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Software cost optimization integrating fuzzy system and COA-Cuckoo optimization algorithm

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Abstract

Processing the uncertainty in the software cost estimation is now highly needful considering the growing use of software cost optimization in modern organizations. In this paper, a new methodology for software cost optimization is introduced. The software cost estimation is an “approximate judgment” of the cost and effort incurred in a software project model. The proposed method (CUCKOO-FIS) integrates two optimization techniques-Cuckoo optimization, a meta-heuristic search algorithm and Fuzzy Inference System, a mathematical system based on fuzzy logic. The collaborated technique is applied to software cost estimation model for effort optimization and is successfully evaluated on the tera-PROMISE datasets. Many model based methods have been proposed earlier but this estimation using Cuckoo algorithm and Fuzzy sets which runs on non-algorithmic methods have showed results with improved accuracy in cost estimation.

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Authors and Affiliations

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

    Anupama Kaushik, Shivi Verma, Harsh Jot Singh & Gitika Chhabra

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  1. Anupama Kaushik
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  2. Shivi Verma
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  3. Harsh Jot Singh
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  4. Gitika Chhabra
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Correspondence to Anupama Kaushik.

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Kaushik, A., Verma, S., Singh, H.J. et al. Software cost optimization integrating fuzzy system and COA-Cuckoo optimization algorithm. Int J Syst Assur Eng Manag 8 (Suppl 2), 1461–1471 (2017). https://doi.org/10.1007/s13198-017-0615-7

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  • DOI: https://doi.org/10.1007/s13198-017-0615-7

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