An Enhanced Multifactor Multiobjective Approach for Software Modularization
Issue date
2022Author
Khan, Muhammad Zakir
Naseem, Rashid
Haq, Ijaz Ul
Hussain, Saddam
Alroobaea, Roobaea
Ullah, Syed Sajid
Umar, Fazlullah
Suggested citation
Khan, Muhammad Zakir;
Naseem, Rashid;
Haq, Ijaz Ul;
Hussain, Saddam;
Alroobaea, Roobaea;
Ullah, Syed Sajid;
Umar, Fazlullah;
.
(2022)
.
An Enhanced Multifactor Multiobjective Approach for Software Modularization.
Mathematical Problems in Engineering, 2022, vol. 2022, 7960610.
https://doi.org/10.1155/2022/7960610.
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Complex software systems, meant to facilitate organizations, undergo frequent upgrades that can erode the system architectures. Such erosion makes understandability and maintenance a challenging task. To this end, software modularization provides an architectural-level view that helps to understand system architecture from its source code. For modularization, nondeterministic search-based optimization uses single-factor single-objective, multifactor single-objective, and single-factor multiobjective, which have been shown to outperform deterministic approaches. The proposed MFMO approach, which uses both a heuristic (Hill Climbing and Genetic) and a meta-heuristic (nondominated sorting genetic algorithms NSGA-II and III), was evaluated using five data sets of different sizes and complexity. In comparison to leading software modularization techniques, the results show an improvement of 4.13% in Move and Join operations (MoJo, MoJoFM, and NED).
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Mathematical Problems in Engineering, 2022, vol. 2022, 7960610European research projects
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