Poster: Software Fault Localization as a Service (SFLaaS)

Qusay Idrees Sarhan, Hassan Bapeer Hassan and Árpád Beszédes
Many tools for enabling developers locating faults in their programs have been proposed in the literature. The majority of the programs they target are those created in the C/C++ and Java. In this paper, we offer a tool named "SFLaaS" for locating faults in programs written in Python, a popular programming language, and is provided as a service rather than as a plugin or a command-line tool to be installed. Thus, our tool can be accessed anytime and from anywhere. The tool employs Spectrum-based fault localization (SBFL) to help Python developers automatically analyze their programs and generate useful data at run-time to be used to produce a ranked list of potentially faulty program elements (i.e., statements). Our proposed tool supports different important features in fault localization such as supporting about 80 SBFL formulas, different tie-breaking methods, showing code elements with different colors, ranging from most suspicious (red) not suspicious (green) based on their suspicious scores, allowing the user to define his/her own formula, etc. Using our tool could help developers to efficiently find the locations of different types of faults in their programs.

Keywords: Debugging, fault localization, Python, SFLaaS, service.