How Does Execution Information Help with Information-Retrieval Based Bug Localization?

Abstract

Bug localization is challenging and time-consuming. Given a bug report, a developer may spend tremendous time comprehending the bug description together with code in order to locate bugs. To facilitate bug report comprehension, information retrieval (IR)-based bug localization techniques have been proposed to automatically search for and rank potential buggy code elements (i.e., classes or methods). However, these techniques do not leverage any dynamic execution information of buggy programs. In this paper, we perform the first systematic study on how dynamic execution information can help with static IR-based bug localization. More specifically, with the fixing patches and bug reports of 157 real bugs, we investigated the impact of various execution information (i.e. coverage, slicing, and spectrum) on three IR-based techniques: the baseline technique, BugLocator, and BLUiR. Our experiments demonstrate that both the coverage and slicing information of failed tests can effectively reduce the search space and improve IR-based techniques at both class and method levels. Using additional spectrum information can further improve bug localization at the method but not the class level. Some of our investigated ways of augmenting IR-based bug localization with execution information even outperform a state-of-the-art technique, which merges spectrum with an IR-based technique in a complicated way. Different from prior work, by investigating various easy-to-understand ways to combine execution information with IR-based techniques, this study shows for the first time that execution information can generally bring considerable improvement to IR-based bug localization.