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.
An empirical study of automated unit test generation for python.Empirical Software Engineering, 28, 01 2023
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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.