2
default-plus-1
default-plus-2
REDUCE-RATIONAL-MULTIPLICATIVE-CONSTANT-<
|(< c (/ x)) positive c --- present in goal|
|(< c (/ x)) positive c --- obj t or nil|
|(< c (/ x)) negative c --- present in goal|
|(< c (/ x)) negative c --- obj t or nil|
|(< c (- x))|
|(< (/ x) c) positive c --- present in goal|
|(< (/ x) c) positive c --- obj t or nil|
|(< (/ x) c) negative c --- present in goal|
|(< (/ x) c) negative c --- obj t or nil|
|(< (/ x) (/ y))|
|(< (- x) c)|
|(< (- x) (- y))|
rationalp-x
PREFER-POSITIVE-EXPONENTS-SCATTER-EXPONENTS-<-2
PREFER-POSITIVE-EXPONENTS-SCATTER-EXPONENTS-EQUAL
default-car
default-cdr
cancel-mod-+
meta-integerp-correct
meta-rationalp-correct
acl2-numberp-x
in-tau-intervalp-rules
intervalp-rules
)))
(local (set-default-hints
'((and stable-under-simplificationp
'(:nonlinearp t))
(and stable-under-simplificationp
(NONLINEARP-DEFAULT-HINT++
ID STABLE-UNDER-SIMPLIFICATIONP HIST NIL))
(and stable-under-simplificationp
(not (cw "Jared-hint: re-enabling slower rules.~%"))
'(:in-theory (enable jared-disables))))))
(defthm tau-bounder-mod-correct
(implies (and (tau-intervalp int1)
(tau-intervalp int2)
(or (equal (tau-interval-dom int1) 'integerp)
(equal (tau-interval-dom int1) 'rationalp))
(or (equal (tau-interval-dom int2) 'integerp)
(equal (tau-interval-dom int2) 'rationalp))
(in-tau-intervalp x int1)
(in-tau-intervalp y int2))
(and (tau-intervalp (tau-bounder-mod int1 int2))
(in-tau-intervalp (mod x y) (tau-bounder-mod int1 int2))
(implies (not (equal (tau-interval-dom (tau-bounder-mod int1 int2)) 'integerp))
(equal (tau-interval-dom (tau-bounder-mod int1 int2)) 'rationalp))
))
:rule-classes
((:rewrite)
(:forward-chaining
:corollary
(implies (and (tau-intervalp int1)
(tau-intervalp int2)
(equal (tau-interval-dom int1) 'integerp)
(equal (tau-interval-dom int2) 'integerp)
(in-tau-intervalp x int1)
(in-tau-intervalp y int2))
(and (tau-intervalp (tau-bounder-mod int1 int2))
(implies (not (equal (tau-interval-dom (tau-bounder-mod int1 int2)) 'integerp))
(equal (tau-interval-dom (tau-bounder-mod int1 int2)) 'rationalp))
(in-tau-intervalp (mod x y) (tau-bounder-mod int1 int2))
))
:trigger-terms ((tau-bounder-mod int1 int2)))
(:forward-chaining
:corollary
(implies (and (tau-intervalp int1)
(tau-intervalp int2)
(equal (tau-interval-dom int1) 'integerp)
(equal (tau-interval-dom int2) 'rationalp)
(in-tau-intervalp x int1)
(in-tau-intervalp y int2))
(and (tau-intervalp (tau-bounder-mod int1 int2))
(implies (not (equal (tau-interval-dom (tau-bounder-mod int1 int2)) 'integerp))
(equal (tau-interval-dom (tau-bounder-mod int1 int2)) 'rationalp))
(in-tau-intervalp (mod x y) (tau-bounder-mod int1 int2))
))
:trigger-terms ((tau-bounder-mod int1 int2)))
(:forward-chaining
:corollary
(implies (and (tau-intervalp int1)
(tau-intervalp int2)
(equal (tau-interval-dom int1) 'rational)
(equal (tau-interval-dom int2) 'integerp)
(in-tau-intervalp x int1)
(in-tau-intervalp y int2))
(and (tau-intervalp (tau-bounder-mod int1 int2))
(implies (not (equal (tau-interval-dom (tau-bounder-mod int1 int2)) 'integerp))
(equal (tau-interval-dom (tau-bounder-mod int1 int2)) 'rationalp))
(in-tau-intervalp (mod x y) (tau-bounder-mod int1 int2))
))
:trigger-terms ((tau-bounder-mod int1 int2)))
(:forward-chaining
:corollary
(implies (and (tau-intervalp int1)
(tau-intervalp int2)
(equal (tau-interval-dom int1) 'rationalp)
(equal (tau-interval-dom int2) 'rationalp)
(in-tau-intervalp x int1)
(in-tau-intervalp y int2))
(and (tau-intervalp (tau-bounder-mod int1 int2))
(implies (not (equal (tau-interval-dom (tau-bounder-mod int1 int2)) 'integerp))
(equal (tau-interval-dom (tau-bounder-mod int1 int2)) 'rationalp))
(in-tau-intervalp (mod x y) (tau-bounder-mod int1 int2))
))
:trigger-terms ((tau-bounder-mod int1 int2)))
)))
; -----------------------------------------------------------------
; The Arithmetic-Logical Functions
; The logical functions always take and return integers. Our theorems require
; this. We thus know that the relations, e.g., ``lo-rel'' and ``hi-rel'',
; bounding the various quantities are always weak. Hence, our functions for
; computing bounds and our theorems about those functions don't traffic in
; relations. For example, ``bounds-of-logand'' takes four argument, the bounds
; on x and y, not eight; it returns two results, not four. (However, the
; theorems still use (<? nil lo ...), for example, rather than (<= lo ...)
; because lo might be a nil representing negative infinity.)
; To help us keep track of these reduced signatures, we add an ``i'' for
; ``integer'' to the bounds functions and theorem names, e.g.,
; ibounds-for-logand and logand-tau-bounder-ibounds. The functions concerned
; are:
; LOGAND
; LOGNOT
; LOGIOR
; LOGORC1
; LOGEQV
; LOGXOR
; EXPT2
; ASH
; If others are added, make sure they traffic only in integers!
; -----------------------------------------------------------------
; LOGAND
; We first prove a variety of lemmas to handle special cases. Some of these
; lemmas restrict the domains of x and y to INTEGERP and some don't. But our
; main result will apply only to INTEGERP domains, INTEGERP bounds, and weak
; relations.
; By the way, it is known that INTEGERP (logand x y), no matter what x and y
; are.
; If x is in the interval 0 <= minx <= x <= maxx and
; y is in the interval 0 <= miny <= y <= maxy, then
; then (logand x y) is in
; the interval 0 <= (logand x y) <= (min maxx maxy).
; Note that we can't raise the lower bound because if x and y have no bits in
; common (as in x=4 and y=8), their logand is in fact 0.
(local
(defthm LOGAND-tau-bounder-both-nonnegative
(implies (and (<= 0 minx) (<= minx x) (<= x maxx)
(<= 0 miny) (<= miny y) (<= y maxy))
(and (<= 0
(logand x y))
(<= (logand x y)
(min maxx maxy))))
:rule-classes (:rewrite :linear)))
; If both x and y are negative integers, then x+y < (logand x y) <= (min x y).
(defun shifts-to-all-ones (x)
(declare (xargs :guard (integerp x)))
; Assuming x < 0, how many times must we shift x to make it -1? This turns out
; to be either (log2 (- x)) or (+ 1 (log2 (- x))), depending on whether (- x)
; is a power of 2 -- but I haven't proved that and don't need it.
(if (and (integerp x)
(< x 0))
(if (equal x -1)
0
(+ 1 (shifts-to-all-ones (ash x -1))))
0))
(local
(encapsulate
nil
(local
(defthm expt-2-shifts-to-all-ones
(implies (and (integerp x) (< x 0))
(<= (- (expt 2 (shifts-to-all-ones x)))
x))
:rule-classes :linear))
(local
(defthm logand-both-negative-lower-bound
(implies (and (integerp x)
(integerp y)
(< x 0)
(< y 0))
(<= (- (expt 2 (max (shifts-to-all-ones x)
(shifts-to-all-ones y))))
(logand x y)))
:hints
(("Goal" :in-theory (e/d (logand)(|(logand (floor x 2) (floor y 2))| ))))
:rule-classes nil))
(local
(defthm logand-both-negative
(implies (and (integerp x)
(integerp y)
(< x 0)
(< y 0))
(and (<= (- (expt 2 (max (shifts-to-all-ones x)
(shifts-to-all-ones y))))
(logand x y))
(<= (logand x y) (min x y))))
:hints (("Goal" :use logand-both-negative-lower-bound))
:rule-classes nil))
(local
(defun shifts-to-all-ones-monotonic-hint (x y)
(if (and (integerp x)
(< x 0)
(integerp y)
(< y 0))
(if (equal x -1)
0
(if (equal y -1)
0
(shifts-to-all-ones-monotonic-hint (ash x -1) (ash y -1))))
0)))
(local
(defthm shifts-to-all-ones-monotic
(implies (and (integerp x)
(integerp y)
(< y 0)
(<= x y))
(<= (shifts-to-all-ones y)
(shifts-to-all-ones x)))
:hints (("Goal" :induct (shifts-to-all-ones-monotonic-hint x y)))
:rule-classes nil))
(defthm logand-tau-bounder-both-negative
(implies (and (integerp x)
(integerp y)
(integerp minx)
(integerp miny)
(integerp maxx)
(integerp maxy)
(<= minx x) (<= x maxx) (< maxx 0)
(<= miny y) (<= y maxy) (< maxy 0))
(and (<= (- (expt 2 (max (shifts-to-all-ones minx)
(shifts-to-all-ones miny))))
(logand x y))
(<= (logand x y) (min maxx maxy))))
:hints (("Goal" :use ((:instance logand-both-negative)
(:instance shifts-to-all-ones-monotic
(x minx)
(y x))
(:instance shifts-to-all-ones-monotic
(x miny)
(y y)))))
:rule-classes (:rewrite :linear))
))
(local
(defthm logand-tau-bounder-both-either-lower-bound
(implies (and (integerp x)
(integerp y)
(integerp minx)
(integerp miny)
(<= minx x)
(<= miny y))
(<= (min 0 (- (expt 2 (max (shifts-to-all-ones minx)
(shifts-to-all-ones miny)))))
(logand x y)))
:hints (("Goal"
:in-theory (disable max)
:cases ((and (< x 0)(< y 0)))))
:rule-classes (:rewrite :linear)))
; The following bound is not very good. Intuitively it ought to be (min maxx
; maxy). But suppose x is -1 and maxx is 2 and y is 8 and maxy is 10: Then the
; (logand x y) = y = 8, but (min maxx maxy) = 2. Oops. The problem is that if
; x and y are allowed to range all over, then (logand x y) might be x or y as
; the other takes on the value -1. But if we have to describe the bounds in
; terms of maxx and maxy, then the best we can do is be ready for either x or
; y, e.g., (max maxx maxy).
