Testability transformation based on equivalence of target statements

Abstract

The application of genetic algorithms in automatically generating test data has become a research hotspot and produced many results in recent years. However, its applicability is limited in the presence of flag variables. This issue, known as the flag problem, has been studied by many researchers to date. We propose a novel method of testability transformation to tackle the flag problem. Different from traditional transformation methods, in our method, the key step is not the transformation of source code, but that of target statements. We search for a new target statement (or a set of target statements) equivalent to the original one and then transform the problem of generating test data that cover the original target statement into the one that cover the new target statement (or a set of target statements). We apply our method in many real-world programs, and the experimental results show its effectiveness.