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Title

Dragonfly Estimator: A Hybrid Software Projects’ Efforts Estimation Model using Artificial Neural Network and Dragonfly Algorithm

Author

Qais M. Yousef*, Yasmeen A. Alshaer, Noor K. Alhammad

Citation

Vol. 17  No. 9  pp. 108-120

Abstract

The estimation of software development efforts has become a crucial activity in software project management. Due to this significance, a few models have been proposed so far to build a connection between the required efforts to be employed, and the software size, time schedule, budget and similar requirements. However, various holes and slips can still be noticed in software effort’s estimation processes due to the lack of enough data available in the initial stage of project’s lifecycle. In order to improve the accuracy of time estimation in the software industry, this work used NASA projects dataset to train and validate the proposed model, which is based on Feedforward Artificial Neural Network. Moreover, Dragonfly Algorithm was used to provide optimal training, which in consequence offered more enhanced and accurate software estimation model. Randomly selected project datasets were used to test the proposed model, which resulted in clear enhanced results in comparison to similar estimation models. Different performance criteria were used to validate and accept the hypothesis suggested by this paper that the proposed model could be used in predicting the efforts required for various types of software projects.

Keywords

effort estimation, software projects, software development, swarm intelligence, artificial intelligence

URL

http://paper.ijcsns.org/07_book/201709/20170916.pdf