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Learn about an innovative interactive approach called iFix that significantly reduces debugging time in automated program repair by enabling developers to compare patch candidates through runtime behavior analysis. Discover how iFix performs static analysis to identify runtime variables related to buggy statements and captures their values during execution, allowing for aligned comparison across different patch candidates. Explore the research findings from a comprehensive user study with 28 participants that demonstrates iFix's ability to reduce task completion time by 33-36% compared to manual inspection and existing interactive patch filtering techniques while improving developer confidence by 20-50%. Understand how the approach addresses the critical challenge of plausible patches that pass test cases but may not correctly fix underlying bugs, and examine the quantitative results showing iFix improves correct patch ranking by at least 39% compared to other methods while maintaining generalizability across different automated program repair tools. Gain insights into the static analysis techniques used to identify relevant runtime variables, the methodology for capturing and aligning runtime values across patch candidates, and the practical implications for software debugging workflows in modern development environments.
