Speeding-up mutation testing via data compression and state infection
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Abstract
Mutation testing is widely considered as a high-end test criterion due to the vast number of mutants it generates. Although many efforts have been made to reduce the computational cost of mutation testing, its scalability issue remains in practice. In this paper, we introduce a novel method to speed up mutation testing based on state infection information. In addition to filtering out uninfected test executions, we further select a subset of mutants and a subset of test cases to run leveraging data-compression techniques. In particular, we adopt Formal Concept Analysis (FCA) to group similar mutants together and then select test cases to cover these mutants. To evaluate our method, we conducted an experimental study on six open source Java projects. We used EvoSuite to automatically generate test cases and to collect mutation data. The initial results show that our method can reduce the execution time by 83.93% with only 0.257% loss in precision.
Cite this as
2016. Speeding-up mutation testing via data compression and state infection. PeerJ Preprints 4:e2632v1 https://doi.org/10.7287/peerj.preprints.2632v1Author comment
This is a preprint submission to PeerJ Preprints.
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Competing Interests
The authors declare that they have no competing interests.
Author Contributions
Qianqian Zhu conceived and designed the experiments, performed the experiments, analyzed the data, contributed reagents/materials/analysis tools, wrote the paper, prepared figures and/or tables, performed the computation work, reviewed drafts of the paper.
Annibale Panichella conceived and designed the experiments, contributed reagents/materials/analysis tools, wrote the paper, reviewed drafts of the paper.
Andy Zaidman conceived and designed the experiments, contributed reagents/materials/analysis tools, wrote the paper, prepared figures and/or tables, reviewed drafts of the paper.
Data Deposition
The following information was supplied regarding data availability:
The raw data or code is included in the manuscript.
Funding
This work was supported by the Testroots project from the Dutch Science Foundation NWO. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
