ICANNGA'09 Proceedings of the 9th international conference on Adaptive and natural computing algorithms
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Providing viable estimates, understanding project requirements and doing proper risk management on software projects require extensive application and sophisticated techniques of analysis and interpretation. There is still a lack of informative techniques and feedback mechanisms that help to assess how well and efficiently a specific development methodology is performing. Analyzing project tasks would enhance how well individual tasks are estimated, how well they are defined, and whether items are completed on-time and on-budget. In this work, we propose a temporal probabilistic model that addresses feedback control mechanisms in project planning using the Complex Adaptive Systems Software Engineering framework (CASSE). We have tested our approach in industry with a software development company in South Africa on two commercial project evaluations. Our preliminary results show that the temporal probabilistic model of the framework demonstrably enhances practitioners’ understanding in managing software projects profitably - hence increasing business sustainability and management.