PELAS-Program Error-Locating Assistant System
IEEE Transactions on Software Engineering
Simplifying and Isolating Failure-Inducing Input
IEEE Transactions on Software Engineering
Visualization of test information to assist fault localization
Proceedings of the 24th International Conference on Software Engineering
Isolating cause-effect chains from computer programs
ACM SIGSOFT Software Engineering Notes
Bug isolation via remote program sampling
PLDI '03 Proceedings of the ACM SIGPLAN 2003 conference on Programming language design and implementation
Locating causes of program failures
Proceedings of the 27th international conference on Software engineering
Scalable statistical bug isolation
Proceedings of the 2005 ACM SIGPLAN conference on Programming language design and implementation
SOBER: statistical model-based bug localization
Proceedings of the 10th European software engineering conference held jointly with 13th ACM SIGSOFT international symposium on Foundations of software engineering
Empirical Software Engineering
Locating faulty code using failure-inducing chops
Proceedings of the 20th IEEE/ACM international Conference on Automated software engineering
Empirical evaluation of the tarantula automatic fault-localization technique
Proceedings of the 20th IEEE/ACM international Conference on Automated software engineering
Improving test suites for efficient fault localization
Proceedings of the 28th international conference on Software engineering
Locating faults through automated predicate switching
Proceedings of the 28th international conference on Software engineering
Failure proximity: a fault localization-based approach
Proceedings of the 14th ACM SIGSOFT international symposium on Foundations of software engineering
Advanced Engineering Mathematics
Advanced Engineering Mathematics
Statistical debugging using compound boolean predicates
Proceedings of the 2007 international symposium on Software testing and analysis
Proceedings of the 2007 international symposium on Software testing and analysis
Effective Fault Localization using Code Coverage
COMPSAC '07 Proceedings of the 31st Annual International Computer Software and Applications Conference - Volume 01
Fault Localization with Non-parametric Program Behavior Model
QSIC '08 Proceedings of the 2008 The Eighth International Conference on Quality Software
Debugging through Evaluation Sequences: A Controlled Experimental Study
COMPSAC '08 Proceedings of the 2008 32nd Annual IEEE International Computer Software and Applications Conference
ICSE '09 Proceedings of the 31st International Conference on Software Engineering
Capturing propagation of infected program states
Proceedings of the the 7th joint meeting of the European software engineering conference and the ACM SIGSOFT symposium on The foundations of software engineering
How Well Do Test Case Prioritization Techniques Support Statistical Fault Localization
COMPSAC '09 Proceedings of the 2009 33rd Annual IEEE International Computer Software and Applications Conference - Volume 01
IEEE Transactions on Software Engineering
Capturing propagation of infected program states
Proceedings of the the 7th joint meeting of the European software engineering conference and the ACM SIGSOFT symposium on The foundations of software engineering
Fault localization through evaluation sequences
Journal of Systems and Software
Non-parametric statistical fault localization
Journal of Systems and Software
Effective software fault localization by statistically testing the program behavior model
ICICA'11 Proceedings of the Second international conference on Information Computing and Applications
Statistical debugging with elastic predicates
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
Reducing confounding bias in predicate-level statistical debugging metrics
Proceedings of the 34th International Conference on Software Engineering
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Fault localization is one of the most difficult activities in software debugging. Many existing statistical fault-localization techniques estimate the fault positions of programs by comparing the program feature spectra between passed runs and failed runs. Some existing approaches develop estimation formulas based on mean values of the underlying program feature spectra and their distributions alike. Our previous work advocates the use of a non-parametric approach in estimation formulas to pinpoint fault-relevant positions. It is worthy of further study to resolve the two schools of thought by examining the fundamental, underlying properties of distributions related to fault localization. In particular, we ask: Can the feature spectra of program elements be safely considered as normal distributions so that parametric techniques can be soundly and powerfully applied? In this paper, we empirically investigate this question from the program predicate perspective. We conduct an experimental study based on the Siemens suite of programs. We examine the degree of normality on the distributions of evaluation biases of the predicates, and obtain three major results from the study. First, almost all examined distributions of evaluation biases are either normal or far from normal, but not in between. Second, the most fault-relevant predicates are less likely to exhibit normal distributions in terms of evaluation biases than other predicates. Our results show that normality is not common as far as evaluation bias can represent. Furthermore, the effectiveness of our non-parametric predicate-based fault-localization technique weakly correlates with the distributions of evaluation biases, making the technique robust to this type of uncertainty in the underlying program spectra.