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my_tauto prose
author Adam Chlipala <adamc@hcoop.net>
date Tue, 28 Oct 2008 16:31:55 -0400
parents 32a5ad6e2bb0
children df289eb8ef76
rev   line source
adamc@62 1 (* Copyright (c) 2008, Adam Chlipala
adamc@62 2 *
adamc@62 3 * This work is licensed under a
adamc@62 4 * Creative Commons Attribution-Noncommercial-No Derivative Works 3.0
adamc@62 5 * Unported License.
adamc@62 6 * The license text is available at:
adamc@62 7 * http://creativecommons.org/licenses/by-nc-nd/3.0/
adamc@62 8 *)
adamc@62 9
adamc@62 10 (* begin hide *)
adamc@62 11 Require Import List.
adamc@62 12
adamc@62 13 Require Import Tactics.
adamc@62 14
adamc@62 15 Set Implicit Arguments.
adamc@62 16 (* end hide *)
adamc@62 17
adamc@62 18
adamc@62 19 (** %\chapter{Infinite Data and Proofs}% *)
adamc@62 20
adamc@62 21 (** In lazy functional programming languages like Haskell, infinite data structures are everywhere. Infinite lists and more exotic datatypes provide convenient abstractions for communication between parts of a program. Achieving similar convenience without infinite lazy structures would, in many cases, require acrobatic inversions of control flow.
adamc@62 22
adamc@62 23 Laziness is easy to implement in Haskell, where all the definitions in a program may be thought of as mutually recursive. In such an unconstrained setting, it is easy to implement an infinite loop when you really meant to build an infinite list, where any finite prefix of the list should be forceable in finite time. Haskell programmers learn how to avoid such slip-ups. In Coq, such a laissez-faire policy is not good enough.
adamc@62 24
adamc@62 25 We spent some time in the last chapter discussing the Curry-Howard isomorphism, where proofs are identified with functional programs. In such a setting, infinite loops, intended or otherwise, are disastrous. If Coq allowed the full breadth of definitions that Haskell did, we could code up an infinite loop and use it to prove any proposition vacuously. That is, the addition of general recursion would make CIC %\textit{%#<i>#inconsistent#</i>#%}%.
adamc@62 26
adamc@62 27 There are also algorithmic considerations that make universal termination very desirable. We have seen how tactics like [reflexivity] compare terms up to equivalence under computational rules. Calls to recursive, pattern-matching functions are simplified automatically, with no need for explicit proof steps. It would be very hard to hold onto that kind of benefit if it became possible to write non-terminating programs; we would be running smack into the halting problem.
adamc@62 28
adamc@62 29 One solution is to use types to contain the possibility of non-termination. For instance, we can create a "non-termination monad," inside which we must write all of our general-recursive programs. In later chapters, we will spend some time on this idea and its applications. For now, we will just say that it is a heavyweight solution, and so we would like to avoid it whenever possible.
adamc@62 30
adamc@62 31 Luckily, Coq has special support for a class of lazy data structures that happens to contain most examples found in Haskell. That mechanism, %\textit{%#<i>#co-inductive types#</i>#%}%, is the subject of this chapter. *)
adamc@62 32
adamc@62 33
adamc@62 34 (** * Computing with Infinite Data *)
adamc@62 35
adamc@62 36 (** Let us begin with the most basic type of infinite data, %\textit{%#<i>#streams#</i>#%}%, or lazy lists. *)
adamc@62 37
adamc@62 38 Section stream.
adamc@62 39 Variable A : Set.
adamc@62 40
adamc@62 41 CoInductive stream : Set :=
adamc@62 42 | Cons : A -> stream -> stream.
adamc@62 43 End stream.
adamc@62 44
adamc@62 45 (** The definition is surprisingly simple. Starting from the definition of [list], we just need to change the keyword [Inductive] to [CoInductive]. We could have left a [Nil] constructor in our definition, but we will leave it out to force all of our streams to be infinite.
