research-article

Software Architecture Recovery using Genetic Black Hole Algorithm

Authors:

Kawal Jeet,

Renu DhirAuthors Info & Claims

ACM SIGSOFT Software Engineering Notes, Volume 40, Issue 1

Pages 1 - 5

https://doi.org/10.1145/2693208.2693230

Published: 06 February 2015 Publication History

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Abstract

Software clustering is a technique that is used to manage a software system by partitioning it into smaller subsystems containing highly related modules. Search-based software clustering techniques are found to be beneficial in effective partitioning of software systems. In this paper, we propose a search-based technique that is based on a combination of a nature-inspired black-hole algorithm and a genetic algorithm for software clustering. In order to evaluate the success of this approach, it has been applied to some real-world software systems. It is observed that this approach deduces a structure similar to the original architecture of the software system concerned.

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Cited By

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Sarhan QAhmed BBures MZamli K(2022)Software Module Clustering: An In-Depth Literature AnalysisIEEE Transactions on Software Engineering10.1109/TSE.2020.304255348:6(1905-1928)Online publication date: 1-Jun-2022
https://dl.acm.org/doi/10.1109/TSE.2020.3042553
Abualigah LElaziz MSumari PKhasawneh AAlshinwan MMirjalili SShehab MAbuaddous HGandomi A(2022)Black hole algorithm: A comprehensive surveyApplied Intelligence10.1007/s10489-021-02980-552:10(11892-11915)Online publication date: 1-Aug-2022
https://dl.acm.org/doi/10.1007/s10489-021-02980-5
Assunção WVergilio SLopez-Herrejon R(2022)Reengineering UML Class Diagram Variants into a Product Line ArchitectureUML-Based Software Product Line Engineering with SMarty10.1007/978-3-031-18556-4_18(393-414)Online publication date: 28-Sep-2022
https://doi.org/10.1007/978-3-031-18556-4_18
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Index Terms

Software Architecture Recovery using Genetic Black Hole Algorithm
1. Social and professional topics
  1. Professional topics
    1. Management of computing and information systems
      1. Software management
        Software maintenance
2. Software and its engineering
  1. Software creation and management
    1. Software post-development issues

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Published In

cover image ACM SIGSOFT Software Engineering Notes

ACM SIGSOFT Software Engineering Notes Volume 40, Issue 1

January 2015

237 pages

ISSN:0163-5948

DOI:10.1145/2693208

Editor:
Michael Wing

Issue’s Table of Contents

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 06 February 2015

Published in SIGSOFT Volume 40, Issue 1

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Sarhan QAhmed BBures MZamli K(2022)Software Module Clustering: An In-Depth Literature AnalysisIEEE Transactions on Software Engineering10.1109/TSE.2020.304255348:6(1905-1928)Online publication date: 1-Jun-2022
https://dl.acm.org/doi/10.1109/TSE.2020.3042553
Abualigah LElaziz MSumari PKhasawneh AAlshinwan MMirjalili SShehab MAbuaddous HGandomi A(2022)Black hole algorithm: A comprehensive surveyApplied Intelligence10.1007/s10489-021-02980-552:10(11892-11915)Online publication date: 1-Aug-2022
https://dl.acm.org/doi/10.1007/s10489-021-02980-5
Assunção WVergilio SLopez-Herrejon R(2022)Reengineering UML Class Diagram Variants into a Product Line ArchitectureUML-Based Software Product Line Engineering with SMarty10.1007/978-3-031-18556-4_18(393-414)Online publication date: 28-Sep-2022
https://doi.org/10.1007/978-3-031-18556-4_18
Pashaei EPashaei E(2021)Training Feedforward Neural Network Using Enhanced Black Hole Algorithm: A Case Study on COVID-19 Related ACE2 Gene Expression ClassificationArabian Journal for Science and Engineering10.1007/s13369-020-05217-8Online publication date: 23-Jan-2021
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Huh JHwa JSeo Y(2020)Hierarchical System Decomposition Using Genetic Algorithm for Future Sustainable ComputingSustainability10.3390/su1206217712:6(2177)Online publication date: 11-Mar-2020
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Akbari MIzadkhah H(2019)Hybrid of genetic algorithm and krill herd for software clustering problem2019 5th Conference on Knowledge Based Engineering and Innovation (KBEI)10.1109/KBEI.2019.8734939(565-570)Online publication date: Feb-2019
https://doi.org/10.1109/KBEI.2019.8734939
Paixao MHarman MZhang YYu Y(2018)An Empirical Study of Cohesion and Coupling: Balancing Optimization and DisruptionIEEE Transactions on Evolutionary Computation10.1109/TEVC.2017.269128122:3(394-414)Online publication date: Jun-2018
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Assunção WVergilio SLopez-Herrejon R(2017)Discovering Software Architectures with Search-Based Merge of UML Model VariantsMastering Scale and Complexity in Software Reuse10.1007/978-3-319-56856-0_7(95-111)Online publication date: 5-Apr-2017
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Kramer HUchoa EFampa MKöhler VVanderbeck F(2016)Column generation approaches for the software clustering problemComputational Optimization and Applications10.1007/s10589-015-9822-964:3(843-864)Online publication date: 1-Jul-2016
https://dl.acm.org/doi/10.1007/s10589-015-9822-9

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A modified genetic algorithm for software clustering problem

An efficient and stable method to cluster software modules using ant colony optimization algorithm

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