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Neural network based models for software effort estimation: a review

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Abstract

Prediction of software development effort is the key task for the effective management of any software industry. The accuracy and reliability of prediction mechanisms is also important. Neural network based models are competitive to traditional regression and statistical models for software effort estimation. This comprehensive article, covers various neural network based models for software estimation as presented by various researchers. The review of twenty-one articles covers a range of features used for effort prediction. This survey aims to support the research for effort prediction and to emphasize capabilities of neural network based model in effort prediction.

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Authors and Affiliations

  1. Department of Computer Science and Engineering, National Institute of Technology, Hamirpur, HP, India

    Vachik S. Dave & Kamlesh Dutta

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  1. Vachik S. Dave
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  2. Kamlesh Dutta
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Correspondence to Kamlesh Dutta.

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Dave, V.S., Dutta, K. Neural network based models for software effort estimation: a review. Artif Intell Rev 42, 295–307 (2014). https://doi.org/10.1007/s10462-012-9339-x

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