(local
(defthm logand-tau-bounder-both-either-upper-bound
(implies (and (integerp x)
(integerp y)
(<= x maxx)
(<= y maxy))
(<= (logand x y) (max maxx maxy)))
:hints (("Goal"
:cases ((and (< x 0)(< y 0)))))
:rule-classes (:rewrite :linear)))
; Unfortunately, the analytical bounds derived above are sometimes not very
; good. We therefore use an empirical method to compute the bounds for logand
; over small intervals.
(local (include-book "find-minimal-2d"))
(defun find-minimal-logand2 (x loy hiy min)
(declare (xargs :measure (nfix (- (+ 1 (ifix hiy)) (ifix loy)))
:guard (and (integerp x)
(integerp loy)
(integerp hiy)
(or (null min) (integerp min)))
:verify-guards nil))
(cond
((mbe :logic (not (and (integerp loy)
(integerp hiy)))
:exec nil)
min)
((> loy hiy) min)
(t (find-minimal-logand2
x
(+ 1 loy) hiy
(if (or (null min)
(< (logand x loy) min))
(logand x loy)
min)))))
(defun find-minimal-logand1 (lox hix loy hiy min)
(declare (xargs :measure (nfix (- (+ 1 (ifix hix)) (ifix lox)))
:guard (and (integerp lox)
(integerp hix)
(integerp loy)
(integerp hiy)
(or (null min) (integerp min)))
:verify-guards nil))
(cond
((mbe :logic (not (and (integerp lox)
(integerp hix)))
:exec nil)
min)
((> lox hix) min)
(t (find-minimal-logand1
(+ 1 lox) hix
loy hiy
(find-minimal-logand2 lox loy hiy min)))))
; This is the wrapper that initializes the running minimal, min, to nil. But
; all our lemmas except the last will be about the two recursive functions
; above.
(defun find-minimal-logand (lox hix loy hiy)
(declare (xargs :guard (and (integerp lox)
(integerp hix)
(integerp loy)
(integerp hiy))
:verify-guards nil))
(find-minimal-logand1 lox hix loy hiy nil))
(local
(defthm find-minimal-logand-correct
(implies (and (integerp lox)
(integerp hix)
(integerp loy)
(integerp hiy)
(integerp x)
(<= lox x)
(<= x hix)
(integerp y)
(<= loy y)
(<= y hiy))
(and (integerp (find-minimal-logand lox hix loy hiy))
(<= (find-minimal-logand lox hix loy hiy)
(logand x y))))
:hints (("Goal" :use (:functional-instance
find-minimal-correct
(fmla (lambda (x y) (logand x y)))
(find-minimal2 find-minimal-logand2)
(find-minimal1 find-minimal-logand1)
(find-minimal find-minimal-logand))))))
(in-theory (disable find-minimal-logand))
(local (include-book "find-maximal-2d"))
(defun find-maximal-logand2 (x loy hiy max)
(declare (xargs :measure (nfix (- (+ 1 (ifix hiy)) (ifix loy)))
:guard (and (integerp x)
(integerp loy)
(integerp hiy)
(or (null max) (integerp max)))
:verify-guards nil))
(cond
((mbe :logic (not (and (integerp loy)
(integerp hiy)))
:exec nil)
max)
((> loy hiy) max)
(t (find-maximal-logand2
x
(+ 1 loy) hiy
(if (or (null max)
(> (logand x loy) max))
(logand x loy)
max)))))
(defun find-maximal-logand1 (lox hix loy hiy max)
(declare (xargs :measure (nfix (- (+ 1 (ifix hix)) (ifix lox)))
:guard (and (integerp lox)
(integerp hix)
(integerp loy)
(integerp hiy)
(or (null max) (integerp max)))
:verify-guards nil))
(cond
((mbe :logic (not (and (integerp lox)
(integerp hix)))
:exec nil)
max)
((> lox hix) max)
(t (find-maximal-logand1
(+ 1 lox) hix
loy hiy
(find-maximal-logand2 lox loy hiy max)))))
; This is the wrapper that initializes the running maximal, max, to nil. But
; all our lemmas except the last will be about the two recursive functions
; above.
(defun find-maximal-logand (lox hix loy hiy)
(declare (xargs :guard (and (integerp lox)
(integerp hix)
(integerp loy)
(integerp hiy))
:verify-guards nil))
(find-maximal-logand1 lox hix loy hiy nil))
; A nice way to demo the effectiveness of guard verification is to admit these
; functions with :verify-guards nil and run
; (time$ (find-minimal-logand 0 1023 0 1023))
; then do the verify-guards below and repeat the timing. You get about a 14x
; speed up.
(verify-guards find-minimal-logand2)
(verify-guards find-minimal-logand1)
(verify-guards find-minimal-logand)
(verify-guards find-maximal-logand2)
(verify-guards find-maximal-logand1)
(verify-guards find-maximal-logand)
(local
(defthm find-maximal-logand-correct
(implies (and (integerp lox)
(integerp hix)
(integerp loy)
(integerp hiy)
(integerp x)
(<= lox x)
(<= x hix)
(integerp y)
(<= loy y)
(<= y hiy))
(and (integerp (find-maximal-logand lox hix loy hiy))
(>= (find-maximal-logand lox hix loy hiy)
(logand x y))))
:hints (("Goal" :use (:functional-instance
find-maximal-correct
(fmla (lambda (x y) (logand x y)))
(find-maximal2 find-maximal-logand2)
(find-maximal1 find-maximal-logand1)
(find-maximal find-maximal-logand))))))
(in-theory (disable find-maximal-logand))
(defthm find-minimal-logand-below-find-maximal-logand
(implies (and (integerp lox)
(integerp hix)
(integerp loy)
(integerp hiy)
(<= lox hix)
(<= loy hiy))
(<= (find-minimal-logand lox hix loy hiy)
(find-maximal-logand lox hix loy hiy)))
:hints (("Goal"
:use
((:instance find-minimal-logand-correct
(x lox)
(y loy))
(:instance find-maximal-logand-correct
(x lox)
(y loy)))
:in-theory (disable find-minimal-logand-correct
find-maximal-logand-correct)))
:rule-classes :linear)
(defconst *logand-empirical-threshhold* (* 1024 1024))
(defun worth-computingp (lox hix loy hiy)
(declare (xargs :guard (and (integerp lox)
(integerp hix)
(integerp loy)
(integerp hiy))))
; This function is for heuristic purposes only. It determines whether we
; compute the exact minimal and maximal of logand over a pair of intervals by
; computing logand for each combination. The threshhold chosen above just
; allows us to compute the bounds on 10-bit x 10-bit logands. It takes a total
; of 0.066123 seconds to compute the two bounds on intervals of this size,
; running on a 2.6 GHz Intel Core i7 Macbook Pro in CCL. Note also that the
; way we actually compute the minimal and maximal (see bounds-of-logand below)
; is to compute them separately in two passes over the matrix. We could
; presumably save a little overhead by computing them in one pass.
(< (* (if (<= lox hix) (+ 1 (- hix lox)) 0)
(if (<= loy hiy) (+ 1 (- hiy loy)) 0))
*logand-empirical-threshhold*))
(in-theory (disable worth-computingp))
; This function assumes both domains are INTEGERp.
