Parallel distributed processing: explorations in the microstructure of cognition, vol. 1: foundations
Self-organizing maps
Data mining: concepts and techniques
Data mining: concepts and techniques
Neural Networks: A Comprehensive Foundation
Neural Networks: A Comprehensive Foundation
Quantitative measurement of program quality
ACM '68 Proceedings of the 1968 23rd ACM national conference
AI Tools for Software Development Effort Estimation
SEEP '96 Proceedings of the 1996 International Conference on Software Engineering: Education and Practice (SE:EP '96)
A neural net based approach to Test Oracle
ACM SIGSOFT Software Engineering Notes
IEEE Transactions on Software Engineering
Software reusability assessment using soft computing techniques
ACM SIGSOFT Software Engineering Notes
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Software Engineering measurement and analysis specially, size estimation initiatives have been in the center of attention for many firms. Function Point (FP) metric is among the most commonly used techniques to estimate the size of software system projects or software systems for measuring the functionality delivered by a system. In this paper we explore an alternative, Artificial Neural Network (ANN) approach for predicting function Point. We proposed an ANN model to explore neural network as tool for function point metric. A multilayer feed forward network is trained using backpropogation algorithm and demonstrated to be suitable. The training and validation data is randomly selected from the data repository of 365 projects [7]. The experimental results of two validation sets each of 55 projects indicate that the Mean Absolute Relative Error (MARE) was 0.198 and 0.145 of ANN model and shows that ANN model is a competitive model as Function Point Metric.