A systematic approach for software refactoring based on class and method level for AI application Online publication date: Tue, 07-Sep-2021
by Rasmita Panigrahi; Sanjay K. Kuanar; Lov Kumar; Neelamadhab Padhy
International Journal of Powertrains (IJPT), Vol. 10, No. 2, 2021
Abstract: Many researchers have investigated the different techniques to detect software code smells, which can be removed by software refactoring. In this paper, the author presents refactoring techniques and their examples and the proposed model for getting the qualitative code after implementing refactoring techniques. The author proposed an algorithm for the extract and move method, and a set of refactoring techniques. This primary goal is to depict refactoring methods and defend retained transition rules among the groups. The author has discussed the state-of-the-art software refactoring techniques, causes of refactoring, and the proposed model. The author has shown a simulation model suggesting transition probability, which allows for making decision software status. The results show that the proposed approach can detect software refactoring accurately with precision and recall values ranging from 88% to 100%. The transformation rules and proposed algorithms and models are suitable and adequate for automated refactoring to improve software quality.
Online publication date: Tue, 07-Sep-2021
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