APPLICATION OF ARTIFICIAL NEURAL NETWORKS IN PREDICTION OF SOFTWARE DEVELOPMENT EFFORT - Zainab Rustum Mohsin (Turkish Journal of Computer and Mathematics Education (TURCOMAT), 2021)
Over the past two decades, there has been a great enhance in researches dealing with the software development effort estimation utilizing machine learning (ML) approaches with the objective of improving the accuracy of the estimates. Among these ML methods, artificial neural network approaches have gained significant scholarly attention thanks to their capability to learn and model non-linear and complex functions. In this paper, artificial neural network technique was considered for modelling software development effort estimation. Datasets considered for estimation were COCOMO. Evaluation measures used were MMRE and correlation R. After building and testing the ANN model, and based on the comparison between the test results of the ANN model and the SLIM, Function Points, and COCOMO-basic models it could be concluded that the ANN was a suitable model in the estimation of the effort. ANN is recommended to be used as a predictive model for software development effort estimation.