Challenges to support automated random testing for dynamically typed languages
Proceedings of the International Workshop on Smalltalk Technologies
Is branch coverage a good measure of testing effectiveness?
Empirical Software Engineering and Verification
Fully automatic and precise detection of thread safety violations
Proceedings of the 33rd ACM SIGPLAN conference on Programming Language Design and Implementation
Sound empirical evidence in software testing
Proceedings of the 34th International Conference on Software Engineering
Proceedings of the 34th International Conference on Software Engineering
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Intuition suggests that random testing of object-oriented programs should exhibit a significant difference in the number of faults detected by two different runs of equal duration. As a consequence, random testing would be rather unpredictable. We evaluate the variance of the number of faults detected by random testing over time. We present the results of an empirical study that is based on 1215 hours of randomly testing 27 Eiffel classes, each with 30 seeds ofthe random number generator. Analyzing over 6 million failures triggered during the experiments, the study provides evidence that the relative number of faults detected by random testing over time is predictable but that different runs of the random test case generator detect different faults. The study also shows that random testing quickly finds faults: the first failure is likely to be triggered within 30 seconds.