A New Metaheuristic-Based Hierarchical Clustering Algorithm for Software Modularization
Software refactoring is a software maintenance action to improve the software internal quality without changing its external behavior. During the maintenance process, structural refactoring is performed by remodularizing the source code. Software clustering is a modularization technique to remodular...
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| Format: | Article |
| Language: | English |
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Wiley
2020-01-01
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| Series: | Complexity |
| Online Access: | http://dx.doi.org/10.1155/2020/1794947 |
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| author | Masoud Aghdasifam Habib Izadkhah Ayaz Isazadeh |
| author_facet | Masoud Aghdasifam Habib Izadkhah Ayaz Isazadeh |
| author_sort | Masoud Aghdasifam |
| collection | DOAJ |
| description | Software refactoring is a software maintenance action to improve the software internal quality without changing its external behavior. During the maintenance process, structural refactoring is performed by remodularizing the source code. Software clustering is a modularization technique to remodularize artifacts of source code aiming to improve readability and reusability. Due to the NP hardness of the clustering problem, evolutionary approaches such as the genetic algorithm have been used to solve this problem. In the structural refactoring literature, there exists no search-based algorithm that employs a hierarchical approach for modularization. Utilizing global and local search strategies, in this paper, a new search-based top-down hierarchical clustering approach, named TDHC, is proposed that can be used to modularize the system. The output of the algorithm is a tree in which each node is an artifact composed of all artifacts in its subtrees and is a candidate to be a software module (i.e., cluster). This tree helps a software maintainer to have better vision on source code structure to decide appropriate composition points of artifacts aiming to create modules (i.e., files, packages, and components). Experimental results on seven folders of Mozilla Firefox with different functionalities and five other software systems show that the TDHC produces modularization closer to the human expert’s decomposition (i.e., directory structure) than the other existing algorithms. The proposed algorithm is expected to help a software maintainer for better remodularization of a source code. The source codes and dataset related to this paper can be accessed at https://github.com/SoftwareMaintenanceLab. |
| format | Article |
| id | doaj-art-77820907598540bdb19bdc1aed674669 |
| institution | Kabale University |
| issn | 1076-2787 1099-0526 |
| language | English |
| publishDate | 2020-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Complexity |
| spelling | doaj-art-77820907598540bdb19bdc1aed6746692025-02-03T01:03:51ZengWileyComplexity1076-27871099-05262020-01-01202010.1155/2020/17949471794947A New Metaheuristic-Based Hierarchical Clustering Algorithm for Software ModularizationMasoud Aghdasifam0Habib Izadkhah1Ayaz Isazadeh2Department of Computer Science, Faculty of Mathematical Sciences, University of Tabriz, Tabriz, IranDepartment of Computer Science, Faculty of Mathematical Sciences, University of Tabriz, Tabriz, IranDepartment of Computer Science, Faculty of Mathematical Sciences, University of Tabriz, Tabriz, IranSoftware refactoring is a software maintenance action to improve the software internal quality without changing its external behavior. During the maintenance process, structural refactoring is performed by remodularizing the source code. Software clustering is a modularization technique to remodularize artifacts of source code aiming to improve readability and reusability. Due to the NP hardness of the clustering problem, evolutionary approaches such as the genetic algorithm have been used to solve this problem. In the structural refactoring literature, there exists no search-based algorithm that employs a hierarchical approach for modularization. Utilizing global and local search strategies, in this paper, a new search-based top-down hierarchical clustering approach, named TDHC, is proposed that can be used to modularize the system. The output of the algorithm is a tree in which each node is an artifact composed of all artifacts in its subtrees and is a candidate to be a software module (i.e., cluster). This tree helps a software maintainer to have better vision on source code structure to decide appropriate composition points of artifacts aiming to create modules (i.e., files, packages, and components). Experimental results on seven folders of Mozilla Firefox with different functionalities and five other software systems show that the TDHC produces modularization closer to the human expert’s decomposition (i.e., directory structure) than the other existing algorithms. The proposed algorithm is expected to help a software maintainer for better remodularization of a source code. The source codes and dataset related to this paper can be accessed at https://github.com/SoftwareMaintenanceLab.http://dx.doi.org/10.1155/2020/1794947 |
| spellingShingle | Masoud Aghdasifam Habib Izadkhah Ayaz Isazadeh A New Metaheuristic-Based Hierarchical Clustering Algorithm for Software Modularization Complexity |
| title | A New Metaheuristic-Based Hierarchical Clustering Algorithm for Software Modularization |
| title_full | A New Metaheuristic-Based Hierarchical Clustering Algorithm for Software Modularization |
| title_fullStr | A New Metaheuristic-Based Hierarchical Clustering Algorithm for Software Modularization |
| title_full_unstemmed | A New Metaheuristic-Based Hierarchical Clustering Algorithm for Software Modularization |
| title_short | A New Metaheuristic-Based Hierarchical Clustering Algorithm for Software Modularization |
| title_sort | new metaheuristic based hierarchical clustering algorithm for software modularization |
| url | http://dx.doi.org/10.1155/2020/1794947 |
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