A Comparative Study of Vectorization Methods on BugLocator

Abstract

CONTEXT: Debugging is a labor-intensive and time-consuming activity. Automatic bug localization techniques have been proposed for reducing this effort. Among the techniques, Information retrieval (IR) based bug localization techniques take a bug report and give a rank list of source modules which are likely to cause the bug. Those techniques use a few variants of tf-idf vectorizations for bug reports and software modules though different vectorizations may give vastly different performances. OBJECTIVE: To explore the effects of vectorization methods on IR-based bug localization. METHOD: An empirical evaluation was conducted with 46 public data sets and 6 vectorization methods. BugLocator was used as a test bed. RESULTS: We found a vectorization used in BugLocator was one of the best. However, we found a better vectorization for representing software modules. CONCLUSIONS: It is worth to examine different vectorization methods for better IR-based bug localization because a preference for the methods can change as demonstrated in this study.