Poster: Software Fault Localization as a Service (SFLaaS)
Qusay Idrees Sarhan, Hassan Bapeer Hassan, Árpád Beszédes · 2023
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 languages. 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) to 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 faults in their programs.