TY - JOUR A2 - Ali, Ghous AU - Zakir Khan, Muhammad AU - Naseem, Rashid AU - Anwar, Aamir AU - ul-Haq, Ijaz AU - Hussain, Saddam AU - Alroobaea, Roobaea AU - Ullah, Syed Sajid AU - Umar, Fazlullah PY - 2022 DA - 2022/06/08 TI - An Enhanced Multifactor Multiobjective Approach for Software Modularization SP - 7960610 VL - 2022 AB - 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). SN - 1024-123X UR - https://doi.org/10.1155/2022/7960610 DO - 10.1155/2022/7960610 JF - Mathematical Problems in Engineering PB - Hindawi KW - ER -