Evaluation and Analysis of Spectrum-Based Fault Localization with Modified Similarity Coefficients for Software Debugging

Abstract

During the process of fault localization, the spectrum-based techniques are frequently used and widely studied since they can automatically and effectively localize the faults of software and be implemented easily. So far most of spectrum-based fault localization techniques have relied heavily on the use of similarity coefficients. However, we noticed that existing similarity coefficients for fault localization may lack measure(s) to properly reflect the relationship between failing and passing test cases. It also has to note that the failing test cases usually are expected to provide more information to the similarity coefficients than the passing test cases. In order to evaluate the importance of failing and passing test cases in the similarity coefficients, a number of modified similarity coefficients in fault localization are presented and discussed. The modified similarity coefficients which are assigned the weights of the failing and/or passing test cases will be studied and analyzed with the multi-coverage-combined techniques. Five open source programs and 75 faulty versions in total from Siemens suite, which have been widely used for software testing and comparison of fault localization techniques, were selected as experiment subjects. Detailed analysis of the results shows that assigning the weights of failing and passing test cases to the similarity coefficients would be able to localize the faults more effectively and accurately.