Partition Testing Does Not Inspire Confidence (Program Testing)
IEEE Transactions on Software Engineering
Analyzing Partition Testing Strategies
IEEE Transactions on Software Engineering
On the Expected Number of Failures Detected by Subdomain Testing and Random Testing
IEEE Transactions on Software Engineering
Partition Testing vs. Random Testing: The Influence of Uncertainty
IEEE Transactions on Software Engineering
Proportional sampling strategy: a compendium and some insights
Journal of Systems and Software
ECSQ '02 Proceedings of the 7th International Conference on Software Quality
Mirror Adaptive Random Testing
QSIC '03 Proceedings of the Third International Conference on Quality Software
Random testing of interrupt-driven software
Proceedings of the 5th ACM international conference on Embedded software
Adaptive random testing with randomly translated failure region
Proceedings of the 1st international workshop on Random testing
An empirical analysis and comparison of random testing techniques
Proceedings of the 2006 ACM/IEEE international symposium on Empirical software engineering
Acquisition of Morphology of an Indic Language from Text Corpus
ACM Transactions on Asian Language Information Processing (TALIP)
A metric for software readability
ISSTA '08 Proceedings of the 2008 international symposium on Software testing and analysis
The road not taken: Estimating path execution frequency statically
ICSE '09 Proceedings of the 31st International Conference on Software Engineering
International Journal of Computers and Applications
Pairwise-adaptive dissimilarity measure for document clustering
Information Sciences: an International Journal
Harnessing web-based application similarities to aid in regression testing
ISSRE'09 Proceedings of the 20th IEEE international conference on software reliability engineering
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The F-measure - the number of distinct test cases to detect the first program failure - is an effectiveness measure for debug testing strategies. We show that for random testing with replacement, the F-measure will be distributed according to the geometric distribution. A simulation study examines the distribution of two adaptive random testing methods, to study how closely their sampling distributions approximate the geometric distribution, revealing that in the worst case scenario, the sampling distribution for adaptive random testing is very similar to random testing. Our results have provided an answer to a conjecture that adaptive random testing is always a more effective alternative to random testing, with reference to the F-measure. We consider the implications of our findings for previous studies conducted in the area, and make recommendations to future studies.