Web service design defects detection: A bi-level multi-objective approach

Context: Web services frequently evolve to integrate new features, update existing operations and fix errors to meet the new requirements of subscribers. While this evolution is critical, it may have a negative impact on the quality of services (QoS) such as reduced cohesion, increased coupling, poor response time and availability, etc. Thus, the design of services could become hard to maintain and extend in future releases. Recent studies addressed the problem of web service design antipatterns detection, also called design defects, by either manually defining detection rules, as combination of quality metrics, or generating them automatically from a set of defect examples. The manual definition of these rules is time-consuming and difficult due to the subjective nature of design issues, especially to find the right thresholds value. The efficiency of the generated rules, using automated approaches, will depend on the quality of the training set since examples of web services antipatterns are limited. Furthermore, the majority of existing studies for design defects detection for web services are limited to structural information (interface/code static metrics) and they ignore the use of quality of services (QoS) or performance metrics, such as response time and availability, for this detection process or understanding the impact of antipatterns on these QoS attributes.