A Software Fault Localization Technique Based on Program Mutations

Recent fault localization techniques leverage program coverage of both passed test runs and failed test runs to reduce the high cost of debugging.The effectiveness of such techniques can be adversely affected by coincidental correctness,which occurs in a passed test run when a fault has been executed but no failure is detected.Studies have shown that coincidental correctness is a common phenomenon and its occurrence can significantly reduce the effectiveness of fault localization.In this paper,a fault localization technique named Muffler is proposed,which uses mutation analysis to address this problem and improve fault localization.Muffler systematically mutates statements in a faulty program and estimates their likelihood of being faulty based on both coverage and how mutation affects the outcome of passed test cases.Experiments on eight benchmark programs widely used in fault localization are conducted to evaluate our method.Results indicate that Muffler can help programmers locate faults effectively with a reduction of 50.26%in code examination effort.