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METARO3: Metamorphic Relation Group for Automatic Program Repair

Tingting Wu1, Yunwei Dong1,*

1 School of Computer Science and Engineering, Northwestern Polytechnical University, Xi’an, 710072, China.

* Corresponding Author: Yunwei Dong. Email: email.

Computer Modeling in Engineering & Sciences 2019, 121(3), 909-928. https://doi.org/10.32604/cmes.2019.07809

Abstract

The application of metamorphic testing (MT) on automatic program repair (APR-MT) is used to generate a patch without test oracles by examining whether the input metamorphic relation (MR) is satisfied or not. However, the delivered patch is plausible since it may satisfy the input MR but violate other MRs. This inspires us to propose an improved approach to enhance the effectiveness of APR-MT with metamorphic relation group. Our approach involves three major steps. First, we formally define the repair process of APR-MT by building the model of automatic program repair and metamorphic testing separately. Then, we propose the advanced model of automatic program repair based on metamorphic relation group, named METARO3 , which takes several MRs as input while only one MR is used in APR-MT. We additionally present two kinds of selection strategies to rank MRs in descending order of the fault detection capability, which helps shorten the repair time of finding a patch. To demonstrate the feasibility and procedure of our approach, an illustration example was conducted. The results show that METARO3 can improve the effectiveness of APR-MT significantly.

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Cite This Article

APA Style
Wu, T., Dong, Y. (2019). Metaro3: metamorphic relation group for automatic program repair. Computer Modeling in Engineering & Sciences, 121(3), 909-928. https://doi.org/10.32604/cmes.2019.07809
Vancouver Style
Wu T, Dong Y. Metaro3: metamorphic relation group for automatic program repair. Comput Model Eng Sci. 2019;121(3):909-928 https://doi.org/10.32604/cmes.2019.07809
IEEE Style
T. Wu and Y. Dong, “METARO3: Metamorphic Relation Group for Automatic Program Repair,” Comput. Model. Eng. Sci., vol. 121, no. 3, pp. 909-928, 2019. https://doi.org/10.32604/cmes.2019.07809



cc Copyright © 2019 The Author(s). Published by Tech Science Press.
This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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