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Khoshnevis, Sedigheh, Rahmanpour, Ehsan, Koohestani, Farnaz. (1403). CIAOERP: A Method for Change Impact Analysis and Search-Based Decision Optimization in Cloud ERP Systems Using Feature Forests. سامانه مدیریت نشریات علمی دانشگاه اصفهان, (), -. doi: 10.22108/jcs.2024.141074.1142
Sedigheh Khoshnevis; Ehsan Rahmanpour; Farnaz Koohestani. "CIAOERP: A Method for Change Impact Analysis and Search-Based Decision Optimization in Cloud ERP Systems Using Feature Forests". سامانه مدیریت نشریات علمی دانشگاه اصفهان, , , 1403, -. doi: 10.22108/jcs.2024.141074.1142
Khoshnevis, Sedigheh, Rahmanpour, Ehsan, Koohestani, Farnaz. (1403). 'CIAOERP: A Method for Change Impact Analysis and Search-Based Decision Optimization in Cloud ERP Systems Using Feature Forests', سامانه مدیریت نشریات علمی دانشگاه اصفهان, (), pp. -. doi: 10.22108/jcs.2024.141074.1142
Khoshnevis, Sedigheh, Rahmanpour, Ehsan, Koohestani, Farnaz. CIAOERP: A Method for Change Impact Analysis and Search-Based Decision Optimization in Cloud ERP Systems Using Feature Forests. سامانه مدیریت نشریات علمی دانشگاه اصفهان, 1403; (): -. doi: 10.22108/jcs.2024.141074.1142

CIAOERP: A Method for Change Impact Analysis and Search-Based Decision Optimization in Cloud ERP Systems Using Feature Forests

Journal of Computing and Security
مقالات آماده انتشار، پذیرفته شده، انتشار آنلاین از تاریخ 28 آبان 1403
نوع مقاله: Research Article
شناسه دیجیتال (DOI): 10.22108/jcs.2024.141074.1142
نویسندگان
Sedigheh Khoshnevis* 1؛ Ehsan Rahmanpour2؛ Farnaz Koohestani3
1Department of Computer Engineering, Islamic Azad University, Shahr-e-Qods Branch, Tehran, Iran
2Department of Computer Engineering, Islamic Azad University, Shahr-e-Qods Branch
3Department of Computer Engineering, Islamic Azad University, Malard Branch
چکیده
Compared with on-premise ERPs, change management is a more serious challenge in cloud ERPs, since changes in an element affect not only other elements, but also multiple instances and tenants. Therefore, to make proper decisions, we need a change impact analysis (CIA) method to analyze the way changes are propagated, the affected elements, and the costs imposed. Introducing the concept of feature forest, from multi software product line engineering, this article addresses how to analyze the impact of changes of “configuration” type in single- and multi-tenant cloud ERPs. Moreover, we propose a multi-objective non-dominated deterministic search algorithm to decide on realizing the changes aiming at minimal change costs. We validated the method by carrying out an empirical experiment following the GQM approach on three real-world cloud ERPs. The evaluation results indicate a decrease of costs about 33% by the method against the average costs of all possible decisions. Moreover, compared with participants, while showing about 67% similarity, we observed an improvement of about 48% in the costs of decisions.
کلیدواژه‌ها
Cloud ERP؛ Change Impact Analysis؛ Multi Software Product Line؛ Feature Forest؛ Search-Based Optimization
آمار
تعداد مشاهده مقاله: 8


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