Modeling Organizational Structures and Agent Knowledge for Mulan Applications

Cabac, Lawrence; Mosteller, David; Wester-Ebbinghaus, Matthias

doi:10.1007/978-3-662-45730-6_4

Cited by 2 publications

(1 citation statement)

References 17 publications

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“…It has the excellent capability of making complex products, apart from what kind of platform or technology is used in these products. However, in comparison, the presentation is still a problem in both styles [ 44 , 45 , 46 , 47 ].…”

Section: Software Architecture Designmentioning

confidence: 99%

Lightweight Software Architecture Evaluation for Industry: A Comprehensive Review

Sahlabadi

Muniyandi

Shukur

et al. 2022

Sensors

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Processes for evaluating software architecture (SA) help to investigate problems and potential risks in SA. It is derived from many studies that proposed a plethora of systematic SA evaluation methods, while industrial practitioners currently refrain from applying them since they are heavyweight. Nowadays, heterogeneous software architectures are organized based on the new infrastructure. Hardware and associated software allow different systems, such as embedded, sensor-based, modern AI, and cloud-based systems, to cooperate efficiently. It brings more complexities to SA evaluation. Alternatively, lightweight architectural evaluation methods have been proposed to satisfy the practitioner’s concerns, but practitioners still do not adopt these methods. This study employs a systematic literature review with a text analysis of SA’s definitions to propose a comparison framework for SA. It identifies lightweight features and factors to improve the architectural evaluation methods among industrial practitioners. The features are determined based on the practitioner’s concerns by analyzing the architecture’s definitions from stakeholders and reviewing architectural evaluation methods. The lightweight factors are acquired by studying the five most commonly used lightweight methods and the Architecture-based Tradeoff Analysis Method (ATAM), the most well-known heavyweight method. Subsequently, the research addresses these features and factors.

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