FeatX extracts epic-feature hierarchies with code mappings from repositories and applies feature edits via a three-stage Evolution Agent, reporting 42.6% relative F1 gain in function-level localization and lower cognitive load versus vanilla ChatGPT in a user study and 38-commit replay.
Reposummary: Feature-oriented summarization and documentation generation for code repositories
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Single-agent RAG pipeline matches multi-agent lexical quality for README generation while cutting token consumption by 86% and doubling speed, with developer-guided planning yielding the highest overall quality.
A systematic review that categorizes prompting strategies for LLM-based code summarization, assesses their effectiveness, and identifies gaps in research and evaluation practices.
citing papers explorer
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FeatX: Editing Software by Editing Features for Repository-Level Code Evolution
FeatX extracts epic-feature hierarchies with code mappings from repositories and applies feature edits via a three-stage Evolution Agent, reporting 42.6% relative F1 gain in function-level localization and lower cognitive load versus vanilla ChatGPT in a user study and 38-commit replay.
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The Illusion of Agentic Complexity in README.md Generation: Evaluating Single-Agent vs. Multi-Agent RAG Systems
Single-agent RAG pipeline matches multi-agent lexical quality for README generation while cutting token consumption by 86% and doubling speed, with developer-guided planning yielding the highest overall quality.
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Prompt-Driven Code Summarization: A Systematic Literature Review
A systematic review that categorizes prompting strategies for LLM-based code summarization, assesses their effectiveness, and identifies gaps in research and evaluation practices.