Generating the structural graph-based model from a program source-code using chaotic forrest optimization algorithm

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dc.authoridArasteh, Bahman/0000-0001-5202-6315
dc.authoridGharehchopogh, Farhad Soleimanian/0000-0003-1588-1659
dc.authoridGhanbarzadeh, Reza/0000-0001-9073-1576
dc.authorwosidArasteh, Bahman/AAN-9555-2021
dc.authorwosidGharehchopogh, Farhad Soleimanian/AAX-9598-2020
dc.authorwosidHosseinAlipour, ali/AAN-3218-2021
dc.contributor.authorArasteh, Bahman
dc.contributor.authorGhanbarzadeh, Reza
dc.contributor.authorGharehchopogh, Farhad Soleimanian
dc.contributor.authorHosseinalipour, Ali
dc.date.accessioned2024-05-19T14:41:37Z
dc.date.available2024-05-19T14:41:37Z
dc.date.issued2023
dc.departmentİstinye Üniversitesien_US
dc.description.abstractOne of the most important and costly stages in software development is maintenance. Understanding the structure of software will make it easier to maintain it more efficiently. Clustering software modules is thought to be an effective reverse engineering technique for deriving structural models of software from source code. In software module clustering, the most essential objectives are to minimize connections between produced clusters, maximize internal connections within created clusters, and maximize clustering quality. Finding the appropriate software system clustering model is considered an NP-complete task. The previously proposed approaches' key limitations are their low success rate, low stability, and poor modularization quality. In this paper, for optimal clustering of software modules, Chaotic based heuristic method using a forest optimization algorithm is proposed. The impact of chaos theory on the performance of the other SFLA-GA and PSO-GA has also been investigated. The results show that using the logistic chaos approach improves the performance of these methods in the software-module clustering problem. The performance of chaotic based FOA, SFLA-GA and PSO-GA is superior to the other heuristic methods in terms of modularization quality and stability of the results.en_US
dc.identifier.doi10.1111/exsy.13228
dc.identifier.issn0266-4720
dc.identifier.issn1468-0394
dc.identifier.issue6en_US
dc.identifier.scopus2-s2.0-85147125383en_US
dc.identifier.scopusqualityQ2en_US
dc.identifier.urihttps://doi.org10.1111/exsy.13228
dc.identifier.urihttps://hdl.handle.net/20.500.12713/5135
dc.identifier.volume40en_US
dc.identifier.wosWOS:000928523200001en_US
dc.identifier.wosqualityN/Aen_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherWileyen_US
dc.relation.ispartofExpert Systemsen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.snmz20240519_kaen_US
dc.subjectForest Optimization Algorithmen_US
dc.subjectModularization Qualityen_US
dc.subjectModule Dependency Graphen_US
dc.subjectSoftware Modules Clusteringen_US
dc.titleGenerating the structural graph-based model from a program source-code using chaotic forrest optimization algorithmen_US
dc.typeArticleen_US

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