Open Access
ARTICLE
Feature Model Configuration Reuse Scheme for Self-Adaptive Systems
1 Electrical and Computer Engineering Department, Altinbas University, Istanbul, 34218, Turkey
2 Faculty of Information Technology, Research Laboratory on Bio-Inspired Software Engineering, Philadelphia University, Amman, 26160, Jordan
* Corresponding Author: Sumaya Alkubaisi. Email:
(This article belongs to the Special Issue: Application of Big Data Analytics in the Management of Business)
Computers, Materials & Continua 2022, 71(1), 1249-1262. https://doi.org/10.32604/cmc.2022.019434
Received 13 April 2021; Accepted 21 May 2021; Issue published 03 November 2021
Abstract
Most large-scale systems including self-adaptive systems utilize feature models (FMs) to represent their complex architectures and benefit from the reuse of commonalities and variability information. Self-adaptive systems (SASs) are capable of reconfiguring themselves during the run time to satisfy the scenarios of the requisite contexts. However, reconfiguration of SASs corresponding to each adaptation of the system requires significant computational time and resources. The process of configuration reuse can be a better alternative to some contexts to reduce computational time, effort and error-prone. Nevertheless, systems’ complexity can be reduced while the development process of systems by reusing elements or components. FMs are considered one of the new ways of reuse process that are able to introduce new opportunities for the reuse process beyond the conventional system components. While current FM-based modelling techniques represent, manage, and reuse elementary features to model SASs concepts, modeling and reusing configurations have not yet been considered. In this context, this study presents an extension to FMs by introducing and managing configuration features and their reuse process. Evaluation results demonstrate that reusing configuration features reduces the effort and time required by a reconfiguration process during the run time to meet the required scenario according to the current context.Keywords
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