Neural network based model for productivity in software development
نویسنده
چکیده
This paper looks into productivity of 634 software projects completed between 2009 and 2013 within the IT department of the Dutch tax administration. A predictive neural network based model is developed in order to produce better estimates for future development efforts. Direct cost drivers and numerous organizational changes are identified in order to analyze their impact on productivity. The neural network is capable of generating better estimates than other software cost estimation methods, such as COCOMO II and QSM-SLIM. The research concludes that there are opportunities to reduce the overall costs of software development by improving planning.
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