Revisiting object similarity-based patch ranking in automated program repair
Ali Ghanbari · 2022
Test-based generate-and-validate automated program repair (APR) systems often generate plausible patches that pass the test suite without fixing the bug. So far, several approaches for automatic assessment of the APR-generated patches are proposed. Among them, dynamic patch correctness assessment relies on comparing run-time information obtained from the program before and after patching. Object similarity-based dynamic patch ranking approaches, specifically, capture system state snapshots after the impact point of patches and express behavior differences in term of object graphs similarities. Dynamic approaches rely on the assumption that, when running the originally passing test cases, the correct patches will not alter the program behavior in a significant way, but such patches will significantly change program behavior for the failing test cases.