Handbook of Software Fault Localization: Foundations and Advances, W.E. Wong and T.H. Tse (eds.), Wiley-IEEE Press, Hoboken, NJ (accepted for publication)
Emerging aspects of software fault localization

T.H. Tse 1 , D. Lo 2 , A. Gorce 3 , M. Perscheid 4 , R. Hirschfeld 4 , and W.E. Wong 5


In this final chapter of the Handbook, we introduce emerging, innovative methods in software fault localization. First, we present scientific and systematic hypothesis-testing techniques, and show they may be applied in practice. Second, for fault localization in the absence of a test oracle, we present a semi-proving methodology based on metamorphic relations and symbolic evaluation. It hinges on causes and effects instead of statistical probabilities. Third, we present an approach to predict the effectiveness of fault localization tools using machine learning. Lastly, we discuss why manually produced test cases are not ideal for fault localization, and explain how to mitigate the problem by using automatically generated test cases.
1. (Corresponding author.)
Department of Computer Science, The University of Hong Kong, Pokfulam, Hong Kong.
2. School of Computing and Information Systems, Singapore Management University, Singapore.
3. School of Informatics, Computing, and Cyber Systems, Northern Arizona University, Flagstaff, AZ, USA.
4. Department of Computer Science, Universitšt Potsdam, Brandenburg, Germany
5. (Corresponding author.)
Department of Computer Science, University of Texas at Dallas, Richardson, TX, USA


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