Work place: Mazandaran University of Sciences and Technology, Iran
E-mail: yavari@ustmb.ac.ir
Website:
Research Interests: Computer systems and computational processes, Neural Networks, Computer Networks, Data Mining, Data Structures and Algorithms
Biography
Ali Yavari received his Master of Science degree in Information Technology from Mazandaran University of Science and Technology (MUST) and works on Software Complexity in agent-oriented Software development. His research interests include fuzzy sets and systems, neural networks, fuzzy neural networks, clustering and classification algorithms in data mining, software risk and also complexity in aspect and agent-oriented methodologies.
By Ali Yavari Maede Golbaghi Hossein Momeni
DOI: https://doi.org/10.5815/ijieeb.2013.04.08, Pub. Date: 8 Oct. 2013
Software development always faces unexpected events such as technology changes, environmental changes, changing user needs. These changes will increase the risk in software projects. We need to risk management to deal with software risks. Risk assessment is one of the most important factors in risk and project management of software projects. In this paper, we use Wallace’s work and five factors to present an efficient method to measure software risk using fuzzy logic. Team, Planning, Complexity, Requirements and User are factors that we use in this paper. Results of experiments shows that our framework is more efficient than other frameworks and approaches for risk assessment in software projects.
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