Author

Corey Yang-Smith

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#machine learning Preprint Sep 2026

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

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 developer's natural top-down debugging workflows, C2C integrates semantic retrieval and Hierar...

Ankur Garg, Corey Yang-Smith, Rishav Rishav et al. · 0 citations

Book Open access Jul 2026

Evaluating and Improving the Quality of LLM-Generated Code

This tutorial introduces a reusable, end-to-end evaluation pipeline grounded in empirical software engineering practices, focusing on post-generation validation rather than prompt design, allowing for validating AI-generated code in modern development workflows.

Glaucia Melo, Jessica Pourleyli, Genevieve Caumartin et al. · SIGSOFT FSE Companion · 0 citations