IssueSpecter combines coverage analysis with LLM defect detection to generate prioritized, actionable issue reports, achieving 84.6% validity on manually reviewed issues from 13 Python projects and outperforming a coverage-driven baseline.
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A literature survey that collects and categorizes 124 papers on LLM-based agents for software engineering from SE and agent perspectives.
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LLM-Guided Issue Generation from Uncovered Code Segments
IssueSpecter combines coverage analysis with LLM defect detection to generate prioritized, actionable issue reports, achieving 84.6% validity on manually reviewed issues from 13 Python projects and outperforming a coverage-driven baseline.
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Large Language Model-Based Agents for Software Engineering: A Survey
A literature survey that collects and categorizes 124 papers on LLM-based agents for software engineering from SE and agent perspectives.