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Multi-dimensional information-driven many-objective software remodularization approach

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Abstract

Most of the search-based software remodularization (SBSR) approaches designed to address the software remodularization problem (SRP) areutilizing only structural information-based coupling and cohesion quality criteria. However, in practice apart from these quality criteria, there require other aspects of coupling and cohesion quality criteria such as lexical and changed-history in designing the modules of the software systems. Therefore, consideration of limited aspects of software information in the SBSR may generate a sub-optimal modularization solution. Additionally, such modularization can be good from the quality metrics perspective but may not be acceptable to the developers. To produce a remodularization solution acceptable from both quality metrics and developers’ perspectives, this paper exploited more dimensions of software information to define the quality criteria as modularization objectives. Further, these objectives are simultaneously optimized using a tailored many-objective artificial bee colony (MaABC) to produce a remodularization solution. To assess the effectiveness of the proposed approach, we applied it over five software projects. The obtained remodularization solutions are evaluated with the software quality metrics and developers view of remodularization. Results demonstrate that the proposed software remodularization is an effective approach for generating good quality modularization solutions.

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Author information

Authors and Affiliations

  1. Department of Computer Science Engineering & Information Technology, Jaypee Istitute of Information Technology, Noida, 201307, India

    Amarjeet Prajapati

  2. Department of Computer Science & Engineering, Thapar Institute of Engineering & Technology, Punjab, 147004, India

    Anshu Parashar

  3. Department of Computer Science, Government College Barota, Haryana, 131301, India

    Amit Rathee

Authors
  1. Amarjeet Prajapati
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  2. Anshu Parashar
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  3. Amit Rathee
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Corresponding author

Correspondence to Amarjeet Prajapati.

Additional information

Amarjeet Prajapati is currently working as Assistant Professor in Department of Computer Science Engineering & Information Technology at Jaypee Institute of Information Technology, India. He received his PhD degree from National Institute of Technology, India. He has published many research papers in reputed journals and conferences. His area of interest includes software engineering, metaheuristic algorithms, machine learning, and soft computing.

Anshu Parashar is currently working as Assistant Professor in Department of Computer Science & Engineering at Thapar Institute of Engineering & Technology (TIET), India. He received his PhD degree from National Institute of Technology, India. He has published many research papers papers in reputed journals and various national and international conferences. His area of interest includes software engineering, machine learning, blockchain and cloud computing for sustainable development.

Amit Rathee is currently working as Assistant Professor in the Department of Computer Science, Government College Barota, India. He was awarded a PhD degree from National Institute of Technology, India in 2020. He has presented and published many research papers in reputed journals and various national and international conferences. His research interests include software engineering, human-computer interaction, soft computing, algorithm, and artificial intelligence.

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Prajapati, A., Parashar, A. & Rathee, A. Multi-dimensional information-driven many-objective software remodularization approach. Front. Comput. Sci. 17, 173209 (2023). https://doi.org/10.1007/s11704-022-1449-2

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