A fuzzy logic approach to measure complexity of agent-oriented systems

Agent-oriented software engineering (AOSE) is rapidly emerging in response to our needs in both software engineering and agent-based computing. One of the most important quality metrics of software is complexity. You can achieve more predictability in managing software projects if you know the level of complexity of your software, you can lower the risk of introducing defects into production if you plan for and manage software complexity. You can lower software complexity costs if you proactively keep your software from becoming excessively or unnecessarily complex. You can preserve the value of your software asset and prolong its useful lifetime if you keep it from becoming excessively complex. You can estimate when it is better to rewrite code than to keep maintaining it. For this reasons we proposed a fuzzy logic approach to measure complexity of Agent-Oriented systems. The result of simulation shows that the proposed system has lower error than other similar approaches

Keywords:

Agent-Oriented Software Engineering , software complexity , measurement , fuzzy logic