Is non-parametric hypothesis testing model robust for statistical fault localization?
Information and Software Technology
Fault localization through evaluation sequences
Journal of Systems and Software
Directed test generation for effective fault localization
Proceedings of the 19th international symposium on Software testing and analysis
Non-parametric statistical fault localization
Journal of Systems and Software
A diagnostic reasoning approach to defect prediction
IEA/AIE'11 Proceedings of the 24th international conference on Industrial engineering and other applications of applied intelligent systems conference on Modern approaches in applied intelligence - Volume Part II
Prioritizing tests for fault localization through ambiguity group reduction
ASE '11 Proceedings of the 2011 26th IEEE/ACM International Conference on Automated Software Engineering
How well does test case prioritization integrate with statistical fault localization?
Information and Software Technology
Information and Software Technology
Fault localization prioritization: Comparing information-theoretic and coverage-based approaches
ACM Transactions on Software Engineering and Methodology (TOSEM) - In memoriam, fault detection and localization, formal methods, modeling and design
A theoretical analysis of the risk evaluation formulas for spectrum-based fault localization
ACM Transactions on Software Engineering and Methodology (TOSEM) - Testing, debugging, and error handling, formal methods, lifecycle concerns, evolution and maintenance
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In continuous integration, a tight integration of test case prioritization techniques and fault-localization techniques may both expose failures faster and locate faults more effectively. Statistical fault-localization techniques use the execution information collected during testing to locate faults. Executing a small fraction of a prioritized test suite reduces the cost of testing, and yet the subsequent fault localization may suffer. This paper presents the first empirical study to examine the impact of test case prioritization on the effectiveness of fault localization. Among many interesting empirical results, we find that coverage-based and random techniques can be more effective than distribution-based techniques in supporting statistical fault localization.