McCurdy, C.J., McMinn, P.S. orcid.org/0000-0001-9137-7433 and Kapfhammer, G.M. (2017) mrstudyr: Retrospectively Studying the Effectiveness of Mutant Reduction Techniques. In: 2016 IEEE International Conference on Software Maintenance and Evolution (ICSME). 2016 International Conference on Software Maintenance and Evolution (ICSME 2016), 2/10/2016 - 10/10/2016, Raleigh, North Carolina, USA. IEEE ISBN 978-1-5090-3806-0
Abstract
Mutation testing is a well-known method for measuring a test suite’s quality. However, due to its computational expense and intrinsic difficulties (e.g., detecting equivalent mutants and potentially checking a mutant’s status for each test), mutation testing is often challenging to practically use. To control the computational cost of mutation testing, many reduction strategies have been proposed (e.g., uniform random sampling over mutants). Yet, a stand-alone tool to compare the efficiency and effectiveness of these methods is heretofore unavailable. Since existing mutation testing tools are often complex and languagedependent, this paper presents a tool, called mrstudyr, that enables the “retrospective” study of mutant reduction methods using the data collected from a prior analysis of all mutants. Focusing on the mutation operators and the mutants that they produce, the presented tool allows developers to prototype and evaluate mutant reducers without being burdened by the implementation details of mutation testing tools. Along with describing mrstudyr’s design and overviewing the experimental results from using it, this paper inaugurates the public release of this open-source tool.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2016 IEEE. This is an author produced version of a paper subsequently published in Software Maintenance and Evolution (ICSME), 2016 IEEE International Conference on. Uploaded in accordance with the publisher's self-archiving policy. |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Computer Science (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 13 Sep 2016 08:56 |
Last Modified: | 30 Jun 2017 20:32 |
Published Version: | https://doi.org/10.1109/ICSME.2016.92 |
Status: | Published |
Publisher: | IEEE |
Refereed: | Yes |
Identification Number: | 10.1109/ICSME.2016.92 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:104206 |