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Research Article | Open Access |

A Multiple-Criteria Decision Making Model for Ranking Refactoring Patterns

Author 1: Abdulmajeed Aljuhani Author 2: Luigi Benedicenti Author 3: Sultan Alshehri
International Journal of Advanced Computer Science and Applications (IJACSA) · Vol. 8, No. 11 · Published 2017

DOI: https://doi.org/10.14569/IJACSA.2017.081101

Abstract

The analytic network process (ANP) is capable of structuring decision problems and finding mathematically determined judgments built on knowledge and experience. Researches suggest that ANP can be useful in software development, where complicated decisions happen routinely. In extreme programming (XP), the refactoring is applied where the code smells bad. This might cost more effort and time. As a result, in order to increase the advantages of refactoring in less effort and time, the analytic network process has been used to accomplish this purpose. This paper presents an example of applying the ANP in order to rank the refactoring patterns regarding the internal code quality attributes. A case study that was conducted in an academic environment is presented in this paper. The results of the case study show the benefits of using the ANP in XP development cycle.

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How to Cite this Article

Aljuhani, A., Benedicenti, L., & Alshehri, S. (2017). A Multiple-Criteria Decision Making Model for Ranking Refactoring Patterns. International Journal of Advanced Computer Science and Applications, 8(11). https://doi.org/10.14569/IJACSA.2017.081101

Aljuhani, Abdulmajeed, et al.. "A Multiple-Criteria Decision Making Model for Ranking Refactoring Patterns." International Journal of Advanced Computer Science and Applications, vol. 8, no. 11, 2017, https://doi.org/10.14569/IJACSA.2017.081101.

@article{Aljuhani2017,
  title     = {A Multiple-Criteria Decision Making Model for Ranking Refactoring Patterns},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {8},
  number    = {11},
  year      = {2017},
  publisher = {The Science and Information Organization},
  author    = {Abdulmajeed Aljuhani and Luigi Benedicenti and Sultan Alshehri},
  doi       = {10.14569/IJACSA.2017.081101},
  url       = {https://doi.org/10.14569/IJACSA.2017.081101}
}

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