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Erschienen in:
2015 | OriginalPaper | Buchkapitel
Searching for Strongly Subsuming Higher Order Mutants by Applying Multi-objective Optimization Algorithm
verfasst von : Quang Vu Nguyen, Lech Madeyski
Erschienen in: Advanced Computational Methods for Knowledge Engineering
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Higher order mutation testing is considered a promising solution for overcoming the main limitations of first order mutation testing. Strongly subsuming higher order mutants (SSHOMs) are the most valuable among all kinds of higher order mutants (HOMs) generated by combining first order mutants (FOMs). They can be used to replace all of its constituent FOMs without scarifying test effectiveness. Some researchers indicated that searching for SSHOMs is a promising approach. In this paper, we not only introduce a new classification of HOMs but also new objectives and fitness function which we apply in multi-objective optimization algorithm for finding valuable SSHOMs.