Poster: Software Fault Localization as a Service (SFLaaS)
Qusay Idrees Sarhan, Hassan Bapeer Hassan and Árpád
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.
fault localization, Python, SFLaaS, service.