A Study of Modified Testing-Based Fault Localization Method

In software development and maintenance, locating faults is generally a complex and time-consuming process. In order to effectively identify the locations of program faults, several approaches have been proposed. Similarity-aware fault localization (SAFL) is a testing-based fault localization method that utilizes testing information to calculate the suspicion probability of each statement. Dicing is also another method that we have used. In this paper, our proposed method focuses on predicates and their influence, instead of on statements in traditional SAFL. In our method, fuzzy theory, matrix calculating, and some probability are used. Our method detects the importance of each predicate and then provides more test data for programmers to analyze the fault locations. Furthermore, programmers will also gain some important information about the program in order to maintain their program accordingly. In order to speed up the efficiency, we also simplified the program. We performed an experimental study for several programs, together with another two testing-based fault localization (TBFL) approaches. These three methods were discussed in terms of different criteria such as line of code and suspicious code coverage. The experimental results show that the proposed method from our study can decrease the number of codes which have more probability of suspicion than real bugs.