(defun tau-bounder-logand (int1 int2)
(declare (xargs :guard (and (tau-intervalp int1)
(tau-intervalp int2)
(equal (tau-interval-dom int1) 'integerp)
(equal (tau-interval-dom int2) 'integerp))))
(let ((lox (tau-interval-lo int1))
(hix (tau-interval-hi int1))
(loy (tau-interval-lo int2))
(hiy (tau-interval-hi int2)))
(cond
((and lox hix loy hiy (worth-computingp lox hix loy hiy))
(make-tau-interval
'integerp
nil
(find-minimal-logand lox hix loy hiy)
nil
(find-maximal-logand lox hix loy hiy)))
((and lox (<= 0 lox) ; x nonnegative
loy (<= 0 loy)) ; y nonnegative
(make-tau-interval 'integerp nil 0 nil (and hix hiy (min hix hiy))))
((and hix (< hix 0) ; x negative
hiy (< hiy 0)) ; y negative
(make-tau-interval
'integerp
nil
(and lox loy
(- (expt 2 (max (shifts-to-all-ones lox)
(shifts-to-all-ones loy)))))
nil
(min hix hiy)))
((and hix (<= hix 0) ; x negative
loy (<= 0 loy)) ; y nonnegative
(make-tau-interval 'integerp nil 0 nil hiy))
((and hiy (<= hiy 0) ; x nonnegative
lox (<= 0 lox)) ; y negative
(make-tau-interval 'integerp nil 0 nil hix))
((and lox (<= 0 lox)) ; x nonnegative, y is either
(make-tau-interval 'integerp nil 0 nil (and hix hiy (max hix hiy))))
((and loy (<= 0 loy)) ; y nonnegative, x is either
(make-tau-interval 'integerp nil 0 nil (and hix hiy (max hix hiy))))
(t
(make-tau-interval
'integerp
nil
(and lox loy (min 0 (- (expt 2 (max (shifts-to-all-ones lox)
(shifts-to-all-ones loy))))))
nil
(and hix hiy (max hix hiy)))))))
(local
(defthm min-max-properties
(and (<= (min x y) x)
(<= (min x y) y)
(<= x (max x y))
(<= y (max x y)))
:rule-classes :linear))
(local (defthm |tau-intervalp tau-bounder-logand|
(implies (and (tau-intervalp int1)
(tau-intervalp int2)
(equal (tau-interval-dom int1) 'integerp)
(equal (tau-interval-dom int2) 'integerp))
(tau-intervalp (tau-bounder-logand int1 int2)))
:hints (("Goal" :in-theory (disable min max)))
))
(local (defthm |tau-interval-dom tau-bounder-logand|
(equal (tau-interval-dom (tau-bounder-logand int1 int2)) 'integerp)))
(local (defthm |in-tau-intervalp tau-bounder-logand|
(implies (and (tau-intervalp int1)
(tau-intervalp int2)
(equal (tau-interval-dom int1) 'integerp)
(equal (tau-interval-dom int2) 'integerp)
(in-tau-intervalp x int1)
(in-tau-intervalp y int2))
(in-tau-intervalp (logand x y) (tau-bounder-logand int1 int2)))
:hints (("Goal" :in-theory (disable min max)))))
(defthm tau-bounder-logand-correct
(implies (and (tau-intervalp int1)
(tau-intervalp int2)
(equal (tau-interval-dom int1) 'integerp)
(equal (tau-interval-dom int2) 'integerp)
(in-tau-intervalp x int1)
(in-tau-intervalp y int2))
(and (tau-intervalp (tau-bounder-logand int1 int2))
(in-tau-intervalp (logand x y) (tau-bounder-logand int1 int2))
(equal (tau-interval-dom (tau-bounder-logand int1 int2)) 'integerp)
))
:hints (("Goal" :in-theory (disable tau-bounder-logand)))
:rule-classes
((:rewrite)
(:forward-chaining :trigger-terms ((tau-bounder-logand int1 int2)))
))
; These bounds aren't always very tight. See the essay On the Accuracy of the
; LOGAND Bounder at the end of this book.
; -----------------------------------------------------------------
; LOGNOT
(defun tau-bounder-lognot (int)
(declare (xargs :guard (tau-intervalp int)))
(let ((lo (tau-interval-lo int))
(hi (tau-interval-hi int)))
(make-tau-interval 'integerp
nil (if hi (- (- hi) 1) nil)
nil (if lo (- (- lo) 1) nil))))
(local (defthm |tau-intervalp tau-bounder-lognot|
(implies (and (tau-intervalp int)
(equal (tau-interval-dom int) 'integerp))
(and (tau-intervalp (tau-bounder-lognot int))
(equal (tau-interval-dom (tau-bounder-lognot int)) 'integerp)
))
:hints (("Goal" :in-theory (disable min max)))
))
(defthm tau-bounder-lognot-correct
(implies (and (tau-intervalp int1)
(equal (tau-interval-dom int1) 'integerp)
(in-tau-intervalp x int1))
(and (tau-intervalp (tau-bounder-lognot int1))
(in-tau-intervalp (lognot x) (tau-bounder-lognot int1))
(equal (tau-interval-dom (tau-bounder-lognot int1)) 'integerp)
))
:hints (("Goal" :in-theory (enable lognot)))
:rule-classes
((:rewrite)
(:forward-chaining :trigger-terms ((tau-bounder-lognot int1)))
))
; -----------------------------------------------------------------
; LOGIOR
; (Logior x y) = (lognot (logand (lognot x) (lognot y)))
; Therefore, we'll first try bounding it by composing our existing bounds functions.
; My old bound theorem for logior only worked for natp x and y. It was:
; (MIN MINX MINY) <= (LOGIOR X Y) <= (EXPT 2 (LOG2 (MAX MAXX MAXY))).
(defun tau-bounder-logior (int1 int2)
(declare (xargs :guard (and (tau-intervalp int1)
(equal (tau-interval-dom int1) 'integerp)
(tau-intervalp int2)
(equal (tau-interval-dom int2) 'integerp))
:guard-hints (("Goal" :use (
(:instance |tau-intervalp tau-bounder-lognot|
(int (tau-bounder-logand
(tau-bounder-lognot int1)
(tau-bounder-lognot int2))))
(:instance |tau-intervalp tau-bounder-logand|
(int1 (tau-bounder-lognot int1))
(int2 (tau-bounder-lognot int2)))
(:instance |tau-intervalp tau-bounder-lognot|
(int int1))
(:instance |tau-intervalp tau-bounder-lognot|
(int int2)))
:in-theory (disable tau-intervalp tau-bounder-lognot tau-bounder-logand)))))
(tau-bounder-lognot
(tau-bounder-logand
(tau-bounder-lognot int1)
(tau-bounder-lognot int2))))
(local (defthm |tau-intervalp tau-bounder-logior|
(implies (and (tau-intervalp int1)
(tau-intervalp int2)
(equal (tau-interval-dom int1) 'integerp)
(equal (tau-interval-dom int2) 'integerp))
(and (tau-intervalp (tau-bounder-logior int1 int2))
(equal (tau-interval-dom (tau-bounder-logior int1 int2)) 'integerp)
))
:hints (("Goal"
:in-theory
(e/d (logior)
(tau-intervalp
in-tau-intervalp
tau-bounder-logand
tau-bounder-lognot
lognot-logand ; rewrite rule in arithmetic-5 that folds logior
(:executable-counterpart make-tau-interval)))))
))
(defthm tau-bounder-logior-correct
(implies (and (tau-intervalp int1)
(tau-intervalp int2)
(equal (tau-interval-dom int1) 'integerp)
(equal (tau-interval-dom int2) 'integerp)
(in-tau-intervalp x int1)
(in-tau-intervalp y int2))
(and (tau-intervalp (tau-bounder-logior int1 int2))
(in-tau-intervalp (logior x y) (tau-bounder-logior int1 int2))
(equal (tau-interval-dom (tau-bounder-logior int1 int2)) 'integerp)
))
:hints
(("Goal"
:in-theory
(e/d (logior)
(tau-intervalp
in-tau-intervalp
tau-bounder-logand
tau-bounder-lognot
lognot-logand ; rewrite rule in arithmetic-5 that folds logior
(:executable-counterpart make-tau-interval)))))
:rule-classes
((:rewrite)
(:forward-chaining :trigger-terms ((tau-bounder-logior int1 int2)))
))
; -----------------------------------------------------------------
; LOGORC1
; (logorc1 x y) = (logior (lognot x) y)
(defun tau-bounder-logorc1 (int1 int2)
(declare (xargs :guard (and (tau-intervalp int1)
(equal (tau-interval-dom int1) 'integerp)
(tau-intervalp int2)
(equal (tau-interval-dom int2) 'integerp))
:guard-hints (("Goal" :use (
(:instance |tau-intervalp tau-bounder-logior|
(int1 (tau-bounder-lognot int1))
(int2 int2))
(:instance |tau-intervalp tau-bounder-lognot|
(int int1)))
:in-theory (disable tau-intervalp tau-bounder-logior tau-bounder-lognot)))))
(tau-bounder-logior
(tau-bounder-lognot int1)
int2))
(local (defthm |tau-intervalp tau-bounder-logorc1|
(implies (and (tau-intervalp int1)
(tau-intervalp int2)
(equal (tau-interval-dom int1) 'integerp)
(equal (tau-interval-dom int2) 'integerp))
(and (tau-intervalp (tau-bounder-logorc1 int1 int2))
(equal (tau-interval-dom (tau-bounder-logorc1 int1 int2)) 'integerp)
))
:hints (("Goal"
:in-theory
(e/d (logorc1)
(tau-intervalp
in-tau-intervalp
tau-bounder-logand
