International Journal of Information Engineering and Electronic Business(IJIEEB)

ISSN: 2074-9023 (Print), ISSN: 2074-9031 (Online)

Published By: MECS Press

IJIEEB Vol.12, No.4, Aug. 2020

Reduction of Multiple Move Method Suggestions Using Total Call-Frequencies of Distinct Entities

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Atish Kumar Dipongkor, Rayhanul Islam, Nadia Nahar, Iftekhar Ahmed, Kishan Kumar Ganguly, S.M. Arif Raian, Abdus Satter

Index Terms

Feature Envy, Move Method Refactoring.


Inappropriate placement of methods causes Feature Envy (FE) code smell and makes classes coupled with each other. To achieve cohesion among classes, FE code smell can be removed using automated Move Method Refactoring (MMR) suggestions. However, challenges arise when existing techniques provide multiple MMR suggestions for a single FE instance. The developers need to manually find an appropriate target classes for applying MMR as an FE instance cannot be moved to multiple classes. In this paper, a technique is proposed named MultiMMRSReducer, to reduce multiple MMR suggestions by considering the Total Call-Frequencies of Distinct Entities (TCFDE). Experimental results show that TCFDE can reduce the multiple MMR suggestions of an FE instance and performs 77.92% better than an existing approach, namely, JDeodorant. Moreover, it can ensure minimum future changes in the dependent classes of an FE instance.

Cite This Paper

Atish Kumar Dipongkor, Rayhanul Islam, Nadia Nahar, Iftekhar Ahmed, Kishan Kumar Ganguly, S.M. Arif Raian, Abdus Satter, " Reduction of Multiple Move Method Suggestions Using Total Call-Frequencies of Distinct Entities", International Journal of Information Engineering and Electronic Business(IJIEEB), Vol.12, No.4, pp. 21-29, 2020. DOI: 10.5815/ijieeb.2020.04.03


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