Evaluating the effectiveness of reliability-assurance techniques
Journal of Systems and Software
Critical slicing for software fault localization
ISSTA '96 Proceedings of the 1996 ACM SIGSOFT international symposium on Software testing and analysis
The use of program profiling for software maintenance with applications to the year 2000 problem
ESEC '97/FSE-5 Proceedings of the 6th European SOFTWARE ENGINEERING conference held jointly with the 5th ACM SIGSOFT international symposium on Foundations of software engineering
Effect of test set minimization on fault detection effectiveness
Software—Practice & Experience
Data mining: concepts and techniques
Data mining: concepts and techniques
TACCLE: a methodology for object-oriented software testing at the class and cluster levels
ACM Transactions on Software Engineering and Methodology (TOSEM)
Finding failures by cluster analysis of execution profiles
ICSE '01 Proceedings of the 23rd International Conference on Software Engineering
Pursuing failure: the distribution of program failures in a profile space
Proceedings of the 8th European software engineering conference held jointly with 9th ACM SIGSOFT international symposium on Foundations of software engineering
Prioritizing Test Cases For Regression Testing
IEEE Transactions on Software Engineering
Visualization of test information to assist fault localization
Proceedings of the 24th International Conference on Software Engineering
Mining intrusion detection alarms for actionable knowledge
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
Automated support for classifying software failure reports
Proceedings of the 25th International Conference on Software Engineering
Finding Latent Code Errors via Machine Learning over Program Executions
Proceedings of the 26th International Conference on Software Engineering
Active learning for automatic classification of software behavior
ISSTA '04 Proceedings of the 2004 ACM SIGSOFT international symposium on Software testing and analysis
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During the debugging of a program to be released, it is unnecessary and impractical for developers to check every failure execution. How to extract the typical ones from the vast set of failure executions is very important for reducing the debugging efforts. In this paper, a revised Markov model used to depict program behaviors is presented firstly. Based on this model, the dissimilarity of two profile matrixes is also defined. After separating the failure executions and non-failure executions into two different subsets, iterative partition clustering and a sampling strategy called priority-ranked n-per-cluster are employed to extract representative failure executions. Finally, with the assistance of our prototype CppTest, we have performed experiment on five subject programs. The results show that the clustering and sampling techniques based on revised Markov model is more effective to find faults than Podgurski's method.