Marya Iqbal¹, Yaser Hafeez¹, Nabil Almashfi², Amjad Alsirhani³, Faeiz Alserhani⁴, Sadia Ali¹, Mamoona Humayun^5,*, Muhammad Jamal⁶

CMC-Computers, Materials & Continua, Vol.79, No.3, pp. 5031-5049, 2024, DOI:10.32604/cmc.2024.051371 - 20 June 2024

Abstract Embracing software product lines (SPLs) is pivotal in the dynamic landscape of contemporary software development. However, the flexibility and global distribution inherent in modern systems pose significant challenges to managing SPL variability, underscoring the critical importance of robust cybersecurity measures. This paper advocates for leveraging machine learning (ML) to address variability management issues and fortify the security of SPL. In the context of the broader special issue theme on innovative cybersecurity approaches, our proposed ML-based framework offers an interdisciplinary perspective, blending insights from computing, social sciences, and business. Specifically, it employs ML for demand analysis, More >

Muhammad Fezan Afzal¹, Imran Khan¹, Javed Rashid^1,2,3, Mubbashar Saddique^4,*, Heba G. Mohamed⁵

CMC-Computers, Materials & Continua, Vol.76, No.3, pp. 3653-3670, 2023, DOI:10.32604/cmc.2023.041627 - 08 October 2023

Abstract Software Product Line (SPL) is a group of software-intensive systems that share common and variable resources for developing a particular system. The feature model is a tree-type structure used to manage SPL’s common and variable features with their different relations and problem of Crosstree Constraints (CTC). CTC problems exist in groups of common and variable features among the sub-tree of feature models more diverse in Internet of Things (IoT) devices because different Internet devices and protocols are communicated. Therefore, managing the CTC problem to achieve valid product configuration in IoT-based SPL is more complex, time-consuming,… More >

Ling Ding¹, Hongyan Wan^2,*, Luokai Hu¹, Yu Chen¹

CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 2655-2670, 2023, DOI:10.32604/cmc.2023.035542 - 31 March 2023

Abstract Product detection based on state abstraction technologies in the software product line (SPL) is more complex when compared to a single system. This variability constitutes a new complexity, and the counterexample may be valid for some products but spurious for others. In this paper, we found that spurious products are primarily due to the failure states, which correspond to the spurious counterexamples. The violated products correspond to the real counterexamples. Hence, identifying counterexamples is a critical problem in detecting violated products. In our approach, we obtain the violated products through the genuine counterexamples, which have… More >

Muhammad Abid Jamil^1,*, Deafallah Alsadie¹, Mohamed K. Nour¹, Normi Sham Awang Abu Bakar²

CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 4407-4422, 2022, DOI:10.32604/cmc.2022.029096 - 16 June 2022

Abstract To improve the maintenance and quality of software product lines, efficient configurations techniques have been proposed. Nevertheless, due to the complexity of derived and configured products in a product line, the configuration process of the software product line (SPL) becomes time-consuming and costly. Each product line consists of a various number of feature models that need to be tested. The different approaches have been presented by Search-based software engineering (SBSE) to resolve the software engineering issues into computational solutions using some metaheuristic approach. Hence, multiobjective evolutionary algorithms help to optimize the configuration process of SPL. More >