Citation

Sahlabadi, Mahdi and Muniyandi, Ravie Chandren and Shukur, Zarina and Islam, Md Rezanur and SaberiKamarposhti, Morteza and Yim, Kangbin (2024) LPMSAEF: Lightweight process mining-based software architecture evaluation framework for security and performance analysis. Heliyon, 10 (5). e26969. ISSN 2405-8440

Text LPMSAEF_ Lightweight process mining-based software architecture evaluation framework for security and performance analysis.pdf - Published Version Restricted to Repository staff only Download (5MB)

Abstract

The article discusses the need for a lightweight software architecture evaluation framework that can address practitioners’ concerns. Specifically, the proposed framework uses process mining and Petri nets to analyze security and performance in software development’s early and late stages. Moreover, the framework has been implemented in six case studies, and the results show that it is a feasible and effective solution that can detect security and performance issues in complex and heterogeneous architecture with less time and effort. Furthermore, the article provides a detailed explanation of the framework’s features, factors, and evaluation criteria. Additionally, this article discusses the challenges associated with traditional software architecture documentation methods using Unified Modeling Language diagrams and the limitations of code alone for creating comprehensive Software Architecture models. Various methods have been developed to extract implicit Software Architecture from code artifacts, but they tend to produce code-oriented diagrams instead of Software Architecture diagrams. Therefore, to bridge the model-code gap, the article proposes a framework that considers existing Software Architecture in the source code as architectural components and focuses on Software Architecture behaviors for analyzing performance and security. The proposed framework also suggests comparing Software Architecture extracted by different Process Mining algorithms to achieve consensus on architecture descriptions, using visualizations to understand differences and similarities. Finally, the article suggests that analyzing the previous version of a system’s Software Architecture can lead to improvements and deviations from planned Software Architecture can be detected using traceability approaches to aid software architects in detecting inconsistencies.

Item Type:	Article
Uncontrolled Keywords:	Architecture
Subjects:	N Fine Arts > NA Architecture
Divisions:	Faculty of Computing and Informatics (FCI)
Depositing User:	Ms Nurul Iqtiani Ahmad
Date Deposited:	31 May 2024 02:45
Last Modified:	31 May 2024 02:45
URII:	http://shdl.mmu.edu.my/id/eprint/12507

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