Taming coincidental correctness: Coverage refinement with context patterns to improve fault localization

Recent techniques for fault localization leverage code coverage to address the high cost problem of debugging. These techniques exploit the correlations between program failures and the coverage of program entities as the clue in locating faults. Experimental evidence shows that the effectiveness of these techniques can be affected adversely by coincidental correctness, which occurs when a fault is executed but no failure is detected. In this paper, we propose an approach to address this problem. We refine code coverage of test runs using control- and data-flow patterns prescribed by different fault types. We conjecture that this extra information, which we call context patterns, can strengthen the correlations between program failures and the coverage of faulty program entities, making it easier for fault localization techniques to locate the faults. To evaluate the proposed approach, we have conducted a mutation analysis on three real world programs and cross-validated the results with real faults. The experimental results consistently show that coverage refinement is effective in easing the coincidental correctness problem in fault localization techniques.