adamc@62 46
adamc@62 47 How do we write down a stream constant? Obviously simple application of constructors is not good enough, since we could only denote finite objects that way. Rather, whereas recursive definitions were necessary to %\textit{%#<i>#use#</i>#%}% values of recursive inductive types effectively, here we find that we need %\textit{%#<i>#co-recursive definitions#</i>#%}% to %\textit{%#<i>#build#</i>#%}% values of co-inductive types effectively.
adamc@62 48
adamc@62 49 We can define a stream consisting only of zeroes. *)
adamc@62 50
adamc@62 51 CoFixpoint zeroes : stream nat := Cons 0 zeroes.
adamc@62 52
adamc@62 53 (** We can also define a stream that alternates between [true] and [false]. *)
adamc@62 54
adamc@62 55 CoFixpoint trues : stream bool := Cons true falses
adamc@62 56 with falses : stream bool := Cons false trues.
adamc@62 57
adamc@62 58 (** Co-inductive values are fair game as arguments to recursive functions, and we can use that fact to write a function to take a finite approximation of a stream. *)
adamc@62 59
adamc@62 60 Fixpoint approx A (s : stream A) (n : nat) {struct n} : list A :=
adamc@62 61 match n with
adamc@62 62 | O => nil
adamc@62 63 | S n' =>
adamc@62 64 match s with
adamc@62 65 | Cons h t => h :: approx t n'
adamc@62 66 end
adamc@62 67 end.
adamc@62 68
adamc@62 69 Eval simpl in approx zeroes 10.
adamc@62 70 (** [[
adamc@62 71
adamc@62 72 = 0 :: 0 :: 0 :: 0 :: 0 :: 0 :: 0 :: 0 :: 0 :: 0 :: nil
adamc@62 73 : list nat
adamc@62 74 ]] *)
adamc@62 75 Eval simpl in approx trues 10.
adamc@62 76 (** [[
adamc@62 77
adamc@62 78 = true
adamc@62 79 :: false
adamc@62 80 :: true
adamc@62 81 :: false
adamc@62 82 :: true :: false :: true :: false :: true :: false :: nil
adamc@62 83 : list bool
adamc@62 84 ]] *)
adamc@62 85
adamc@68 86 (* begin thide *)
adamc@62 87 (** So far, it looks like co-inductive types might be a magic bullet, allowing us to import all of the Haskeller's usual tricks. However, there are important restrictions that are dual to the restrictions on the use of inductive types. Fixpoints %\textit{%#<i>#consume#</i>#%}% values of inductive types, with restrictions on which %\textit{%#<i>#arguments#</i>#%}% may be passed in recursive calls. Dually, co-fixpoints %\textit{%#<i>#produce#</i>#%}% values of co-inductive types, with restrictions on what may be done with the %\textit{%#<i>#results#</i>#%}% of co-recursive calls.
adamc@62 88
adamc@62 89 The restriction for co-inductive types shows up as the %\textit{%#<i>#guardedness condition#</i>#%}%, and it can be broken into two parts. First, consider this stream definition, which would be legal in Haskell.
adamc@62 90
adamc@62 91 [[
adamc@68 92 (* end thide *)
adamc@62 93 CoFixpoint looper : stream nat := looper.
adamc@68 94 (* begin thide *)
adamc@62 95 [[
adamc@62 96 Error:
adamc@62 97 Recursive definition of looper is ill-formed.
adamc@62 98 In environment
adamc@62 99 looper : stream nat
adamc@62 100
adamc@62 101 unguarded recursive call in "looper"
adamc@62 102 *)
adamc@68 103 (* end thide *)
adamc@62 104
adamc@62 105 (** The rule we have run afoul of here is that %\textit{%#<i>#every co-recursive call must be guarded by a constructor#</i>#%}%; that is, every co-recursive call must be a direct argument to a constructor of the co-inductive type we are generating. It is a good thing that this rule is enforced. If the definition of [looper] were accepted, our [approx] function would run forever when passed [looper], and we would have fallen into inconsistency.
