A Study on Detection of Anti-Patterns in Object-Oriented Systems

Software quality is an important issue in the development of software systems. The extent to which the software possesses a desired set of quality attributes such as testability, performance, maintainability, and manageability indicates the success of the design and the overall quality of the software system. These attributes are adversely affected by anti-patterns. These design smells, the symptoms of code smells, are introduced during software development that constrains the evolution of system by making it difficult for engineers to bring changes. Researchers and practitioners put a great effort to detect these anti-patterns to reduce costs, effort and resources. Their detection is important because it allows refactoring or removing them from systems. Consequently, it improves software quality and usability. This paper discusses various manual, semi-automated and SVM based anti-pattern detection techniques for object-oriented systems, so that researchers can get a clear and concise view about them. The limitations and advantages (over previous approaches) of some detection techniques are also compared in this paper.