SFLaaS: Software Fault Localization as a Service
Qusay Idrees Sarhan, Hassan Bapeer Hassan and Árpád
Beszédes
Many tools for enabling developers to locate bugs in
their programs have been proposed in the literature. The majority
of programs they target are based on C/C++ and Java. In this
paper, we offer a tool named "SFLaaS" for locating faults in
programs written in Python 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 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.
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