Improving Source Code Quality by Minimizing Refactoring Effort
Hayatou Oumarou(1*); Kabirrou Hamadou Tizi(2);
(1) The University of Maroua
(2) The University of Maroua
(*) Corresponding Author
AbstractSoftware maintenance is a time-consuming and costly endeavor. As a part of maintenance, refactoring is aimed at enhancing quality. Due to project deadlines and limited resources, developers need to prioritize refactoring activities. In this paper, we present a livestock management-inspired approach for identifying and prioritizing classes to refactor within an object-oriented program. This approach empowers developers to enhance the time/quality ratio. The novelty of our approach lies in utilizing established metrics for detecting code defects to prioritize each class. To validate its effectiveness, the approach was tested on four distinct Pharo-based open source programs. The results demonstrate the approach's efficacy in improving software quality, reducing development time, and enhancing team productivity
KeywordsEvaluation Model; Maintainability; Metric; Refactoring; Software Quality
|
Full Text:PDF |
Article MetricsAbstract view: 58 timesPDF view: 50 times |
Digital Object Identifierhttps://doi.org/10.33096/ilkom.v16i2.1908.145-150 |
Cite |
References
M. M. Lehman, J. F. Ramil, P. D. Wernick, D. E. Perry and W. M. Turski, "Metrics and laws of software evolution-the nineties," International Software Metrics Symposium, vol. 4, 1997.
S. S. Ali, M. S. Zafar And M. T. Saeed, "Effort estimation problems in software maintenance–a survey," 2020.
Z. R. e. A. Fontana, Software Clone Detection and Refactoring, University of Milano-Bicoco, Italy, 2019.
K. e. a. Martin Fowler, Refactoring: Improving the Design of Existing code, Wesley, 1999.
N. Walkinshaw And L. Minku, "Are 20% of files responsible for 80% of defects?," ACM/IEEE International Symposium on Empirical Software Engineering and Measurement., vol. I, no. 12, pp. 1-10., 2018.
A. ChaouldHary, Effective Prioritization of Classes for Reduced Refactoring Effort ", 31e conférence internationale IEEE/ACM sur le génie logiciel automatisé, Communiqué, 2018.
G. Lacerda, F. Petrillo, M. Pimenta And G. Yann-Gaël, "Code smells and refactoring: A tertiary systematic review of challenges and observations.," vol. 167, 2020.
o. Hachemane, évaluation de l'impact du refactoring basé sur les clones sur la qualité (maintenabillté-testabillté) des systèmes orientés objet, 2018.
M. D.-P. Vidal, approach to prioritize code smells for refactoring, 2020.
H. H. I. K. Yang, Filtering Clones for Individual User Based on Machine Learning Analysis, 2019.
Z. Fontana, Code smell severity classification using machine learning techniques, 2019.
A. Kaur, S. Jain And S. Goel, "Sandpiper optimization algorithm: a novel approach for solving real-life engineering problems.," Applied Intelligence, vol. 50, pp. 582-619, 2020.
e. H. Zhao, Predicting classes in need of refactoring: an application of static metrics, 2006.
Khosla, Priorisation des classes pour le refactoring : une étape vers l'amélioration de la qualité du logiciel, 2020.
E. Steidl, Prioritizing maintainability defects based on refactoring recommendations, in: in Proceedings of the 22nd International Conference on Program Comprehension, 2018.
T. e. B. Kosker, An expert system for determining candidate software classes for refactoring, 2019.
J. K. C. Rani, Prioritization of smelly classes: A two phase approach (reducing refactoring efforts), 2017.
A. C. Tarwani, Prioritization of code restructuring for severely affected classes under release time constraints, 2018.
H. Oumarou, D. K. Moulla and Kolyang, "Using Quality Measures During the Software Development Process: Case Study of Cameroonian Software Industry.," Indonesian Journal of Computer Science, vol. 12, no. 3, 2023.
S. R. C. a. C. F. Kemerer, A Metrics Suite for Object, IEEE Transaction on Software Engineering, 2020.
C. a. N. Harrison, Evaluation of the MOOD Set of Object-Oriented Software Metrics, IEEE Transaction on Software, 2020.
O. Hayatou, "A Source-Code Maintainability Evaluation Model for Software Products.," vol. 3, no. 2, 2023.
R. Jangra, O. P. Sangwan and D. Nandal, "A Novel Approach for Software Effort Estimation using Optimized C&K Metrics," 2022.
P. Mengal, "Métriques Et Critères D’évaluation De La Qualité Du Code Source D’un Logiciel," Revue d’un professionnel de l’industrie du logicie, Paris, 2019.
N. Anquetil, A. Etien, M. Houekpetodji, B. Verhaeghe, S. Ducasse, T. Clotilde, D. Fatiha, S. Jerôme and D. Mustapha, "Modular Moose: a new generation of software reverse engineering platform.," Reuse in Emerging Software Engineering Practices, no. 19, 2020.
Refbacks
- There are currently no refbacks.
Copyright (c) 2024 Hayatou Oumarou, Kabirrou Hamadou Tizi
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.