The search for the laws of automatic random testing
Proceedings of the 28th Annual ACM Symposium on Applied Computing
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Automated random testing is an effective and predictable method for finding faults. While it was recently studied both in practice and in theory, no general laws were found that express the number of faults in function of the time or the number of tests performed. This article evaluates the Michaelis-Menten equation (Max * t)/(K + t) as a law for representing the number of faults found by automated random testing. Max is the number of faults it can uncover in the code, K is a constant dependent on the tested code and the strategy used and t is the number of tests. The evaluation relies on the testing of more than 6000 Java classes from the Qualitas Corpus.