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cv usk
@cv_usk
AI / Software Research Notes AI Agent, LLMOps, MLOps, Software Architecture 投稿は個人の意見です。
参加 May 2026
286 フォロー中    469 ファン
Formal specifications used in program verification were always treated as locked once written. This paper argues that's exactly what causes cascading failures. Title: SpecAgent: Empowering Program Verification with Agentic Synthesis of Formal Program Specifications URL: 📝 Overview SpecAgent synthesizes ACSL specifications (preconditions, postconditions, loop invariants) for C program verification through coordinated specialized agents, reframing specification synthesis as an iterative agentic process of planning, retrieval-augmented generation, verification, repair, and critique. ❓ Problem Solved Existing approaches follow a forward-only workflow where once a specification is generated it stays fixed, so when downstream verification fails, they repeatedly attempt ineffective local repairs instead of revisiting the upstream specification that's the actual root cause. 💡 Method & Approach A planning agent identifies targets and dependencies; a retrieval-augmented generation agent injects similar examples from a 184-entry knowledge base to produce ACSL; a verification gate runs Frama-C/WP; a repairing agent diagnoses root causes; and a critique agent judges specification strength as ACCEPT, IMPROVE, or REPLAN. 📊 Results SpecAgent with DeepSeek-V4 hits 96.82% precision and 88.95% recall, beating every baseline. Ablations show the repair stage drives a big precision gain, and the full pipeline lifts recall by 8.02 points over generation alone. It discharges 604 of 811 real-world verification targets (74.5%) at lower cost than both Preguss and Codex. #ProgramVerification# #AIAgents#
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