adamc@62 106
adamc@62 107 The second rule of guardedness is easiest to see by first introducing a more complicated, but legal, co-fixpoint. *)
adamc@62 108
adamc@62 109 Section map.
adamc@62 110 Variables A B : Set.
adamc@62 111 Variable f : A -> B.
adamc@62 112
adamc@62 113 CoFixpoint map (s : stream A) : stream B :=
adamc@62 114 match s with
adamc@62 115 | Cons h t => Cons (f h) (map t)
adamc@62 116 end.
adamc@62 117 End map.
adamc@62 118
adamc@62 119 (** This code is a literal copy of that for the list [map] function, with the [Nil] case removed and [Fixpoint] changed to [CoFixpoint]. Many other standard functions on lazy data structures can be implemented just as easily. Some, like [filter], cannot be implemented. Since the predicate passed to [filter] may reject every element of the stream, we cannot satisfy even the first guardedness condition.
adamc@62 120
adamc@62 121 The second condition is subtler. To illustrate it, we start off with another co-recursive function definition that %\textit{%#<i>#is#</i>#%}% legal. The function [interleaves] takes two streams and produces a new stream that alternates between their elements. *)
adamc@62 122
adamc@62 123 Section interleave.
adamc@62 124 Variable A : Set.
adamc@62 125
adamc@62 126 CoFixpoint interleave (s1 s2 : stream A) : stream A :=
adamc@62 127 match s1, s2 with
adamc@62 128 | Cons h1 t1, Cons h2 t2 => Cons h1 (Cons h2 (interleave t1 t2))
adamc@62 129 end.
adamc@62 130 End interleave.
adamc@62 131
adamc@62 132 (** Now say we want to write a weird stuttering version of [map] that repeats elements in a particular way, based on interleaving. *)
adamc@62 133
adamc@62 134 Section map'.
adamc@62 135 Variables A B : Set.
adamc@62 136 Variable f : A -> B.
adamc@62 137
adamc@68 138 (* begin thide *)
adamc@62 139 (** [[
adamc@68 140 (* end thide *)
adamc@62 141
adamc@62 142 CoFixpoint map' (s : stream A) : stream B :=
adamc@62 143 match s with
adamc@62 144 | Cons h t => interleave (Cons (f h) (map' s)) (Cons (f h) (map' s))
adamc@68 145 end.
adamc@68 146 (* begin thide *)
adamc@68 147 *)
adamc@62 148
adamc@62 149 (** We get another error message about an unguarded recursive call. This is because we are violating the second guardedness condition, which says that, not only must co-recursive calls be arguments to constructors, there must also %\textit{%#<i>#not be anything but [match]es and calls to constructors of the same co-inductive type#</i>#%}% wrapped around these immediate uses of co-recursive calls. The actual implemented rule for guardedness is a little more lenient than what we have just stated, but you can count on the illegality of any exception that would enhance the expressive power of co-recursion.
adamc@62 150
adamc@62 151 Why enforce a rule like this? Imagine that, instead of [interleave], we had called some other, less well-behaved function on streams. Perhaps this other function might be defined mutually with [map']. It might deconstruct its first argument, retrieving [map' s] from within [Cons (f h) (map' s)]. Next it might try a [match] on this retrieved value, which amounts to deconstructing [map' s]. To figure out how this [match] turns out, we need to know the top-level structure of [map' s], but this is exactly what we started out trying to determine! We run into a loop in the evaluation process, and we have reached a witness of inconsistency if we are evaluating [approx (map' s) 1] for any [s]. *)
adamc@68 152 (* end thide *)
adamc@62 153 End map'.
adamc@62 154
adamc@63 155
adamc@63 156 (** * Infinite Proofs *)
adamc@63 157
adamc@63 158 (** Let us say we want to give two different definitions of a stream of all ones, and then we want to prove that they are equivalent. *)
adamc@63 159
adamc@63 160 CoFixpoint ones : stream nat := Cons 1 ones.
