REAgent improves LLM patch generation for software issues by 17.4% on average through automated construction, quality checking, and iterative refinement of structured issue-oriented requirements.
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ARGUS extracts fragmented code change rationales from multiple documents using LLMs and generates summaries that developers rate as useful for review and maintenance.
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REAgent: Requirement-Driven LLM Agents for Software Issue Resolution
REAgent improves LLM patch generation for software issues by 17.4% on average through automated construction, quality checking, and iterative refinement of structured issue-oriented requirements.
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Fine-grained Multi-Document Extraction and Generation of Code Change Rationale
ARGUS extracts fragmented code change rationales from multiple documents using LLMs and generates summaries that developers rate as useful for review and maintenance.