An Enhanced Multifactor Multiobjective Approach for Software Modularization

Muhammad Zakir Khan, Rashid Naseem, Aamir Anwar, Ijaz ul-Haq, Saddam Hussain, Roobaea Alroobaea, Syed Sajid Ullah, Fazlullah Umar and Ghous Ali

Mathematical Problems in Engineering, 2022, vol. 2022, 1-13

Abstract: 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).

Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:hin:jnlmpe:7960610

DOI: 10.1155/2022/7960610

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