adamc@63 161 Definition ones' := map S zeroes.
adamc@63 162
adamc@63 163 (** The obvious statement of the equality is this: *)
adamc@63 164
adamc@63 165 Theorem ones_eq : ones = ones'.
adamc@63 166
adamc@63 167 (** However, faced with the initial subgoal, it is not at all clear how this theorem can be proved. In fact, it is unprovable. The [eq] predicate that we use is fundamentally limited to equalities that can be demonstrated by finite, syntactic arguments. To prove this equivalence, we will need to introduce a new relation. *)
adamc@68 168 (* begin thide *)
adamc@63 169 Abort.
adamc@63 170
adamc@63 171 (** Co-inductive datatypes make sense by analogy from Haskell. What we need now is a %\textit{%#<i>#co-inductive proposition#</i>#%}%. That is, we want to define a proposition whose proofs may be infinite, subject to the guardedness condition. The idea of infinite proofs does not show up in usual mathematics, but it can be very useful (unsurprisingly) for reasoning about infinite data structures. Besides examples from Haskell, infinite data and proofs will also turn out to be useful for modelling inherently infinite mathematical objects, like program executions.
adamc@63 172
adamc@63 173 We are ready for our first co-inductive predicate. *)
adamc@63 174
adamc@63 175 Section stream_eq.
adamc@63 176 Variable A : Set.
adamc@63 177
adamc@63 178 CoInductive stream_eq : stream A -> stream A -> Prop :=
adamc@63 179 | Stream_eq : forall h t1 t2,
adamc@63 180 stream_eq t1 t2
adamc@63 181 -> stream_eq (Cons h t1) (Cons h t2).
adamc@63 182 End stream_eq.
adamc@63 183
adamc@63 184 (** We say that two streams are equal if and only if they have the same heads and their tails are equal. We use the normal finite-syntactic equality for the heads, and we refer to our new equality recursively for the tails.
adamc@63 185
adamc@63 186 We can try restating the theorem with [stream_eq]. *)
adamc@63 187
adamc@63 188 Theorem ones_eq : stream_eq ones ones'.
adamc@63 189 (** Coq does not support tactical co-inductive proofs as well as it supports tactical inductive proofs. The usual starting point is the [cofix] tactic, which asks to structure this proof as a co-fixpoint. *)
adamc@63 190 cofix.
adamc@63 191 (** [[
adamc@63 192
adamc@63 193 ones_eq : stream_eq ones ones'
adamc@63 194 ============================
adamc@63 195 stream_eq ones ones'
adamc@63 196 ]] *)
adamc@63 197
adamc@63 198 (** It looks like this proof might be easier than we expected! *)
adamc@63 199
adamc@63 200 assumption.
adamc@63 201 (** [[
adamc@63 202
adamc@63 203 Proof completed. *)
adamc@63 204
adamc@63 205 (** Unfortunately, we are due for some disappointment in our victory lap. *)
adamc@63 206
adamc@63 207 (** [[
adamc@63 208 Qed.
adamc@63 209
adamc@63 210 Error:
adamc@63 211 Recursive definition of ones_eq is ill-formed.
adamc@63 212
adamc@63 213 In environment
adamc@63 214 ones_eq : stream_eq ones ones'
adamc@63 215
adamc@63 216 unguarded recursive call in "ones_eq" *)
adamc@63 217
adamc@63 218 (** Via the Curry-Howard correspondence, the same guardedness condition applies to our co-inductive proofs as to our co-inductive data structures. We should be grateful that this proof is rejected, because, if it were not, the same proof structure could be used to prove any co-inductive theorem vacuously, by direct appeal to itself!
