Abstract
Like any other large and complex systems, user requirements may change for Service Based Systems (SBSs), as well as their execution contexts, in the form of evolution and maintenance. Consequently, these changes may cause degradation of design, and Quality of Service (QoS), resulting to the bad practiced solutions, commonly known as Antipatterns. Therefore, detecting SOA (Service Oriented Architecture) antipatterns deserves an extra importance for assessing the design and QoS of SBSs. Also, this detection may facilitate the future evolution and maintenance. Despite of its importance, there are no methods and techniques for detecting SOA antipatterns within SBSs. The subject of my PhD thesis is to propose a novel and innovative approach, supported by a framework for specifying and detecting SOA antipatterns. My contributions are: (1) an approach for SOA antipatterns detection, (2) a framework supporting analysis and detection for SOA antipatterns in SBSs, and finally (3) a concrete empirical evidence to show the effectiveness of the proposed approach and framework.
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