Abstract
In the current researches of fault localization, the spectrum-based techniques are frequently and widely studied for researchers since it can automatically and effectively localize the faults of software and also can be implemented easily. Most of the spectrum-based fault localization techniques rely on using the similarity coefficients. However, the existing similarity coefficients for fault localization lack a measure to properly reflect the relation between the failing and passing test cases. The failing test cases are expected to provide more information to the similarity coefficients than the passing test cases. In order to accurately evaluate the relative importance of failing and passing test cases in the similarity coefficients, several widely used similarity coefficients in fault localization are investigated in our study. The modified similarity coefficients which are assigned the weight of the failing/passing test cases are proposed and analyzed by using the multiple coverage-combined technique. The performance evaluation of our approach indicates that the proposed approach performs better than the original methods including the Ochiai coefficient, which has the best performance in current researches. Therefore, our study shows that assigning the weight of failing and passing test cases to the similarity coefficients can localize the faults more effectively.