adamc@63 219
adamc@63 220 Thinking about how Coq would generate a proof term from the proof script above, we see that the problem is that we are violating the first part of the guardedness condition. During our proofs, Coq can help us check whether we have yet gone wrong in this way. We can run the command [Guarded] in any context to see if it is possible to finish the proof in a way that will yield a properly guarded proof term.
adamc@63 221
adamc@63 222 [[
adamc@63 223 Guarded.
adamc@63 224
adamc@63 225 Running [Guarded] here gives us the same error message that we got when we tried to run [Qed]. In larger proofs, [Guarded] can be helpful in detecting problems %\textit{%#<i>#before#</i>#%}% we think we are ready to run [Qed].
adamc@63 226
adamc@63 227 We need to start the co-induction by applying one of [stream_eq]'s constructors. To do that, we need to know that both arguments to the predicate are [Cons]es. Informally, this is trivial, but [simpl] is not able to help us. *)
adamc@63 228
adamc@63 229 Undo.
adamc@63 230 simpl.
adamc@63 231 (** [[
adamc@63 232
adamc@63 233 ones_eq : stream_eq ones ones'
adamc@63 234 ============================
adamc@63 235 stream_eq ones ones'
adamc@63 236 ]] *)
adamc@63 237
adamc@63 238 (** It turns out that we are best served by proving an auxiliary lemma. *)
adamc@63 239 Abort.
adamc@63 240
adamc@63 241 (** First, we need to define a function that seems pointless on first glance. *)
adamc@63 242
adamc@63 243 Definition frob A (s : stream A) : stream A :=
adamc@63 244 match s with
adamc@63 245 | Cons h t => Cons h t
adamc@63 246 end.
adamc@63 247
adamc@63 248 (** Next, we need to prove a theorem that seems equally pointless. *)
adamc@63 249
adamc@63 250 Theorem frob_eq : forall A (s : stream A), s = frob s.
adamc@63 251 destruct s; reflexivity.
adamc@63 252 Qed.
adamc@63 253
adamc@63 254 (** But, miraculously, this theorem turns out to be just what we needed. *)
adamc@63 255
adamc@63 256 Theorem ones_eq : stream_eq ones ones'.
adamc@63 257 cofix.
adamc@63 258
adamc@63 259 (** We can use the theorem to rewrite the two streams. *)
adamc@63 260 rewrite (frob_eq ones).
adamc@63 261 rewrite (frob_eq ones').
adamc@63 262 (** [[
adamc@63 263
adamc@63 264 ones_eq : stream_eq ones ones'
adamc@63 265 ============================
adamc@63 266 stream_eq (frob ones) (frob ones')
adamc@63 267 ]] *)
adamc@63 268
adamc@63 269 (** Now [simpl] is able to reduce the streams. *)
adamc@63 270
adamc@63 271 simpl.
adamc@63 272 (** [[
adamc@63 273
adamc@63 274 ones_eq : stream_eq ones ones'
adamc@63 275 ============================
adamc@63 276 stream_eq (Cons 1 ones)
adamc@63 277 (Cons 1
adamc@63 278 ((cofix map (s : stream nat) : stream nat :=
adamc@63 279 match s with
adamc@63 280 | Cons h t => Cons (S h) (map t)
adamc@63 281 end) zeroes))
adamc@63 282 ]] *)
adamc@63 283
adamc@63 284 (** Since we have exposed the [Cons] structure of each stream, we can apply the constructor of [stream_eq]. *)
adamc@63 285
adamc@63 286 constructor.
adamc@63 287 (** [[
adamc@63 288
adamc@63 289 ones_eq : stream_eq ones ones'
adamc@63 290 ============================
adamc@63 291 stream_eq ones
adamc@63 292 ((cofix map (s : stream nat) : stream nat :=
adamc@63 293 match s with
adamc@63 294 | Cons h t => Cons (S h) (map t)
adamc@63 295 end) zeroes)
adamc@63 296 ]] *)
adamc@63 297
adamc@63 298 (** Now, modulo unfolding of the definition of [map], we have matched our assumption. *)
adamc@63 299 assumption.
