An Efficient Method for Automatic Antipatterns Detection of REST Web Services


  • Sobhan Mohammadnia Department of Computer Engineering and Information Technology, Shiraz University of Technology, Shiraz, Iran
  • Rasool Esmaeilyfard Department of Computer Engineering and Information Technology, Shiraz University of Technology, Shiraz, Iran
  • Reza Akbari Department of Computer Engineering and Information Technology, Shiraz University of Technology, Shiraz, Iran



REST, Web Services, Service-Oriented Architecture, Quality of Service(QoS), Anti-patterns Detection


REST Web Services is a lightweight, maintainable, and scalable service accelerating client application development. The antipatterns of these services are inadequate and counter-productive design solutions. They have caused many qualitative problems in the maintenance and evolution of REST web services. This paper proposes an automated approach toward antipattern detection of the REST web services using Genetic Programming (GP). Three sets of generic, REST-specific and code-level metrics are considered. Twelve types of antipatterns are examined. The results are compared with the manual rule-based approach. The statistical analysis indicates that the proposed method has an average precision and recall scores of 98% (95% CI, 92.8% to 100%) and 82% (95% CI, 79.3% to 84.7%) and effectively detects REST antipatterns.


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Author Biographies

Sobhan Mohammadnia, Department of Computer Engineering and Information Technology, Shiraz University of Technology, Shiraz, Iran

Sobhan Mohammadnia received the MSc degree from the Shiraz University of Technology, Iran, in 2019 under the supervision of Dr. Rasool Esmaeilyfard and Dr. Reza Akbari. He is currently a system analyst. His main research interests include analyzing service-oriented and process-oriented systems, information systems, and business process management., in particular, he is interested in detecting service and process antipatterns in systems and evaluating the QoS of APIs.

Rasool Esmaeilyfard, Department of Computer Engineering and Information Technology, Shiraz University of Technology, Shiraz, Iran

Rasool Esmaeilyfard received his Ph.D. from the Isfahan University of Technology, Isfahan, Iran in 2017. Since 2018, he has been with the Faculty of the Department of Computer Engineering and Information Technology at the Shiraz University of Technology where he currently holds an assistant professor position. He is also a consultant, specializing in software architecture and distributed systems in the last ten years. His general research interests are in the areas of software architecture and crowd management.

Reza Akbari, Department of Computer Engineering and Information Technology, Shiraz University of Technology, Shiraz, Iran

Reza Akbari has a PhD in software engineering from Shiraz University. Currently, he is an associate professor at department of Computer Engineering and Information Technology of Shiraz University of Technology. His special fields of interest include software engineering, machine and deep learning, and optimization algorithms.


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