Exploring the Characteristics of Spectra Distribution and Their Impacts on Fault Localization

Abstract

Spectrum-Based Fault Localization (SBFL) follows the basic intuitions that the faulty parts are more likely to be covered by failure-revealing test cases and less likely to be covered by passed test cases. However, due to the diversity of programs and faults, many other characteristics (related to program structure, test suites, and type of faulty components) will influence the practical application of SBFL. For example, a statement can be covered by numerous failure-revealing test cases, and also covered by numerous passed test cases. To get more indicators about the faulty components towards a better application of SBFL, we extend the scope of spectrum-based knowledge from the basic intuitions to the Characteristics of Spectra Distribution (CSDs for short). That is, we explore the relationships between different types of statements and their spectra. Firstly, we introduce the concepts of Failure-Independent, Failure-Related, and Failure-Exclusionary to describe the relationships between different types of statements and their executions. Then, we propose two probabilistic models, with and without the noise of fault interference, respectively, to identify various CSDs for each type of statements. As the analysis results, we introduce a visualization technique to generalize the identified CSDs and provide an overall picture of spectra distribution and its dynamics. Finally, based on our analysis and also the observation of the program spectra of current benchmarks, we design a technique to filter the potential non-faulty statements to improve the accuracy of SBFL.