adamc@63 300 Qed.
adamc@63 301
adamc@63 302 (** Why did this silly-looking trick help? The answer has to do with the constraints placed on Coq's evaluation rules by the need for termination. The [cofix]-related restriction that foiled our first attempt at using [simpl] is dual to a restriction for [fix]. In particular, an application of an anonymous [fix] only reduces when the top-level structure of the recursive argument is known. Otherwise, we would be unfolding the recursive definition ad infinitum.
adamc@63 303
adamc@63 304 Fixpoints only reduce when enough is known about the %\textit{%#<i>#definitions#</i>#%}% of their arguments. Dually, co-fixpoints only reduce when enough is known about %\textit{%#<i>#how their results will be used#</i>#%}%. In particular, a [cofix] is only expanded when it is the discriminee of a [match]. Rewriting with our superficially silly lemma wrapped new [match]es around the two [cofix]es, triggering reduction.
adamc@63 305
adamc@63 306 If [cofix]es reduced haphazardly, it would be easy to run into infinite loops in evaluation, since we are, after all, building infinite objects.
adamc@63 307
adamc@63 308 One common source of difficulty with co-inductive proofs is bad interaction with standard Coq automation machinery. If we try to prove [ones_eq'] with automation, like we have in previous inductive proofs, we get an invalid proof. *)
adamc@63 309
adamc@63 310 Theorem ones_eq' : stream_eq ones ones'.
adamc@63 311 cofix; crush.
adamc@63 312 (** [[
adamc@63 313
adamc@63 314 Guarded. *)
adamc@63 315 Abort.
adamc@68 316 (* end thide *)
adamc@63 317
adamc@63 318 (** The standard [auto] machinery sees that our goal matches an assumption and so applies that assumption, even though this violates guardedness. One usually starts a proof like this by [destruct]ing some parameter and running a custom tactic to figure out the first proof rule to apply for each case. Alternatively, there are tricks that can be played with "hiding" the co-inductive hypothesis. We will see examples of effective co-inductive proving in later chapters. *)
adamc@64 319
adamc@64 320
adamc@64 321 (** * Simple Modeling of Non-Terminating Programs *)
adamc@64 322
adamc@67 323 (** We close the chapter with a quick motivating example for more complex uses of co-inductive types. We will define a co-inductive semantics for a simple assembly language and use that semantics to prove that an optimization function is sound. We start by defining types of registers, program labels, and instructions. *)
adamc@64 324
adamc@64 325 Inductive reg : Set := R1 | R2.
adamc@64 326 Definition label := nat.
adamc@64 327
adamc@64 328 Inductive instrs : Set :=
adamc@64 329 | Const : reg -> nat -> instrs -> instrs
adamc@64 330 | Add : reg -> reg -> reg -> instrs -> instrs
adamc@64 331 | Halt : reg -> instrs
adamc@64 332 | Jeq : reg -> reg -> label -> instrs -> instrs.
adamc@64 333
adamc@67 334 (** [Const] stores a constant in a register; [Add] stores in the first register the sum of the values in the second two; [Halt] ends the program, returning the value of its register argument; and [Jeq] jumps to a label if the values in two registers are equal. Each instruction but [Halt] takes an [instrs], which can be read as "list of instructions," as the normal continuation of control flow.
adamc@67 335
adamc@67 336 We can define a program as a list of lists of instructions, where labels will be interpreted as indexing into such a list. *)
adamc@67 337
adamc@64 338 Definition program := list instrs.
adamc@64 339
adamc@67 340 (** We define a polymorphic map type for register keys, with its associated operations. *)
adamc@64 341 Section regmap.
adamc@64 342 Variable A : Set.
adamc@64 343
adamc@64 344 Record regmap : Set := Regmap {
adamc@64 345 VR1 : A;
adamc@64 346 VR2 : A
adamc@64 347 }.
