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.
Mon 17 AprDisplayed time zone: Dublin change
14:00 - 15:30 | Session 4: Fault Localization & DebuggingResearch Papers / Tool Demo / Industry / Journal-First Papers at Pearse suite Chair(s): Shin Yoo KAIST | ||
14:00 20mTalk | Flake Aware Culprit Finding Industry Tim A. D. Henderson Google LLC, Bobby Dorward Google, Eric Nickell Google, Collin Johnson Google, Avi Kondareddy Google LLC Pre-print | ||
14:20 20mTalk | An Empirical Characterization of Software Bugs in Open-Source Cyber-Physical Systems Journal-First Papers Fiorella Zampetti University of Sannio, Italy, Ritu Kapur University of Sannio, Massimiliano Di Penta University of Sannio, Italy, Sebastiano Panichella Zurich University of Applied Sciences | ||
14:40 20mTalk | A Case Against Coverage-Based Program Spectra Research Papers Péter Attila Soha Department of Software Engineering, University of Szeged, Tamás Gergely Department of Software Engineering, University of Szeged, Ferenc Horv�th University of Szeged, Department of Software Engineering, Béla Vancsics Department of Software Engineering, University of Szeged, Árpád Beszédes Department of Software Engineering, University of Szeged | ||
15:00 10mTalk | SFLaaS: Software Fault Localization as a Service Tool Demo Qusay Idrees Sarhan Department of Software Engineering, University of Szeged, Hassan Bapeer Hassan University of Duhok, Árpád Beszédes Department of Software Engineering, University of Szeged |