tau-bounder-lognot
|(logior y x)| ; commutative rule for logior
(:executable-counterpart make-tau-interval)))))
))
(defthm tau-bounder-logorc1-correct
(implies (and (tau-intervalp int1)
(tau-intervalp int2)
(equal (tau-interval-dom int1) 'integerp)
(equal (tau-interval-dom int2) 'integerp)
(in-tau-intervalp x int1)
(in-tau-intervalp y int2))
(and (tau-intervalp (tau-bounder-logorc1 int1 int2))
(in-tau-intervalp (logorc1 x y) (tau-bounder-logorc1 int1 int2))
(equal (tau-interval-dom (tau-bounder-logorc1 int1 int2)) 'integerp)
))
:hints
(("Goal"
:in-theory
(e/d (logorc1)
(tau-intervalp
in-tau-intervalp
tau-bounder-logior
tau-bounder-lognot
|(logior y x)| ; commutative rule for logior
(:executable-counterpart make-tau-interval)))))
:rule-classes
((:rewrite)
(:forward-chaining :trigger-terms ((tau-bounder-logorc1 int1 int2)))
))
; -----------------------------------------------------------------
; LOGEQV
; (logeqv x y) = (logand (logorc1 x y) (logorc1 y x))
(defun tau-bounder-logeqv (int1 int2)
(declare (xargs :guard (and (tau-intervalp int1)
(tau-intervalp int2)
(equal (tau-interval-dom int1) 'integerp)
(equal (tau-interval-dom int2) 'integerp))
:guard-hints (("Goal" :use (
(:instance |tau-intervalp tau-bounder-logand|
(int1 (tau-bounder-logorc1 int1 int2))
(int2 (tau-bounder-logorc1 int2 int1)))
(:instance |tau-intervalp tau-bounder-logorc1|
(int1 int1)
(int2 int2))
(:instance |tau-intervalp tau-bounder-logorc1|
(int1 int2)
(int2 int1)))
:in-theory (disable tau-intervalp tau-bounder-logand tau-bounder-logorc1)))))
(tau-bounder-logand
(tau-bounder-logorc1 int1 int2)
(tau-bounder-logorc1 int2 int1)))
(local (defthm |tau-intervalp tau-bounder-logeqv|
(implies (and (tau-intervalp int1)
(tau-intervalp int2)
(equal (tau-interval-dom int1) 'integerp)
(equal (tau-interval-dom int2) 'integerp))
(and (tau-intervalp (tau-bounder-logeqv int1 int2))
(equal (tau-interval-dom (tau-bounder-logeqv int1 int2)) 'integerp)
))
:hints (("Goal"
:in-theory
(e/d (logeqv)
(tau-intervalp
in-tau-intervalp
tau-bounder-logand
tau-bounder-logorc1
(:executable-counterpart make-tau-interval)))))
))
(defthm tau-bounder-logeqv-correct
(implies (and (tau-intervalp int1)
(tau-intervalp int2)
(equal (tau-interval-dom int1) 'integerp)
(equal (tau-interval-dom int2) 'integerp)
(in-tau-intervalp x int1)
(in-tau-intervalp y int2))
(and (tau-intervalp (tau-bounder-logeqv int1 int2))
(in-tau-intervalp (logeqv x y) (tau-bounder-logeqv int1 int2))
(equal (tau-interval-dom (tau-bounder-logeqv int1 int2)) 'integerp)
))
:hints
(("Goal"
:in-theory
(e/d (logeqv)
(tau-intervalp
in-tau-intervalp
logorc1
tau-bounder-logand
tau-bounder-logorc1
(:executable-counterpart make-tau-interval)))))
:rule-classes
((:rewrite)
(:forward-chaining :trigger-terms ((tau-bounder-logeqv int1 int2)))
))
; -----------------------------------------------------------------
; LOGXOR
; (logxor x y) = (lognot (logeqv x y))
(defun tau-bounder-logxor (int1 int2)
(declare (xargs :guard (and (tau-intervalp int1)
(tau-intervalp int2)
(equal (tau-interval-dom int1) 'integerp)
(equal (tau-interval-dom int2) 'integerp))
:guard-hints (("Goal" :use (
(:instance |tau-intervalp tau-bounder-lognot|
(int (tau-bounder-logeqv int1 int2)))
(:instance |tau-intervalp tau-bounder-logeqv|
(int1 int1)
(int2 int2)))
:in-theory (disable tau-intervalp tau-bounder-lognot tau-bounder-logeqv)))))
(tau-bounder-lognot
(tau-bounder-logeqv int1 int2)))
(defthm tau-bounder-logxor-correct
(implies (and (tau-intervalp int1)
(tau-intervalp int2)
(equal (tau-interval-dom int1) 'integerp)
(equal (tau-interval-dom int2) 'integerp)
(in-tau-intervalp x int1)
(in-tau-intervalp y int2))
(and (tau-intervalp (tau-bounder-logxor int1 int2))
(in-tau-intervalp (logxor x y) (tau-bounder-logxor int1 int2))
(equal (tau-interval-dom (tau-bounder-logxor int1 int2)) 'integerp)
))
:hints
(("Goal"
:in-theory
(e/d (logxor)
(tau-intervalp
in-tau-intervalp
logeqv
tau-bounder-lognot
tau-bounder-logeqv
(:executable-counterpart make-tau-interval)))))
:rule-classes
((:rewrite)
(:forward-chaining :trigger-terms ((tau-bounder-logxor int1 int2)))
))
; -----------------------------------------------------------------
; (EXPT 2 y)
; While we could bound (EXPT x y), we choose for the moment to focus on just
; what we need for ASH, which is (EXPT 2 y). The situations for x < 0 and (not
; (integerp x)) are messy. We assume y is an INTEGERP.
; Note that this ``i''-bounds function uncharacteristically returns the domain
; pair of (expt 2 y) as well. The trouble is that while y must be an integer
; and (expt 2 y) is an integer for non-negative y, (expt 2 y) is a rational for
; negative y.
(defun tau-bounder-expt2 (int2)
(declare (xargs :guard (and (tau-intervalp int2)
(equal (tau-interval-dom int2) 'integerp))))
(let ((loy (tau-interval-lo int2))
(hiy (tau-interval-hi int2)))
(if loy
(if (<= 0 loy)
(if hiy
(make-tau-interval 'integerp nil (expt 2 loy) nil (expt 2 hiy))
(make-tau-interval 'integerp nil (expt 2 loy) nil nil))
(if hiy
(make-tau-interval 'rationalp nil (expt 2 loy) nil (expt 2 hiy))
(make-tau-interval 'rationalp nil (expt 2 loy) nil nil)))
(if hiy
(make-tau-interval 'rationalp t 0 nil (expt 2 hiy))
(make-tau-interval 'rationalp t 0 nil nil)))))
; Warning: We only deal with (EXPT 2 y), for integerp y!
(defthm tau-bounder-expt2-correct
(implies (and (tau-intervalp int2)
(equal (tau-interval-dom int2) 'integerp)
(in-tau-intervalp y int2))
(and (tau-intervalp (tau-bounder-expt2 int2))
(in-tau-intervalp (expt 2 y) (tau-bounder-expt2 int2))
(implies (not (equal (tau-interval-dom (tau-bounder-expt2 int2)) 'integerp))
(equal (tau-interval-dom (tau-bounder-expt2 int2)) 'rationalp))
))
:rule-classes
((:rewrite)
(:forward-chaining :trigger-terms ((tau-bounder-expt2 int2)))
))
; -----------------------------------------------------------------
; (EXPT r i)
; Both parameters of this tau-bounder are intervals. So tau-system can accept
; it. It recognizes specific case r=2 and delegates it to the previous bounder
; and returns the entire rational set in the general case.
(defun tau-bounder-expt (intr inti)
(declare (xargs :guard (and (tau-intervalp intr)
(tau-intervalp inti)
(equal (tau-interval-dom intr) 'integerp)
(equal (tau-interval-dom inti) 'integerp))))
(if
(and
(equal (tau-interval-lo intr) 2)
(equal (tau-interval-hi intr) 2))
(tau-bounder-expt2 inti)
(make-tau-interval 'rationalp nil nil nil nil)))
; Warning: We only deal with (EXPT 2 i), for integerp i!
(defthm tau-bounder-expt-correct
(implies (and (tau-intervalp intr)
(equal (tau-interval-dom intr) 'integerp)
(in-tau-intervalp r intr)
(tau-intervalp inti)
(equal (tau-interval-dom inti) 'integerp)
(in-tau-intervalp i inti))
(and (tau-intervalp (tau-bounder-expt intr inti))
(in-tau-intervalp (expt r i) (tau-bounder-expt intr inti))
(implies (not (equal (tau-interval-dom (tau-bounder-expt intr inti)) 'integerp))
(equal (tau-interval-dom (tau-bounder-expt intr inti)) 'rationalp))
))
:rule-classes
((:rewrite)
(:forward-chaining :trigger-terms ((tau-bounder-expt intr inti)))
))
; -----------------------------------------------------------------
; ASH
; (ash x y) = (floor (* (ifix x) (expt 2 y)) 1)
(defun tau-bounder-ash (int1 int2)
(declare (xargs :guard (and (tau-intervalp int1)
(tau-intervalp int2)
(equal (tau-interval-dom int1) 'integerp)
(equal (tau-interval-dom int2) 'integerp))))
(tau-bounder-floor
(tau-bounder-* int1
(tau-bounder-expt2 int2))
(make-tau-interval 'integerp nil 1 nil 1)))
; Weakness: See the little essay immediately below on why I need the :use hint!