adamc@64 348
adamc@67 349 Definition empty (v : A) : regmap := Regmap v v.
adamc@64 350 Definition get (rm : regmap) (r : reg) : A :=
adamc@64 351 match r with
adamc@64 352 | R1 => VR1 rm
adamc@64 353 | R2 => VR2 rm
adamc@64 354 end.
adamc@64 355 Definition set (rm : regmap) (r : reg) (v : A) : regmap :=
adamc@64 356 match r with
adamc@64 357 | R1 => Regmap v (VR2 rm)
adamc@64 358 | R2 => Regmap (VR1 rm) v
adamc@64 359 end.
adamc@64 360 End regmap.
adamc@64 361
adamc@67 362 (** Now comes the interesting part. We define a co-inductive semantics for programs. The definition itself is not surprising. We could change [CoInductive] to [Inductive] and arrive at a valid semantics that only covers terminating program executions. Using [CoInductive] admits infinite derivations for infinite executions. *)
adamc@67 363
adamc@64 364 Section run.
adamc@64 365 Variable prog : program.
adamc@64 366
adamc@64 367 CoInductive run : regmap nat -> instrs -> nat -> Prop :=
adamc@64 368 | RConst : forall rm r n is v,
adamc@64 369 run (set rm r n) is v
adamc@64 370 -> run rm (Const r n is) v
adamc@64 371 | RAdd : forall rm r r1 r2 is v,
adamc@64 372 run (set rm r (get rm r1 + get rm r2)) is v
adamc@64 373 -> run rm (Add r r1 r2 is) v
adamc@64 374 | RHalt : forall rm r,
adamc@64 375 run rm (Halt r) (get rm r)
adamc@64 376 | RJeq_eq : forall rm r1 r2 l is is' v,
adamc@64 377 get rm r1 = get rm r2
adamc@64 378 -> nth_error prog l = Some is'
adamc@64 379 -> run rm is' v
adamc@64 380 -> run rm (Jeq r1 r2 l is) v
adamc@64 381 | RJeq_neq : forall rm r1 r2 l is v,
adamc@64 382 get rm r1 <> get rm r2
adamc@64 383 -> run rm is v
adamc@64 384 -> run rm (Jeq r1 r2 l is) v.
adamc@64 385 End run.
adamc@64 386
adamc@67 387 (** We can write a function which tracks known register values to attempt to constant fold a sequence of instructions. We track register values with a [regmap (option nat)], where a mapping to [None] indicates no information, and a mapping to [Some n] indicates that the corresponding register is known to have value [n]. *)
adamc@67 388
adamc@64 389 Fixpoint constFold (rm : regmap (option nat)) (is : instrs) {struct is} : instrs :=
adamc@64 390 match is with
adamc@64 391 | Const r n is => Const r n (constFold (set rm r (Some n)) is)
adamc@64 392 | Add r r1 r2 is =>
adamc@64 393 match get rm r1, get rm r2 with
adamc@67 394 | Some n1, Some n2 =>
adamc@67 395 Const r (n1 + n2) (constFold (set rm r (Some (n1 + n2))) is)
adamc@64 396 | _, _ => Add r r1 r2 (constFold (set rm r None) is)
adamc@64 397 end
adamc@64 398 | Halt _ => is
adamc@64 399 | Jeq r1 r2 l is => Jeq r1 r2 l (constFold rm is)
adamc@64 400 end.
adamc@64 401
adamc@67 402 (** We characterize when the two types of register maps we are using agree with each other. *)
adamc@67 403
adamc@64 404 Definition regmapCompat (rm : regmap nat) (rm' : regmap (option nat)) :=
adamc@64 405 forall r, match get rm' r with
adamc@64 406 | None => True
adamc@64 407 | Some v => get rm r = v
adamc@64 408 end.
