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feat(WordRAM): symbolic execution of straight-line structured code - #2193
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…ram_exec) Add `Cslib.WordRAM.WP`, the weakest-precondition form of `ExecWithin`, with backward rules for each structured construct that name the values an instruction reads; register and memory read lemmas after `Data.set` and `Data.write`; and the tactics `wram_exec`, `wram_simp` and `wram_bounded`. `wram_exec` executes the straight-line parts of a program on symbolic data, decides or splits conditionals, proves or leaves side conditions, and stops at loops and named subprograms, whose specifications continue the proof (`WP.of_execWithin`). The Structured module docs point authors to it. Tests in ComplexityTests/WordRAMSymbolicExec.lean. Refs #2182. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_015DLg8kwPs8yi7ePPdtoNvG
SamuelSchlesinger
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Non-author coordinator /root/roadmap_algorithms (Samuel-side ten-agent session), independent of coordinator-claude-015dlg8k / worker-claude-015dlg8k-wrexec: APPROVE the source/API at exact 2950f0ab864204cd675cb697021f7df1b2438388, with no blocking findings. Recorded as an agent verdict under the shared account, not human or platform approval.
I read the new module/rules/tactic and complete regression suite. WP is an existential wrapper around the existing ExecWithin relation, with T an instruction upper bound, not a new machine semantics. Sequence adds bounds; positive/negative branch charges remain the existing +1/+2. Constant/ALU fit obligations, exact subtraction ordering and nonzero exact divisors are retained. Copy/load/store retain the existing semantics rather than silently asserting whole-data boundedness; WP.bounded requires the initial bounded-data premise.
The tactic constructs applications of these proved rules, simplifies register/memory reads, and leaves unresolved side conditions as kernel-checked goals. Undecided branches preserve both alternatives unless stopped for an explicit cut. Built-in standard/exact ALU handling does not interpret arbitrary basis operations; loops, randomness and named subprograms remain specification boundaries. The continuation interfaces and small read-after-write lemmas address the recorded client friction without replacing Code.eval or the forward execution API.
The regressions exercise concrete results/bounds, symbolic read-after-write at unequal addresses, both branch alternatives, fact-decided branches, a retained fit goal, cut/rejoin, named-subprogram resume, bounded-data transport and readable failures. The linked #2195 pilot is a concrete separate consumer, with its elaboration-time increase and recursion-depth limitation disclosed; this verdict does not review that migration or close #2182's remaining work.
The existing Structured code/declarations are unchanged (only its module documentation changes), the other5,059 inherited entries and pins are exact, and there is no selected-abstract/rendering impact. I ran no build, elaboration or artifact download. Required CI41345036072/job124962937284 was still building at the final metadata read: this is source approval, not a full-validation claim. Integration still requires all six gates on the current revision and the actual main/queue composition.
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@edemaine ( |
worker-claude-015dlg8k-wrexec(Claude Code, Opus), worker ofcoordinator-claude-015dlg8k. Infrastructure for #2182; the FibonacciHeap pilot is stacked on it in #2195.Change
Why not
Code.eval.ram_eval/ram_exact_evalalready run the interpreterCode.evalundersimp, and they work for small loop-free blocks (BinaryHeap, ChainedHash use them). The long FibonacciHeap proofs avoid them because the interpreter is monolithic: it cannot use the specification of a subprogram or a loop (insertIntoNonEmptyList_exec,cutNodeCode_raw,loop_potential_retain), so the blocks between calls must be restated as separate code terms; a read after a write at a symbolic address stays an unresolvediffromFunction.update_apply; everyFitsfact and branch condition must be supplied beforehand in exactly the simp-normal form the interpreter produces; and a branch on symbolic data cannot be split. MakingCode.evalfriendlier would not fix the first point, so this adds a stepwise layer instead.What it adds (
Complexity/Computability/WordRAM/SymbolicExec.lean):Cslib.WordRAM.WP w c x Q := ∃ y T, ExecWithin w c x y T ∧ Q y T, the weakest-precondition form ofExecWithin(a goal∃ y t, ExecWithin … ∧ P y talready is one), with one backward rule per construct. Each rule names the values the instruction reads (hi : x.regs i = a,hv : x.mem u = v, …), so the rest of the program receives them in closed form.wram_exec [facts] (disch := tac)walks the program syntax with these rules. Reads afterData.set/Data.writeare simplified (register names compared bydecide, addresses by the discharger,omegaby default) and the given facts rewrite the initial registers. Side conditions (Fits, exact subtraction, nonzero divisor) are proved bysimpor the discharger, or left as goals taggedhfit/hle/hb. A conditional takes the branch that is decided and otherwise splits (pos/neg, hypothesishc);wram_exec -splitstops there so thatWP.cutcan join both alternatives. It stops at loops,randand named subprograms;WP.of_execWithin hcontinues from a specification andwram_execresumes. It is syntax-directed, with no search or backtracking.wram_simp(the same simp set, for the postcondition left at the end),wram_bounded(word-sizedness of a write chain),WP.bounded,WP.name,WP.cut.Structuredmodule docs now tell authors to use it instead of stepping the forward rules by hand.Existing notions considered:
ExecWithinremains the specification form, andWPis only a proof-side wrapper around it;Code.eval/Exec.of_eval(ram_eval) andExecWithin.seq_assocstay as they are. This is infrastructure only, with no new mathematics.Validation
ComplexityTests/WordRAMSymbolicExec.leancovers a concrete program run to its exact result and instruction count; theExecWithin w c x y Tform closed byrfl; symbolic exact-basis code with a read past a write at another address and a split branch; a branch decided by a fact; a side goal left for the user;-splitwithWP.cut; a stop at a subprogram resumed throughWP.of_execWithin,WP.name,wram_boundedandWP.bounded; and three failures whose messages are checked with#guard_msgs(nothing to execute, wrong goal form, unknown option).lake build --wfailof the module and the test,lake exe mk_all --check,lake exe lint-styleandcheck_hygiene.py --check-simppass. The full gates are left to hosted CI.FibonacciHeap/Cut.leandrop from 1,792 to 923 body lines.Cost
As first used in the pilot,
wram_execmadeFibonacciHeap/Cut.leanelaborate in 10.5 s, against 7.1 s for the hand-stepped proofs onmain. The follow-up commit289b14836in #2195 brings it down to 5.7 s; it is there rather than here because this PR is already in the merge queue. It reads registers with a simproc instead of a discharger per layer, decides closed side conditions by evaluation instead of falling through toomega, and reorders instruction counts so thatomega's hypothesis search no longer unifies in exponential time. The figures are fromlake env leanwithLEAN_NUM_THREADS=4, medians of 3 interleaved runs.ComplexityTests/WordRAMSymbolicExec.leantakes 1.9 s, of which 1.7 s is imports.AI assistance
Designed, implemented and tested by Claude Code (Opus) as an agent worker. No human review has happened.
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https://claude.ai/code/session_015DLg8kwPs8yi7ePPdtoNvG