; It opens a raft of difficulties.
(defthm tau-bounder-ash-correct
(implies (and (tau-intervalp int1)
(tau-intervalp int2)
(equal (tau-interval-dom int1) 'integerp)
(equal (tau-interval-dom int2) 'integerp)
(in-tau-intervalp x int1)
(in-tau-intervalp y int2))
(and (tau-intervalp (tau-bounder-ash int1 int2))
(in-tau-intervalp (ash x y) (tau-bounder-ash int1 int2))
(equal (tau-interval-dom (tau-bounder-ash int1 int2)) 'integerp)
))
:hints
(("Goal"
:use ((:instance tau-bounder-floor-correct
(x (* x (expt 2 y)))
(int1 (TAU-BOUNDER-* INT1 (TAU-BOUNDER-EXPT2 INT2)))
(y 1)
(int2 (MAKE-TAU-INTERVAL 'INTEGERP NIL 1 NIL 1))))
:in-theory
(e/d (ash)
(tau-intervalp
in-tau-intervalp
tau-bounder-floor
tau-bounder-*
tau-bounder-expt2
tau-bounder-floor-correct ; <--- since I :use it above
(:executable-counterpart make-tau-interval)))))
:rule-classes
((:rewrite)
(:forward-chaining :trigger-terms ((tau-bounder-ash int1 int2)))
))
; On Why We Need the :USE Hint in the Proof of that the ASH Bounder is Correct
; Consider just the proof of the first concluding conjunct above,
; (TAU-INTERVALP (TAU-BOUNDER-ASH INT1 INT2)).
; After opening up, this is:
; (TAU-INTERVALP (TAU-BOUNDER-FLOOR
; (TAU-BOUNDER-* INT1
; (TAU-BOUNDER-EXPT2 INT2))
; (MAKE-TAU-INTERVAL 'INTEGERP NIL 1 NIL 1)))
; We mean to prove this by :forward-chaining from the three correctness lemmas
; for FLOOR, *, and EXPT2. To use the TAU-BOUNDER-FLOOR-CORRECT theorem, we
; need to have derived:
; [1] (tau-intervalp (TAU-BOUNDER-* INT1 (TAU-BOUNDER-EXPT2 INT2)))
; [2] (tau-intervalp (MAKE-TAU-INTERVAL 'INTEGERP NIL 1 NIL 1))
; We could get [2] in one of several ways but we don't pursue those
; improvements because we'd still be blocked from our ultimate ASH goal by the
; problems raised by [1]. But to elaborate slightly on fixing [2], one
; solution would be to add the :forward-chaining rule:
; (defthm make-tau-interval-x-x
; (implies (integerp x)
; (and (equal (tau-interval-dom (make-tau-interval 'integerp nil x nil x)) 'integerp)
; (tau-intervalp (make-tau-interval 'integerp nil x nil x))
; (in-tau-intervalp x (make-tau-interval 'integerp nil x nil x))))
; :rule-classes ((:forward-chaining :trigger-terms ((make-tau-interval 'integerp nil x nil x)))))
; Alternatively we could rely on the fact that forward-chaining evaluates
; ground terms and [2] is a ground term, but we have (:executable-counterpart
; make-tau-interval) disabled in these ``second style'' proofs so as to simplify
; the application of our basic rules for tearing apart IN-TAU-INTERVALP and
; INTERVALP of MAKE-TAU-INTERVAL expressions. (If ground MAKE-TAU-INTERVALs are
; evaluated, we'd have to recode some of those rules so that, for example
; (in-tau-intervalp x (cons dom (cons (cons lo-rel lo) (cons hi-rel hi)))) is
; expanded appropriately.)
; But as noted, we don't try to fix [2] because we're still blocked by [1].
; What does it take to get [1]? To apply tau-bounder-*-correct we need to
; know that its second argument, (TAU-BOUNDER-EXPT2 INT2), is an intervalp
; [which we can get via tau-bounder-expt2-correct] and we need to know that
; the domain of (TAU-BOUNDER-EXPT2 INT2) is either 'INTEGERP or 'RATIONALP.
; Now in fact the domain of (TAU-BOUNDER-EXPT2 INT2) is one of those two, but
; we don't know which. (If Y is non-negative, the domain is INTEGERP and if Y
; is negative it is RATIONALP -- but this fact, like the fact that
; tau-bounder-* is weak because it doesn't tell us when the product is an
; INTEGERP -- is not proved here.) But even we had proved this fact, it
; wouldn't help us because we don't know the sign of Y, forward-chaining
; doesn't do case analysis, and forward-chaining cannot propagage disjunctions.
; The only way to win here is to :USE some rule that puts the necessary
; conditions into the theorem and let the simplifier consider the cases.
; This perhaps calls into question the whole ``second style'' of proof, based
; on forward-chaining from previously proved correctness theorems. However,
; revisit the discussion on the role of forward-chaining in the comment
; preceding tau-bounder-floor-correct.
; -----------------------------------------------------------------
; There are no events beyond this point
; -----------------------------------------------------------------
; On the Accuracy of the LOGAND Bounder
;
; [This essay was written to be somewhat self-contained and so repeats some basic
; facts before getting to the gist of the matter.]
;
; Tau is capable of tracking finite intervals. For example, suppose x is known
; to be an integer that lies between two known integer constants, e.g., 0 <= x <= 15.
; This information is treated by tau as a ``type'' in the sense that it can
; be propagated by signatures and other rules available to the system.
;
; Suppose the lower and upper bounds of the interval on x are given by the
; integers lox (``low x'') and hix (``high x''), and the bounds on y are
; loy and hiy. Obviously then, the bounds on (+ x y) are lox+loy and hix+hiy.
; Note that the bounds on (+ x y) are constants, computed by summing the constant
; bounds on the inputs x and y.
;
; In the same fashion, we wish to bound (logand x y).
;
; A little bit of analysis can provide some rough bounds. For example, if both
; input intervals are non-negative (i.e., 0 <= lox and 0 <= loy), then
; (logand x y) can be no smaller than 0 and no larger than the minimum of hix and
; hiy. If both input intervals are strictly negative, (logand x y) is negative
; and can be no smaller than
;
; (- (expt 2 (max (shifts-to-all-ones lox)
; (shifts-to-all-ones loy))))
;
; and no greater than the minimum of hix and hiy. Here, shifts-to-all-ones is
; the function that determines how many times its argument must be right
; shifted to produce -1 (and is thus ceiling of the log base 2 of the negative
; of its argument; e.g., (shifts-to-all-ones -9) = 4).
;
; Using this analysis, if -7 <= x <= -1 and -6 <= y <= -2, then
; -8 <= (logand x y) <= -2.
;
; One can similarly work out analytical bounds for when one of the inputs is
; strictly negative and the other is non-negative, and for when both can range
; over both the negatives and non-negatives.
;
; I have worked out such analytical bounds and proved that they are sufficient
; to actually contain all values of the relevant logand expressions. However,
; my analytical bounds of logand can be quite inaccurate. [Footnote: I say
; ``my analytical bounds'' because one could probably work out more accurate
; ones and, indeed, I illustrate the approach below but don't pursue it.]
;
; To give an example of the inaccuracy of my bounds, consider a simple case
; where both x and y range over non-negative values. Analytically we say that
; (logand x y) in this cases ranges from 0 to the minimal of the upper bounds of
; x and y. This is obvious since logand will only turn some bits off.
;
; But now consider this example:
;
; lox = (+ (expt 2 31) 8)
; hix = (+ (expt 2 31) 8 7)
; loy = (+ (expt 2 30) 8)
; hiy = (+ (expt 2 30) 8 7) = 1073741839
;
; The analytical answer says 0 <= (logand x y) <= 1073741839. But actually, we
; can see that 8 <= (logand x y) <= 15. Thus both our lower analytical bound and
; our upper analytical bound can be wildly inaccurate.
;
; Part of the project of computing bounds for logand was to address the
; inaccuracy of this analysis. Notice that despite the magnitude of the bounds
; above, there are only 8 possible values of x and 8 possible values of y.
; Hence, there are only 64 combinations and it is straightforward to evaluate
; logand on those 64 combinations to compute the actual bounds. I call this the
; ``empirical'' method instead of the (my) ``analytical'' method.
;
; Of course, the empirical method cannot be applied to problems beyond a certain
; small size (as measured by the product of the widths of the two input
; intervals). This size, called the ``empirical threshhold,'' is set currently
; at 1024^2 or 1,048,576. This allows us to bound 10-bit by 10-bit logands
; perfectly. The time it takes to compute both the upper and lower bounds for an
; interval of this size is 0.066123 seconds on a Macbook Pro running CCL on an
; 2.6 GHz Intel Core i7. Of course, we might wish to lower the threshhold to
; avoid the empirical computation if we decide that it is just too expensive in
; actual proofs. My gut feeling is that since this only happens when we
; encounter LOGANDs, we can probably afford the 10-bit by 10-bit test.
