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Semantic-based architecture smell analysis

Authors
Chondamrongkul, NachaSun, JingWarren, IanLee, Scott Uk Jin
Issue Date
Oct-2020
Publisher
Association for Computing Machinery
Keywords
Architecture Smells; Model Checking; Ontology Web Language; Smell Detection; Software Architecture
Citation
Proceedings - 2020 IEEE/ACM 8th International Conference on Formal Methods in Software Engineering, FormaliSE 2020, pp 109 - 118
Pages
10
Indexed
SCOPUS
Journal Title
Proceedings - 2020 IEEE/ACM 8th International Conference on Formal Methods in Software Engineering, FormaliSE 2020
Start Page
109
End Page
118
URI
https://scholarworks.bwise.kr/erica/handle/2021.sw.erica/1831
DOI
10.1145/3372020.3391564
ISSN
0000-0000
2575-5099
Abstract
Software smells have negative impacts on the reliability and modifiability of software systems. The smells in architecture design can be cascaded down to the implementation level and cause issues that require much effort to fix. Therefore, early detection of the architecture smells can benefit the overall quality of the software system. This paper presents an integration of methods that formally define the software architecture design towards architecture smell detection. Our approach serves as a framework that allows the architectural structures and behaviours to be formally analysed based on a coherent technique. We evaluated the accuracy and performance of our approach with the models generated from open source projects. The results show that our approach is effective and functions well. © 2020 Copyright held by the owner/author(s). Publication rights licensed to ACM.
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ERICA 소프트웨어융합대학 (ERICA 컴퓨터학부)
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