「z3」の検索結果

Expert guide for mathematical formal verification, SMT solver constraints (Z3, Dafny, TLA+), invariant theorem proving for FinTech billing state machines, RBAC/ABAC authorization, and zero-violation architecture / Panduan ahli verifikasi formal matematis, SMT solver (Z3, Dafny, TLA+), pembuktian invarian state machine billing FinTech, otorisasi RBAC/ABAC, dan arsitektur zero-violation.

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Z3 SMT solver ile CTF constraint çözme — byte equations, hash collision, validator bypass

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Symbolic execution and constraint solving playbook. Use when solving CTF reversing challenges, recovering keys, bypassing checks, or automating binary analysis with angr, Z3, or Unicorn Engine.

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Performs symbolic execution to detect potential errors by exploring execution paths, solving path constraints, and generating test inputs. Use when you need to analyze code for bugs like null dereferences, division by zero, buffer overflows, or assertion violations. Also use to generate test inputs that exercise different code paths, find edge cases, or explore all reachable program states. Supports Python, Java, and C/C++ through manual symbolic execution techniques and integration with tools like KLEE, angr, Z3, and Symbolic PathFinder.

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Think and work like an expert Logician. Use when a task calls for Logician judgment. Reasons from syntax-versus-semantics and object-versus-metalanguage discipline, the ⊢/⊨ distinction, and matching each logic to its intended semantics through natural deduction and sequent calculus (cut-elimination, subformula property), compactness and Löwenheim–Skolem, forcing and diagonalization, and proof assistants (Lean 4/mathlib, Coq, Isabelle/HOL, Agda) with Z3/CVC5/Vampire/Mace4 automation while treating use–mention conflation, second-order misuse of compactness, mis-stated incompleteness hypotheses (ω-consistency vs consistency), and Gödel philosophical overreach as first-class failure modes.

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Think and work like an expert Formal Methods Researcher. Use when a task calls for Formal Methods Researcher judgment. Reasons from operational semantics and temporal logics through SPIN/TLA+/PRISM, Coq/Lean/Isabelle, Z3/CVC5, refinement and separation logic, vacuity and false-positive diagnosis, and Dafny/F* versus property-based testing boundaries.

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Think and work like an expert Computer Scientist. Use when a task calls for Computer Scientist judgment. Reasons from computational models, abstraction contracts, invariants, and measurable complexity through CLRS-grade algorithm analysis, impossibility results (FLP, CAP, NP-hardness), property-based and chaos testing, and formal tools (TLA+, Coq, Z3) while treating partial failure, race conditions, label leakage, and abstraction leaks like GC pauses and clock skew as first-class failure modes.

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Proves protocols and agent workflows with TLA+, P, Alloy, Z3, Dafny, or Lean. Use when proving protocols correct, writing TLA+ specs, or verifying LLM proofs.

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Automate on-target verification of a program's logic by driving its RTT console with rttsh - write Lua scripts that exercise commands and assert responses, output and timing on real hardware. Use when asked to verify target-side behavior on board, build board-level checks for firmware features, or automate hardware test runs.

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Portable Codebase Argus agent playbook for evidence-first multi-agent review of GitHub pull requests, CI failures, GitHub Actions logs, GitHub App webhook review, /argus PR comment commands, autofix branch planning, OpenAI/Claude/Gemini/Codex provider tribunals, downstream merge/rebase work, and long-lived fork sync against an upstream repository.

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Use when a query needs direct SMT solving, an unsat core needs debugging, or another tool reports a solver timeout or unknown. Not for deciding what to prove: use proof-driven.

日本語の概要は準備中です。原文の説明を表示しています。