;
; The approach we adopted in tau-bounder-logand is to first determine the size
; of the problem. If it is small enough, we use the empirical method.
; Otherwise, we use the analytic method. We call this combined scheme the
; ``heuristic method.''
;
; In tau-bounder-logand-correct, above, I prove that the heuristic bounds are
; logically sufficient: they are always wide enough to include the right answer.
;
; Two ill-formed questions swirl in my mind. It would be nice if someone with a
; more analytical mindset (or a sense of having more time!) made the two
; questions more precise so they could actually be answered. One question is:
; if we didn't use the empirical method to make some of our bounds perfect,
; how bad would it be? Of course, the example above shows that the error can be
; about as bad as you can imagine. Indeed, if the two inputs have exactly one
; bit in common, that bit determines both the upper and lower bounds of the interval
; (they're equal) and all the other bits in the two inputs contribute only to the
; size of the error! But really, how often do these bad cases happen over random
; input intervals? This clearly has a precise, abstract answer but I haven't
; pursued it.
;
; The second question is: how much more accurate do it get if we use the
; empirical method on the small problems? This could help us decide whether the
; empirical method is worth its cost.
;
; Of course, the more meaningful cost/benefit question is: how many more
; theorems (that we're likely to run into) would we prove due to the use of the
; empirical method on small problems? In the absence of an answer to that more
; meaningful question, an accuracy analysis of tau-bounder-logand is sort of
; irrelevant or, at least to me, of secondary importance. That's why I'm
; satisfied with a proof of correctness and a half-baked experimental
; determination that the empirical methods sort of seems to probably improve
; accuracy by a meaningful amount.
;
; With these apologies, let me now present my experimental setup and results.
;
; Let k be some natural number. In the tests below, I use k=5, 10, 15, ..., 50.
; I call k the ``radius'' of a test. In a test of radius k, I consider all
; combinations of two intervals whose upper and lower bounds are between -k and
; k. I call this the test set. More precisely, the test set for radius k is the
;
; {(make-tau-interval 'integerp nil lo nil hi) : (-k <= lo <= k) & (lo <= hi <= k)}
;
; Note: hi must be at least lo for the interval to be legal.
;
; The test for radius k then chooses every possible combination of intervals from
; the test set and assesses the accuracy of the logand bounder, with and without
; the empirical method.
;
; But how do I ``assess accuracy?'' The only way I know is to use the empirical
; method to determine the true bounds of each combination.
;
; Since the number of combinations in a test set increases exponentially with k,
; this experiment gets computationally expensive. I therefore limit my tests to
; radii below 50. However, if every interval in every test set is small, then
; they'd all fall below the threshhold for using the empirical method and every
; single result of tau-bounder-logand would be perfect.
;
; To deal with this, I set the thresshold artificially low: 100. That is,
; tau-bounder-logand uses the empirical method only when product of the size of
; the two intervals is less than 10 * 10. (To run tau-bounder-logand without it
; using the empirical method at all, I set the threshhold to 0.)
;
; My hypothesis is that even with a relatively low threshhold (so that the number
; of combinations handled correctly ``by definition'' becomes increasiningly
; small compared to the number of combinations), the empirical method improves
; accuracy significantly. Here are my results. See the Appendix A for the code
; and resulting raw data from which this table is extracted.
;
; k A H (E coverage)
;
; 5 65 100 (99)
; 10 60 87 (80)
; 15 61 87 (58)
; 20 57 77 (43)
; 25 58 75 (32)
; 30 60 73 (25)
; 35 57 68 (20)
; 40 56 65 (17)
; 45 56 65 (14)
; 50 57 65 (12)
;
; In column A I show the percentage of the combinations bounded perfectly by the
; analytical method (i.e., with the threshhold set to 0 so that the empirical
; method is not employed). Note that it seems to hold steady at about 57% as k
; increases.
;
; In column H I show the percentage of the combinations bounded perfectly by the
; heuristic method (which augments the analytical method with the empirical
; method for combinations under the size threshhold of 100).
;
; In parenthesis I show the percentage of the cases covered by the empirical
; method. For example, when k=50, the heuristic method is perfect 65 percent of
; the time but only 12% of the cases were handled by the empirical method.
;
; What this shows is that the empirical method increases the accuracy even as it
; addresses a smaller percentage of the cases. Since the empirical method is
; limited to small cases, I suspect this means that the small cases are handled
; inaccurately by the analytical method a disproportionate number of times.
;
; -----------------------------------------------------------------
; Appendix A.
;
; In this section I show the raw Lisp code and raw data behind the table above.
;
; ; These bounds aren't always very tight. Let k be some natural number.
; ; Consider every combination of:
;
; ; -k <= lox <= hix <= k and -k <= loy <= hiy <= k
;
; ; and then compute the predicted bounds of logand. Then, for every x and y in
; ; the given two intervals, compute the actual lo and the actual hi of (logand x
; ; y). Let dlo be the distances between the actual lo and the predicted lo, and
; ; let dhi be the comparable hi distance. Sum dlo and dhi to get a measure how
; ; accurate the interval is. Sum all the measures across all combinations of
; ; input intervals.
;
; (include-book "elementary-bounders")
;
; (value :q)
;
; ; This test, which should return T, confirms that we can rebind the threshhold
; ; to control whether the empirical method is used by tau-bounder-logand:
;
; (not (equal (worth-computingp 0 100 0 100)
; (let ((*logand-empirical-threshhold* 100))
; (worth-computingp 0 100 0 100))))
;
; (defun score-logand-prediction (k)
; ; Given a max radius of k, compute the
; (let ((combinations 0)
; (perfect 0)
; (perfect-by-def 0)
; (worst-miss-on-lo nil)
; (worst-miss-on-hi nil)
; (score nil))
; ; When non-nil, the two ``worst-miss'' values are:
; ; (miss-magnitude (lox hix loy hiy) (predicted-lo predicted-hi) (alo ahi))
; (setq score
; (loop for lox from (- k) to k
; sum
; (loop for hix from lox to k
; sum
; (let ((int1 (make-tau-interval 'integerp nil lox nil hix)))
; (loop for loy from (- k) to k
; sum
; (loop for hiy from loy to k
; sum
; (let* ((int2 (make-tau-interval 'integerp nil loy nil hiy))
; (int (tau-bounder-logand int1 int2))
; (lo (tau-interval-lo int))
; (hi (tau-interval-hi int))
;
; ; Warning: Even though we construct the input intervals int1 and int2, we still
; ; exploit the fact that the variables lox, hix, loy, and hiy are bound to the
; ; respective bounds of those intervals.
