Abstract
One of the most critical requirements of High Maturity practices is the development of valid and usable prediction models (Process Performance Model, PPM) for quantitatively managing the outcome of a process. Multiple Regression Analysis is a tool generally used for model building. Over the last few years, Artificial Neural Networks have received a great deal of attention as prediction and classification tools. They have been applied successfully in diverse fields as data analysis tools. Here, we explore the applicability of neural network models for bug fix effort prediction in corrective maintenance project and present our findings
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Bharathi, V., Shastry, U. (2011). Neural Network Based Effort Prediction Model for Maintenance Projects. In: O’Connor, R.V., Rout, T., McCaffery, F., Dorling, A. (eds) Software Process Improvement and Capability Determination. SPICE 2011. Communications in Computer and Information Science, vol 155. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21233-8_29
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DOI: https://doi.org/10.1007/978-3-642-21233-8_29
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