This work presents Evolutionary Self-Debugging Agents (ESDA), which mines tool traces into structured failure signatures and uses them to maintain a strategy bank of reusable debugging policies, and analyze transfer across languages and build systems and finds that mining failure signatures yields consistent gains under distribution shift.
Shuang Cao, Rui Li· Proceedings of the 32nd ACM...· 0 citations
A Aegis scheduler is presented, a scheduler that adapts placement using live fabric telemetry under operator-defined contracts that reduces service p99 RPC latency, cuts SLO violations, and lowers ECN mark rate while improving utilization under production-derived workloads.
Rui Li, Shuang Cao· Conference on Applications,...· 0 citations
Repository-level code repair generates rich tool traces, but most LLM agents discard this data and keep restarting from a fixed debugging loop. We present Evolutionary Self-Debugging Agents (ESDA), which mines tool traces into structured failure signatures and uses them to maintain a strategy bank of reusable debugging policies. Policies are stored as modular prompt genomes with typed slots, enabling slot-level reuse, mutation, and crossover as new tasks arrive. A cost-aware ranking objective prioritizes strategies that are likely to succeed in the first few evaluator calls under tight budgets. On RepoBench, ESDA solves 58.4% of tasks within the first two evaluator calls and reduces median wall-clock time by 3.0x compared to strong baselines. We further analyze transfer across languages and build systems and find that mining failure signatures yields consistent gains under distribution shift.
Shuang Cao, Rui Li· Proceedings of the 32nd ACM...· 0 citations
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