Statistical fault localization aims at detecting execution features that correlate with failures, such as whether individual lines are part of the execution. We introduce SFLKit, an out-of-the-box workbench for statistical fault localization. The framework provides straightforward access to the fundamental concepts of statistical fault localization. It supports five predicate types, four coverage-inspired spectra, like lines, and 44 similarity coefficients, e.g., TARANTULA or OCHIAI, for statistical program analysis.
SFLKit separates the execution of tests from the analysis of the results and is therefore independent of the used testing framework. It leverages program instrumentation to enable the logging of events and derives the predicates and spectra from these logs. This instrumentation allows for introducing multiple programming languages and the extension of new concepts in statistical fault localization. Currently, SFLKit supports the instrumentation of Python programs. It is highly configurable, requiring only the logging of the required events.
Tue 15 NovDisplayed time zone: Beijing, Chongqing, Hong Kong, Urumqi change
14:00 - 15:30 | Debugging/localizationResearch Papers / Industry Paper / Demonstrations / Ideas, Visions and Reflections at SRC LT 51 Chair(s): Mauro Pezze USI Lugano; Schaffhausen Institute of Technology | ||
14:00 15mTalk | Metadata-Based Retrieval for Resolution Recommendation in AIOps Industry Paper DOI | ||
14:15 15mTalk | PaReco: Patched Clones and Missed Patches among the Divergent Variants of a Software Family Research Papers Poedjadevie Kadjel Ramkisoen University of Antwerp; Flanders Make, John Businge University of Antwerp; Flanders Make; University of Nevada at Las Vegas, Brent van Bladel University of Antwerp; Flanders Make, Alexandre Decan University of Mons; F.R.S.-FNRS, Serge Demeyer University of Antwerp; Flanders Make, Coen De Roover Vrije Universiteit Brussel, Foutse Khomh Polytechnique Montréal DOI | ||
14:30 15mTalk | Fault Localization to Detect Co-change Fixing Locations Research Papers Yi Li New Jersey Institute of Technology, Shaohua Wang New Jersey Institute of Technology, Tien N. Nguyen University of Texas at Dallas DOI | ||
14:45 15mTalk | Reflections on Software Failure Analysis Ideas, Visions and Reflections Paschal Amusuo Purdue University, Aishwarya Sharma Purdue University, Siddharth R. Rao Purdue University, Abbey Vincent Purdue University, James C. Davis Purdue University DOI | ||
15:00 7mTalk | eGEN: An Energy-saving Modeling Language and Code Generator for Location-sensing of Mobile Apps Demonstrations Kowndinya Boyalakuntla Indian Institute of Technology Tirupati, Marimuthu Chinnakali National Institute of Technology Karnataka, Sridhar Chimalakonda IIT Tirupati, K. Chandrasekaran National Institute of Technology Karnataka | ||
15:08 7mTalk | SFLKit: A Workbench for Statistical Fault Localization Demonstrations Marius Smytzek CISPA Helmholtz Center for Information Security, Andreas Zeller CISPA Helmholtz Center for Information Security Pre-print | ||