;
; (alo (find-minimal-logand lox hix loy hiy))
; (ahi (find-maximal-logand lox hix loy hiy)))
; (setq combinations (+ 1 combinations))
; (if (worth-computingp lox hix loy hiy)
; (setq perfect-by-def (+ 1 perfect-by-def)))
; (if (and (equal lo alo)
; (equal hi ahi))
; (setq perfect (+ 1 perfect)))
; (if (or (null worst-miss-on-lo)
; (< (car worst-miss-on-lo)
; (abs (- lo alo))))
; (setq worst-miss-on-lo
; `(,(abs (- lo alo))
; (,lox ,hix ,loy ,hiy)
; (,lo ,hi)
; (,alo ,ahi))))
; (if (or (null worst-miss-on-hi)
; (< (car worst-miss-on-hi)
; (abs (- hi ahi))))
; (setq worst-miss-on-hi
; `(,(abs (- hi ahi))
; (,lox ,hix ,loy ,hiy)
; (,lo ,hi)
; (,alo ,ahi))))
; (+ (abs (- lo alo))
; (abs (- hi ahi))))))))))
; `((combinations ,combinations)
; (perfect ,perfect)
; (perfect-percentage ,(floor (* 100 (/ perfect combinations)) 1) %)
; (perfect-by-def ,perfect-by-def)
; (perfect-by-def-percentage ,(floor (* 100 (/ perfect-by-def combinations)) 1) %)
; (perfect-otherwise ,(- perfect perfect-by-def))
; (perfect-otherwise-percentage ,(floor (* 100 (/ (- perfect perfect-by-def) combinations)) 1) %)
; (score ,score)
; (average-error ,(float (/ score combinations)))
; (worst-miss-on-lo ,worst-miss-on-lo)
; (worst-miss-on-hi ,worst-miss-on-hi))))
;
; ; The test:
;
; (let ((*logand-empirical-threshhold* *logand-empirical-threshhold*))
; (progn
; (print (setq *logand-empirical-threshhold* 100))
; (print (list '(score-logand-prediction 5) (score-logand-prediction 5)))
; (print (list '(score-logand-prediction 10) (score-logand-prediction 10)))
; (print (list '(score-logand-prediction 15) (score-logand-prediction 15)))
; (print (list '(score-logand-prediction 20) (score-logand-prediction 20)))
; (print (list '(score-logand-prediction 25) (score-logand-prediction 25)))
; (print (list '(score-logand-prediction 30) (score-logand-prediction 30)))
; (print (list '(score-logand-prediction 35) (score-logand-prediction 35)))
; (print (list '(score-logand-prediction 40) (score-logand-prediction 40)))
; (print (list '(score-logand-prediction 45) (score-logand-prediction 45)))
; (print (list '(score-logand-prediction 50) (score-logand-prediction 50)))
; (print (setq *logand-empirical-threshhold* 0))
; (print (list '(score-logand-prediction 5) (score-logand-prediction 5)))
; (print (list '(score-logand-prediction 10) (score-logand-prediction 10)))
; (print (list '(score-logand-prediction 15) (score-logand-prediction 15)))
; (print (list '(score-logand-prediction 20) (score-logand-prediction 20)))
; (print (list '(score-logand-prediction 25) (score-logand-prediction 25)))
; (print (list '(score-logand-prediction 30) (score-logand-prediction 30)))
; (print (list '(score-logand-prediction 35) (score-logand-prediction 35)))
; (print (list '(score-logand-prediction 40) (score-logand-prediction 40)))
; (print (list '(score-logand-prediction 45) (score-logand-prediction 45)))
; (print (list '(score-logand-prediction 50) (score-logand-prediction 50)))
; nil
; ))
;
; ; Output:
;
; 100
; ((SCORE-LOGAND-PREDICTION 5)
; ((COMBINATIONS 4356) (PERFECT 4356) (PERFECT-PERCENTAGE 100 %)
; (PERFECT-BY-DEF 4347) (PERFECT-BY-DEF-PERCENTAGE 99 %) (PERFECT-OTHERWISE 9)
; (PERFECT-OTHERWISE-PERCENTAGE 0 %) (SCORE 0) (AVERAGE-ERROR 0.0)
; (WORST-MISS-ON-LO (0 (-5 -5 -5 -5) (-5 -5) (-5 -5)))
; (WORST-MISS-ON-HI (0 (-5 -5 -5 -5) (-5 -5) (-5 -5)))))
; ((SCORE-LOGAND-PREDICTION 10)
; ((COMBINATIONS 53361) (PERFECT 49621) (PERFECT-PERCENTAGE 92 %)
; (PERFECT-BY-DEF 43165) (PERFECT-BY-DEF-PERCENTAGE 80 %) (PERFECT-OTHERWISE 6456)
; (PERFECT-OTHERWISE-PERCENTAGE 12 %) (SCORE 11498) (AVERAGE-ERROR 0.21547572)
; (WORST-MISS-ON-LO (7 (-9 -1 -1 10) (-16 10) (-9 10)))
; (WORST-MISS-ON-HI (6 (-10 10 0 4) (0 10) (0 4)))))
; ((SCORE-LOGAND-PREDICTION 15)
; ((COMBINATIONS 246016) (PERFECT 214784) (PERFECT-PERCENTAGE 87 %)
; (PERFECT-BY-DEF 143557) (PERFECT-BY-DEF-PERCENTAGE 58 %)
; (PERFECT-OTHERWISE 71227) (PERFECT-OTHERWISE-PERCENTAGE 28 %) (SCORE 105010)
; (AVERAGE-ERROR 0.42684215) (WORST-MISS-ON-LO (7 (-9 -4 -1 15) (-16 15) (-9 12)))
; (WORST-MISS-ON-HI (12 (-15 15 0 3) (0 15) (0 3)))))
; ((SCORE-LOGAND-PREDICTION 20)
; ((COMBINATIONS 741321) (PERFECT 574847) (PERFECT-PERCENTAGE 77 %)
; (PERFECT-BY-DEF 319249) (PERFECT-BY-DEF-PERCENTAGE 43 %)
; (PERFECT-OTHERWISE 255598) (PERFECT-OTHERWISE-PERCENTAGE 34 %) (SCORE 967170)
; (AVERAGE-ERROR 1.3046575)
; (WORST-MISS-ON-LO (15 (-17 -13 -1 18) (-32 18) (-17 18)))
; (WORST-MISS-ON-HI (18 (-20 20 0 2) (0 20) (0 2)))))
; ((SCORE-LOGAND-PREDICTION 25)
; ((COMBINATIONS 1758276) (PERFECT 1321323) (PERFECT-PERCENTAGE 75 %)
; (PERFECT-BY-DEF 579499) (PERFECT-BY-DEF-PERCENTAGE 32 %)
; (PERFECT-OTHERWISE 741824) (PERFECT-OTHERWISE-PERCENTAGE 42 %) (SCORE 2743968)
; (AVERAGE-ERROR 1.5606014) (WORST-MISS-ON-LO (16 (-16 -7 16 25) (0 25) (16 25)))
; (WORST-MISS-ON-HI (24 (-25 25 0 1) (0 25) (0 1)))))
; ((SCORE-LOGAND-PREDICTION 30)
; ((COMBINATIONS 3575881) (PERFECT 2634466) (PERFECT-PERCENTAGE 73 %)
; (PERFECT-BY-DEF 927789) (PERFECT-BY-DEF-PERCENTAGE 25 %)
; (PERFECT-OTHERWISE 1706677) (PERFECT-OTHERWISE-PERCENTAGE 47 %) (SCORE 6587188)
; (AVERAGE-ERROR 1.8421161) (WORST-MISS-ON-LO (16 (-16 -10 16 30) (0 30) (16 22)))
; (WORST-MISS-ON-HI (29 (-30 30 0 1) (0 30) (0 1)))))
; ((SCORE-LOGAND-PREDICTION 35)
; ((COMBINATIONS 6533136) (PERFECT 4502512) (PERFECT-PERCENTAGE 68 %)
; (PERFECT-BY-DEF 1367879) (PERFECT-BY-DEF-PERCENTAGE 20 %)
; (PERFECT-OTHERWISE 3134633) (PERFECT-OTHERWISE-PERCENTAGE 47 %) (SCORE 19708780)
; (AVERAGE-ERROR 3.016741) (WORST-MISS-ON-LO (32 (-32 -8 32 35) (0 35) (32 35)))
; (WORST-MISS-ON-HI (34 (-35 35 0 1) (0 35) (0 1)))))
; ((SCORE-LOGAND-PREDICTION 40)
; ((COMBINATIONS 11029041) (PERFECT 7251983) (PERFECT-PERCENTAGE 65 %)
; (PERFECT-BY-DEF 1905769) (PERFECT-BY-DEF-PERCENTAGE 17 %)
; (PERFECT-OTHERWISE 5346214) (PERFECT-OTHERWISE-PERCENTAGE 48 %) (SCORE 42591220)
; (AVERAGE-ERROR 3.8617337) (WORST-MISS-ON-LO (32 (-32 -21 32 40) (0 40) (32 40)))
; (WORST-MISS-ON-HI (39 (-40 40 0 1) (0 40) (0 1)))))
; ((SCORE-LOGAND-PREDICTION 45)
; ((COMBINATIONS 17522596) (PERFECT 11407801) (PERFECT-PERCENTAGE 65 %)
; (PERFECT-BY-DEF 2547459) (PERFECT-BY-DEF-PERCENTAGE 14 %)
; (PERFECT-OTHERWISE 8860342) (PERFECT-OTHERWISE-PERCENTAGE 50 %) (SCORE 72472530)
; (AVERAGE-ERROR 4.135947) (WORST-MISS-ON-LO (32 (-32 -25 32 44) (0 44) (32 39)))
; (WORST-MISS-ON-HI (44 (-45 45 0 1) (0 45) (0 1)))))
; ((SCORE-LOGAND-PREDICTION 50)
; ((COMBINATIONS 26532801) (PERFECT 17294676) (PERFECT-PERCENTAGE 65 %)
; (PERFECT-BY-DEF 3298343) (PERFECT-BY-DEF-PERCENTAGE 12 %)
; (PERFECT-OTHERWISE 13996333) (PERFECT-OTHERWISE-PERCENTAGE 52 %)
; (SCORE 114203530) (AVERAGE-ERROR 4.3042397)
; (WORST-MISS-ON-LO (32 (-32 -27 32 48) (0 48) (32 37)))
; (WORST-MISS-ON-HI (50 (-50 50 0 0) (0 50) (0 0)))))
; 0
; ((SCORE-LOGAND-PREDICTION 5)
; ((COMBINATIONS 4356) (PERFECT 2873) (PERFECT-PERCENTAGE 65 %) (PERFECT-BY-DEF 0)
; (PERFECT-BY-DEF-PERCENTAGE 0 %) (PERFECT-OTHERWISE 2873)
; (PERFECT-OTHERWISE-PERCENTAGE 65 %) (SCORE 2845) (AVERAGE-ERROR 0.6531221)
; (WORST-MISS-ON-LO (5 (-3 -3 5 5) (0 5) (5 5)))
; (WORST-MISS-ON-HI (5 (-5 5 0 0) (0 5) (0 0)))))
