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New C2C framework uses AI to pinpoint software bugs more accurately

By PulseAugur Editorial · [1 sources] ·

Researchers have developed a new framework called C2C (From Codebase to Culprit) designed to improve the accuracy and efficiency of bug localization in software development. C2C utilizes a two-stage process that combines semantic retrieval with Hierarchical Reinforcement Learning (HRL). Initially, it retrieves potentially buggy code segments using semantic vector similarity search, leveraging CodeBERT for embeddings. Subsequently, an HRL agent progressively narrows down the search from files to functions and finally to specific lines of code, mimicking a developer's top-down debugging approach. Experiments on Java and Python codebases show that C2C enhances retrieval precision and localization accuracy compared to previous methods. AI

IMPACT This framework could significantly speed up debugging cycles for developers by automating and refining the bug-finding process.

RANK_REASON The cluster describes a research paper detailing a new framework for bug localization in software development. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.LG →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

New C2C framework uses AI to pinpoint software bugs more accurately

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The cluster describes a research paper detailing a new framework for bug localization in software development. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.LG TIER_1 English(EN) · Ankur Garg, Corey Yang-Smith, Rishav Rishav, Ahmad Abdellatif, Samira Ebrahimi Kahou ·

    From Codebase to Culprit (C2C): Reducing the Search Space for Bugs with Semantic Retrieval and Hierarchical Reinforcement Learning

    arXiv:2609.38402v1 Announce Type: cross Abstract: We introduce C2C (From Codebase to Culprit), a framework for precise bug localization that progressively reduces the debugging search space across multiple levels of granularity: files, functions, and lines of code. To mirror deve…

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