Binary Pattern for Nested Cardinality Constraints for Software Product Line of IoT-Based Feature Models

Abbas, Asad, Siddiqui, Isma Farah, Lee, Scott Uk-Jin and Bashir, Ali Kashif ORCID: https://orcid.org/0000-0001-7595-2522 (2017) Binary Pattern for Nested Cardinality Constraints for Software Product Line of IoT-Based Feature Models. IEEE Access, 5. pp. 3971-3980. ISSN 2169-3536

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Official URL: https://ieeexplore.ieee.org/document/7875079

Abstract

Software product line (SPL) is extensively used for reusability of resources in family of products. Feature modeling is an important technique used to manage common and variable features of SPL in applications, such as Internet of Things (IoT). In order to adopt SPL for application development, organizations require information, such as cost, scope, complexity, number of features, total number of products, and combination of features for each product to start the application development. Application development of IoT is varied in different contexts, such as heat sensor indoor and outdoor environment. Variability management of IoT applications enables to find the cost, scope, and complexity. All possible combinations of features make it easy to find the cost of individual application. However, exact number of all possible products and features combination for each product is more valuable information for an organization to adopt product line. In this paper, we have proposed binary pattern for nested cardinality constraints (BPNCC), which is simple and effective approach to calculate the exact number of products with complex relationships between application's feature models. Furthermore, BPNCC approach identifies the feasible features combinations of each IoT application by tracing the constraint relationship from top-to-bottom. BPNCC is an open source and tool-independent approach that does not hide the internal information of selected and non-selected IoT features. The proposed method is validated by implementing it on small and large IoT application feature models with “n” number of constraints, and it is found that the total number of products and all features combinations in each product without any constraint violation.

Item Type:	Article
Peer-reviewed:	Yes
Date Deposited:	09 May 2019 09:23
Publisher:	Institute of Electrical and Electronics Engineers (IEEE)
Additional Information:	Open Access article. Copyright 2017 IEEE. Translations and content mining are permitted for academic research only. Personal use is also permitted, but republication/redistribution requires IEEE permission. See http://www.ieee.org/publications_standards/publications/rights/index.html for more information.
Divisions:	Faculties > Science and Engineering
Subject terms:	Science & Technology, Technology, Computer Science, Information Systems, Engineering, Electrical & Electronic, Telecommunications, Computer Science, Engineering, Software product line, feature model, internet of things (IoT), cost estimation models, 08 Information and Computing Sciences, 09 Engineering, 10 Technology
URI:	https://e-space.mmu.ac.uk/id/eprint/622921
DOI:	https://doi.org/10.1109/access.2017.2680470
ISSN	2169-3536
e-ISSN	2169-3536

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