; ((SCORE-LOGAND-PREDICTION 10)
; ((COMBINATIONS 53361) (PERFECT 32499) (PERFECT-PERCENTAGE 60 %) (PERFECT-BY-DEF 0)
; (PERFECT-BY-DEF-PERCENTAGE 0 %) (PERFECT-OTHERWISE 32499)
; (PERFECT-OTHERWISE-PERCENTAGE 60 %) (SCORE 68793) (AVERAGE-ERROR 1.2892)
; (WORST-MISS-ON-LO (10 (-6 -6 10 10) (0 10) (10 10)))
; (WORST-MISS-ON-HI (10 (-10 10 0 0) (0 10) (0 0)))))
; ((SCORE-LOGAND-PREDICTION 15)
; ((COMBINATIONS 246016) (PERFECT 150727) (PERFECT-PERCENTAGE 61 %)
; (PERFECT-BY-DEF 0) (PERFECT-BY-DEF-PERCENTAGE 0 %) (PERFECT-OTHERWISE 150727)
; (PERFECT-OTHERWISE-PERCENTAGE 61 %) (SCORE 405365) (AVERAGE-ERROR 1.6477181)
; (WORST-MISS-ON-LO (15 (-1 -1 15 15) (0 15) (15 15)))
; (WORST-MISS-ON-HI (15 (-15 15 0 0) (0 15) (0 0)))))
; ((SCORE-LOGAND-PREDICTION 20)
; ((COMBINATIONS 741321) (PERFECT 429599) (PERFECT-PERCENTAGE 57 %)
; (PERFECT-BY-DEF 0) (PERFECT-BY-DEF-PERCENTAGE 0 %) (PERFECT-OTHERWISE 429599)
; (PERFECT-OTHERWISE-PERCENTAGE 57 %) (SCORE 1889899) (AVERAGE-ERROR 2.5493667)
; (WORST-MISS-ON-LO (20 (-12 -12 20 20) (0 20) (20 20)))
; (WORST-MISS-ON-HI (20 (-20 20 0 0) (0 20) (0 0)))))
; ((SCORE-LOGAND-PREDICTION 25)
; ((COMBINATIONS 1758276) (PERFECT 1034743) (PERFECT-PERCENTAGE 58 %)
; (PERFECT-BY-DEF 0) (PERFECT-BY-DEF-PERCENTAGE 0 %) (PERFECT-OTHERWISE 1034743)
; (PERFECT-OTHERWISE-PERCENTAGE 58 %) (SCORE 4887045) (AVERAGE-ERROR 2.7794528)
; (WORST-MISS-ON-LO (25 (-7 -7 25 25) (0 25) (25 25)))
; (WORST-MISS-ON-HI (25 (-25 25 0 0) (0 25) (0 0)))))
; ((SCORE-LOGAND-PREDICTION 30)
; ((COMBINATIONS 3575881) (PERFECT 2146211) (PERFECT-PERCENTAGE 60 %)
; (PERFECT-BY-DEF 0) (PERFECT-BY-DEF-PERCENTAGE 0 %) (PERFECT-OTHERWISE 2146211)
; (PERFECT-OTHERWISE-PERCENTAGE 60 %) (SCORE 11087983) (AVERAGE-ERROR 3.1007695)
; (WORST-MISS-ON-LO (30 (-2 -2 30 30) (0 30) (30 30)))
; (WORST-MISS-ON-HI (30 (-30 30 0 0) (0 30) (0 0)))))
; ((SCORE-LOGAND-PREDICTION 35)
; ((COMBINATIONS 6533136) (PERFECT 3786285) (PERFECT-PERCENTAGE 57 %)
; (PERFECT-BY-DEF 0) (PERFECT-BY-DEF-PERCENTAGE 0 %) (PERFECT-OTHERWISE 3786285)
; (PERFECT-OTHERWISE-PERCENTAGE 57 %) (SCORE 27677205) (AVERAGE-ERROR 4.236435)
; (WORST-MISS-ON-LO (35 (-29 -29 35 35) (0 35) (35 35)))
; (WORST-MISS-ON-HI (35 (-35 35 0 0) (0 35) (0 0)))))
; ((SCORE-LOGAND-PREDICTION 40)
; ((COMBINATIONS 11029041) (PERFECT 6215779) (PERFECT-PERCENTAGE 56 %)
; (PERFECT-BY-DEF 0) (PERFECT-BY-DEF-PERCENTAGE 0 %) (PERFECT-OTHERWISE 6215779)
; (PERFECT-OTHERWISE-PERCENTAGE 56 %) (SCORE 55769581) (AVERAGE-ERROR 5.056612)
; (WORST-MISS-ON-LO (40 (-24 -24 40 40) (0 40) (40 40)))
; (WORST-MISS-ON-HI (40 (-40 40 0 0) (0 40) (0 0)))))
; ((SCORE-LOGAND-PREDICTION 45)
; ((COMBINATIONS 17522596) (PERFECT 9959663) (PERFECT-PERCENTAGE 56 %)
; (PERFECT-BY-DEF 0) (PERFECT-BY-DEF-PERCENTAGE 0 %) (PERFECT-OTHERWISE 9959663)
; (PERFECT-OTHERWISE-PERCENTAGE 56 %) (SCORE 92758101) (AVERAGE-ERROR 5.2936277)
; (WORST-MISS-ON-LO (45 (-19 -19 45 45) (0 45) (45 45)))
; (WORST-MISS-ON-HI (45 (-45 45 0 0) (0 45) (0 0)))))
; ((SCORE-LOGAND-PREDICTION 50)
; ((COMBINATIONS 26532801) (PERFECT 15351489) (PERFECT-PERCENTAGE 57 %)
; (PERFECT-BY-DEF 0) (PERFECT-BY-DEF-PERCENTAGE 0 %) (PERFECT-OTHERWISE 15351489)
; (PERFECT-OTHERWISE-PERCENTAGE 57 %) (SCORE 144236691) (AVERAGE-ERROR 5.4361653)
; (WORST-MISS-ON-LO (50 (-14 -14 50 50) (0 50) (50 50)))
; (WORST-MISS-ON-HI (50 (-50 50 0 0) (0 50) (0 0)))))
;
;
; -----------------------------------------------------------------
; Appendix B.
;
; I now discuss briefly the prospects of refining my analysis so that it is
; inherently more accurate. I am not optimistic but record my thoughts for
; posterity in case somebody wants to pursue it.
;
; Here is an example of a bad case. The x interval contains only one element.
; The y interval contains 64 elements, so it is easy to compute the empirical
; answer. The analytical range is 0 to 3392, but the actual range is 3072 to
; 3104. Furthermore, there are only two points in the actual range: 3072 and
; 3104. Here is some Common Lisp code to confirm these statements:
;
; (let* ((lox #b10110000100000)
; (loy #b00110100000000)
; (hiy #b00110101000000)
; (hix lox))
; (mv-let (rel1 lo rel2 hi)
; (ibounds-of-logand nil lox nil hix nil loy nil hiy)
; `((lox ,lox)
; (hix ,hix)
; (loy ,loy)
; (hiy ,hiy)
; (,lo --- ,hi)
; (,(find-minimal-logand lox hix loy hiy) ---
; ,(find-maximal-logand lox hix loy hiy))
; (all ,(let ((ans nil))
; (loop for x from lox to hix
; do (loop for y from loy to hiy
; do (or (member-equal (logand x y) ans)
; (setq ans (cons (logand x y) ans)))))
; ans)))))
; This produces:
;
; ((LOX 11296)
; (HIX 11296)
; (LOY 3328)
; (HIY 3392)
; (0 --- 3392) ; analytical interval
; (3072 --- 3104) ; actual interval
; (ALL (3104 3072))) ; all possible actual values of (logand x y)
;
; Let's blow up this example to see why the prediction is so hard. I discuss
; the example in the text below and, in the ``footnotes'', discuss the
; generalization of the example to whole classes of problems.
;
; bits a b c d e f g h i j k l m n
; pwr 13 12 11 10 9 8 7 6 5 4 3 2 1 0
;
; lox = hix = #b 1 0 1 1 0 0 0 0 1 0 0 0 0 0
; loy = #b 0 0 1 1 0 1 0 0 0 0 0 0 0 0
; hiy = #b 0 0 1 1 0 1 0 1 0 0 0 0 0 0
;
; Note that as y ranges from loy to hiy, we will generate all possible 6-bit
; patterns in bits i through n, stopping when we finally set bit h. [Footnote:
; In general we won't generate all h-bit patterns, since we start with the
; pattern given by the low h bits of loy and end with the pattern given by the
; low h+1 bits of hiy, but since in this example, loy and hiy both have all 0s
; below bit h, we will generate all patterns.] Thus, all the y's in the range
; share the same bits above bit h. Thus, every logand of x and y will be
; non-zero, because x and every y will always share whatever bits all three
; share above bit h. In this case that is bits c and d, which is 2^11 + 2^10 =
; 3072. [Footnote: Clearly we could have an arbitrary number of shared bits
; contributing to this lower bound.] Furthermore, since there is only one x
; and it has only one bit set below bit h, as y varies it the low order h bits
; of (logand x y) will will either be all 0 or all 0 except for 1 in bit i.
; This will mean that the low order h bits of the logand either contribute 0 or
; 2^5 to the value. This is how the empirical hi is achieved: lo + 2^5 = 3104.
; This accounts for all (both) of the values of the logand. [Footnote: By
; choosing an x with multiple bits set below bit h we can arrange for multiple
; values to be generated by the logand. Precisely which values can only be
; determined, I think, by generating each of the h-bit numbers between the low
; h bits of loy and the low h bits of hiy and loganding those patterns with the
; low h bits of x.]
;
; One could over estimate the maximal amount by which lo will be incremented by
; supposing that there exists a combination in y that will select all of the
; lower h bits of x.
;
; But I've decided that trying to get more accurate analytical bounds is not
; worth the effort. Instead, I'll just go with the empirical approach. We'll
; see if this is helpful enough.
|