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Incorporating whale optimization algorithm with deep belief network for software development effort estimation

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Abstract

The software industry is highly competitive, and hence, it is imperative to have an accurate method to estimate the effort needed in the key phases of software development. Accurate estimates ensure efficient allocation of human and machine resources for the project. This paper proposes a technique for software development effort estimation using deep belief network (DBN). For fine-tuning of DBN, Whale Optimization Algorithm (WOA) is used which mimics the social behaviour of humpback whales. The proposed technique DBN-WOA has been experimentally evaluated on four promise datasets—COCOMO81, NASA93, MAXWELL and CHINA. The results from DBN-WOA are compared with the results from fine-tuning of DBN with backpropagation (DBN-BP) and it is observed that the proposed technique outscores DBN-BP. The proposed approach is also empirically validated through a statistical framework.

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The author(s) received no financial support for the research, authorship, and/or publication of this article.

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Authors and Affiliations

  1. Department of IT, Maharaja Surajmal Institute of Technology, New Delhi, India

    Anupama Kaushik, Niyati Singal & Malvika Prasad

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  1. Anupama Kaushik
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  2. Niyati Singal
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  3. Malvika Prasad
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Correspondence to Anupama Kaushik.

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Kaushik, A., Singal, N. & Prasad, M. Incorporating whale optimization algorithm with deep belief network for software development effort estimation. Int J Syst Assur Eng Manag 13, 1637–1651 (2022). https://doi.org/10.1007/s13198-021-01519-8

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  • DOI: https://doi.org/10.1007/s13198-021-01519-8

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