Using Data Flow Patterns for Equivalent Mutant Detection
Marinos Kintis, Nicos Malevris · 2014
This paper introduces a set of data flow patterns that reveal code locations able to produce equivalent mutants. For each pattern, a formal definition is given and the necessary conditions implying its existence in the source code of the program under test are described. By identifying such problematic situations, the introduced patterns can provide advice on code locations that should not be mutated. Apart from dealing with equivalent mutants, the proposed patterns are able to identify specific paths for which a mutant is functionally equivalent to the original program. This knowledge can be leveraged by test case generation techniques in order not to target these paths when attempting to kill the corresponding mutants. An empirical study, conducted on a set of manually identified equivalent mutants, provides evidence regarding the detection power of the introduced patterns and unveils their existence in real world software.