Improving Evolutionary Testing in the Presence of Function-Assigned Flags

Evolutionary structural testing, an approach to automatically generating relevant unit test cases, encounters difficulties when the tested software contains boolean variables. This issue, known as the flag problem, has been studied by many researchers. However, previous work does not address the issue of function-assigned flags which constitutes a special type of the flag problem that often occurs in the context of object-orientation. This paper elaborates on a new approach to the flag problem that can also handle function-assigned flags while being applicable to the conventional flag problem, as well. It relies on a code transformation that leads to an improved fitness landscape which provides better guidance to the evolutionary search. We present four case studies including a fitness landscape analysis and empirical results. The results show that the suggested code transformation improves evolutionary structural testing in the presence of function-assigned flags.