Reversa is a reverse documentation engineering framework that deploys a multi-agent pipeline to extract implicit rules from legacy software and produce traceable specifications with confidence scores and explicit gaps for human review.
Large language model-based agents for software engineering: A survey.ACM Transactions on Software Engineering and Methodology
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CodeSpecBench shows LLMs achieve at most 20.2% pass rate on repository-level executable behavioral specification generation, revealing that strong code generation does not imply deep semantic understanding.
Audit of GSO, SWE-Perf and SWE-fficiency reveals that reference patches satisfy validity rules across machines for only 39/102, 11/140 and 411/498 tasks respectively, public submissions beat references on 85.3% of replay-valid tasks, and scoring rules cause ranking disagreements.
citing papers explorer
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Reversa: A Reverse Documentation Engineering Framework for Converting Legacy Software into Operational Specifications for AI Agents
Reversa is a reverse documentation engineering framework that deploys a multi-agent pipeline to extract implicit rules from legacy software and produce traceable specifications with confidence scores and explicit gaps for human review.
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CodeSpecBench: Benchmarking LLMs for Executable Behavioral Specification Generation
CodeSpecBench shows LLMs achieve at most 20.2% pass rate on repository-level executable behavioral specification generation, revealing that strong code generation does not imply deep semantic understanding.
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Are Performance-Optimization Benchmarks Reliably Measuring Coding Agents?
Audit of GSO, SWE-Perf and SWE-fficiency reveals that reference patches satisfy validity rules across machines for only 39/102, 11/140 and 411/498 tasks respectively, public submissions beat references on 85.3% of replay-valid tasks, and scoring rules cause ranking disagreements.