A Probabilistic Analysis of the Efficiency of Automated Software Testing

摘要

We study the relative efficiencies of the random and systematic approaches to automated software testing. Using a simple but realistic set of assumptions, we propose a general model for software testing and define sampling strategies for random () and systematic () testing, where each sampling is associated with a sampling cost: 1 and units of time, respectively. The two most important goals of software testing are: (i) achieving in minimal time a given degree of confidence in a program's correctness and (ii) discovering a maximal number of errors within a given time bound . For both (i) and (ii), we show that there exists a bound on beyond which performs better than