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A Unified Debugging Approach via LLM-Based Multi-Agent Synergy.

, , , , , и . CoRR, (2024)

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Hong Xia

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Ying Xia

 

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Less training, more repairing please: revisiting automated program repair via zero-shot learning., и . ESEC/SIGSOFT FSE, стр. 959-971. ACM, (2022)Large Language Models Are Zero-Shot Fuzzers: Fuzzing Deep-Learning Libraries via Large Language Models., , , , и . ISSTA, стр. 423-435. ACM, (2023)A Unified Debugging Approach via LLM-Based Multi-Agent Synergy., , , , , и . CoRR, (2024)Balancing Effectiveness and Flakiness of Non-Deterministic Machine Learning Tests., , , , и . ICSE, стр. 1801-1813. IEEE, (2023)Large Language Models are Edge-Case Generators: Crafting Unusual Programs for Fuzzing Deep Learning Libraries., , , , , и . ICSE, стр. 70:1-70:13. ACM, (2024)Agentless: Demystifying LLM-based Software Engineering Agents., , , и . CoRR, (2024)Automated Program Repair in the Era of Large Pre-trained Language Models., , и . ICSE, стр. 1482-1494. IEEE, (2023)Fuzz4All: Universal Fuzzing with Large Language Models., , , , и . ICSE, стр. 126:1-126:13. ACM, (2024)Copiloting the Copilots: Fusing Large Language Models with Completion Engines for Automated Program Repair., , и . ESEC/SIGSOFT FSE, стр. 172-184. ACM, (2023)Conversational Automated Program Repair., и . CoRR, (2023)