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

Anupama Kaushik (), Shivi Verma (), Harsh Jot Singh () and Gitika Chhabra ()
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Anupama Kaushik: Maharaja Surajmal Institute of Technology
Shivi Verma: Maharaja Surajmal Institute of Technology
Harsh Jot Singh: Maharaja Surajmal Institute of Technology
Gitika Chhabra: Maharaja Surajmal Institute of Technology

International Journal of System Assurance Engineering and Management, 2017, vol. 8, issue 2, No 72, 1471 pages

Abstract: 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.

Keywords: Software cost optimization (SCO); Cuckoo optimization algorithm (COA); Fuzzy logic; Fuzzy inference system (FIS); CUCKOO-FIS (search for similar items in EconPapers)
Date: 2017
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Citations: View citations in EconPapers (3)

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DOI: 10.1007/s13198-017-0615-7

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