adamc@64 409
adamc@67 410 (** We prove two lemmas about how register map modifications affect compatibility. A tactic [compat] abstracts the common structure of the two proofs. *)
adamc@67 411
adamc@67 412 (** remove printing * *)
adamc@64 413 Ltac compat := unfold regmapCompat in *; crush;
adamc@64 414 match goal with
adamc@88 415 | [ H : _ |- match get _ ?R with Some _ => _ | None => _ end ] => generalize (H R); destruct R; crush
adamc@64 416 end.
adamc@64 417
adamc@64 418 Lemma regmapCompat_set_None : forall rm rm' r n,
adamc@64 419 regmapCompat rm rm'
adamc@64 420 -> regmapCompat (set rm r n) (set rm' r None).
adamc@64 421 destruct r; compat.
adamc@64 422 Qed.
adamc@64 423
adamc@64 424 Lemma regmapCompat_set_Some : forall rm rm' r n,
adamc@64 425 regmapCompat rm rm'
adamc@64 426 -> regmapCompat (set rm r n) (set rm' r (Some n)).
adamc@64 427 destruct r; compat.
adamc@64 428 Qed.
adamc@64 429
adamc@67 430 (** Finally, we can prove the main theorem. *)
adamc@64 431
adamc@64 432 Section constFold_ok.
adamc@64 433 Variable prog : program.
adamc@64 434
adamc@64 435 Theorem constFold_ok : forall rm is v,
adamc@64 436 run prog rm is v
adamc@64 437 -> forall rm', regmapCompat rm rm'
adamc@64 438 -> run prog rm (constFold rm' is) v.
adamc@64 439 Hint Resolve regmapCompat_set_None regmapCompat_set_Some.
adamc@64 440 Hint Constructors run.
adamc@64 441
adamc@65 442 cofix;
adamc@65 443 destruct 1; crush; eauto;
adamc@65 444 repeat match goal with
adamc@67 445 | [ H : regmapCompat _ _
adamc@67 446 |- run _ _ (match get ?RM ?R with
adamc@67 447 | Some _ => _
adamc@67 448 | None => _
adamc@67 449 end) _ ] =>
adamc@65 450 generalize (H R); destruct (get RM R); crush
adamc@65 451 end.
adamc@64 452 Qed.
adamc@64 453 End constFold_ok.
adamc@64 454
adamc@67 455 (** If we print the proof term that was generated, we can verify that the proof is structured as a [cofix], with each co-recursive call properly guarded. *)
adamc@67 456
adamc@64 457 Print constFold_ok.
adamc@81 458
adamc@81 459
adamc@81 460 (** * Exercises *)
adamc@81 461
adamc@81 462 (** %\begin{enumerate}%#<ol>#
adamc@81 463
adamc@81 464 %\item%#<li># %\begin{enumerate}%#<ol>#
adamc@81 465 %\item%#<li># Define a co-inductive type of infinite trees carrying data of a fixed parameter type. Each node should contain a data value and two child trees.#</li>#
adamc@81 466 %\item%#<li># Define a function [everywhere] for building a tree with the same data value at every node.#</li>#
adamc@81 467 %\item%#<li># Define a function [map] for building an output tree out of two input trees by traversing them in parallel and applying a two-argument function to their corresponding data values.#</li>#
adamc@104 468 %\item%#<li># Define a tree [falses] where every node has the value [false].#</li>#
adamc@104 469 %\item%#<li># Define a tree [true_false] where the root node has value [true], its children have value [false], all nodes at the next have the value [true], and so on, alternating boolean values from level to level.#</li>#
adamc@81 470 %\item%#<li># Prove that [true_falses] is equal to the result of mapping the boolean "or" function [orb] over [true_false] and [falses]. You can make [orb] available with [Require Import Bool.]. You may find the lemma [orb_false_r] from the same module helpful. Your proof here should not be about the standard equality [=], but rather about some new equality relation that you define.#</li>#
adamc@81 471 #</ol>#%\end{enumerate}% #</li>#
adamc@81 472
adamc@81 473 #</ol>#%\end{enumerate}% *)