Semantic-based architecture smell analysis

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2
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4

초록

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.

키워드

Architecture Smells; Model Checking; Ontology Web Language; Smell Detection; Software Architecture; Formal methods; IEEE Standards; Odors; Semantics; Software reliability; Architectural structure; Architecture designs; Modifiability; Open source projects; Overall quality; Software architecture design; Software systems; Open source software
제목
Semantic-based architecture smell analysis
저자
Chondamrongkul, Nacha; Sun, Jing; Warren, Ian; Lee, Scott Uk Jin
DOI
10.1145/3372020.3391564
발행일
2020-10
유형
Proceedings Paper
저널명
2020 IEEE/ACM 8TH INTERNATIONAL CONFERENCE ON FORMAL METHODS IN SOFTWARE ENGINEERING, FORMALISE
페이지
109 ~ 118