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Statistical fault localization techniques find suspicious faulty program entities in programs by comparing passed and failed executions. Existing studies show that such techniques can be promising in locating program faults. However, coincidental correctness and execution crashes may make program entities indistinguishable in the execution spectra under study, or cause inaccurate counting, thus severely affecting the precision of existing fault localization techniques. In this paper, the authors propose a BlockRank technique, which calculates, contrasts, and propagates the mean edge profiles between passed and failed executions to alleviate the impact of coincidental correctness.
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