An ecological space based hybrid swarm-evolutionary algorithm for software reliability model parameter estimation

Sangeeta (), Kapil Sharma () and Manju Bala ()
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Sangeeta: Delhi Technological University
Kapil Sharma: Delhi Technological University
Manju Bala: Delhi University

International Journal of System Assurance Engineering and Management, 2020, vol. 11, issue 1, No 7, 77-92

Abstract: Abstract Reliability analysis of the software has attracted a lot of attention of the software developers and researchers due to rapid growing need of software in routine life. The software reliability prediction by mathematical models is entirely centered on the estimation of parameter values, and the parameter estimation of the models poses a non-differential, nonlinear, and multimodal problem. A new algorithm based on the concept of ecological space, method of differential evolution (DE) and intelligent behavior of artificial bee colony (ABC) for optimizing the parameter values has been proposed in this paper. The exploration capability in ABC algorithm has been improved by introducing the concept of ecological space. Ecological space is one of the important factors for evolution and reflects the expansion of individual bee in search space. DE technique provides the diversity of bee’s population and faster convergence. The proposed algorithm has been tested with four standard failure datasets. Proficiency of proposed algorithm is also compared with other meta-heuristic algorithms namely ABC, genetic algorithm and particle swarm optimization. Further validation of proposed algorithm is done through comparing its efficiency with hybrid partilce swarm optimization and gravitational search Algorithm. Simulation results verify that proposed hybrid algorithm is very much effective in field of software reliability estimation and would be a competitive one among meta-heuristic optimization algorithms.

Keywords: Artificial bee colony; Differential evolution; Ecological space; Genetic algorithm; Particle swarm optimization; Software reliability models (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (1)

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DOI: 10.1007/s13198-019-00926-2

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