Abstract
This paper presents some connections between dependence analysis and mutation testing. Specifically, dependence analysis can be applied to two problems in mutation testing, captured by the questions:
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1.
How do we avoid the creation of equivalent mutants?
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2.
How do we generate test data that kills non-equivalent mutants?
The theoretical connections described here suggest ways in which a dependence analysis tool might be used, in combination with existing tools for mutation testing, for test-data generation and equivalent-mutant detection.
In this paper the variable orientated, fine grained dependence framework of Jackson and Rollins is used to achieve these two goals. Yhis framework of dependence analysis appears to be better suited to mutation testing than the more traditional, Program Dependence Graph (PDG) approach, used in slicing and other forms of program analysis.
The relationship between dependence analysis and muataion testing is used to defined an augmented mutation testing process, with starts and ends with dependence analysis phases. The pre-analysis removes a class of equivalent mutants from further analysis, while the post-analysis phase is used to simplify the human effort required ti study the few mutants that evade the automated phases of the process.
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Harman, M., Hierons, R., Danicic, S. (2001). The Relationship Between Program Dependence and Mutation Analysis. In: Wong, W.E. (eds) Mutation Testing for the New Century. The Springer International Series on Advances in Database Systems, vol 24. Springer, Boston, MA. https://doi.org/10.1007/978-1-4757-5939-6_4
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