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Future of Information and Communication Conference

FICC 2018: Advances in Information and Communication Networks pp 256–270Cite as

MUT-APR: MUTation-Based Automated Program Repair Research Tool

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 887))

Abstract

Automated program repair (APR) techniques introduced to fix faults through the insertion of new code or modifying existing ones until the program under test passes a given set of test cases called repair tests. MUTation based Automated Program Repair (MUT-APR) is a prototype tool built on the top of GenProg to fix binary operator faults in C programs. MUT-APR is a configurable mutation-based APR tool that varies the APR mechanisms and components to find the best combination for a problem under study. The implementation of MUT-APR components is discussed in this paper as well as how the tool can be used to repair faults. Limitations of the existing framework are also discussed.

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Acknowledgment

The authors would like to thank Westley Weimer and his research group for sharing GenProg, and Yuhua Qi et al. [14] for sharing the GenProg-FL tool.

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Authors and Affiliations

  1. Faculty of Computing and Information Technology, King Abdulaziz University, Jeddah, 21589, Kingdom of Saudi Arabia

    Fatmah Y. Assiri

  2. Computer Science Department, Colorado State University, Fort Collins, CO, 80523-1873, USA

    James M. Bieman

Authors
  1. Fatmah Y. Assiri
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  2. James M. Bieman
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Corresponding author

Correspondence to Fatmah Y. Assiri .

Editor information

Editors and Affiliations

  1. Faculty of Science and Engineering, Saga University, Saga, Japan

    Kohei Arai

  2. The Science and Information (SAI) Organization, Bradford, West Yorkshire, UK

    Supriya Kapoor

  3. The Science and Information (SAI) Organization, New Delhi, India

    Rahul Bhatia

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Assiri, F.Y., Bieman, J.M. (2019). MUT-APR: MUTation-Based Automated Program Repair Research Tool. In: Arai, K., Kapoor, S., Bhatia, R. (eds) Advances in Information and Communication Networks. FICC 2018. Advances in Intelligent Systems and Computing, vol 887. Springer, Cham. https://doi.org/10.1007/978-3-030-03405-4_17

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  • DOI: https://doi.org/10.1007/978-3-030-03405-4_17

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-03404-7

  • Online ISBN: 978-3-030-03405-4

  • eBook Packages: EngineeringEngineering (R0)

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