Paper Details: Downloads: 578
Serial Number: P1120729003
Title: Parameter Estimation of Software Reliability Growth Models by Particle Swarm Optimization
Authors: Alaa Sheta
Abstract: Building software reliability growth models (SRGM) for predicting software reliability represents a challenge for software testing engineers. Being able to predict the number of faults (failure) in the software during development and testing processes helps significantly in specifying/computing the software release day and in managing project resources (i.e people and money). In this paper, we explore the use of Particle Swarm Optimization (PSO) algorithm to estimate SRGM parameters. The proposed method shows significant advantages in handling variety of modeling problems such as the exponential model (EXPM), power model (POWM) and Delayed S-Shaped model (DSSM). PSO algorithm will be used to estimate the parameters of the well known SRGM. Detailed results and analysis are provided showing the potential advantages of using PSO in solving this problem.
Keywords: Particle Swarm Optimization, Software Reliability Growth Modeling, Software Testing
Journal/Conference: International Journal of Artificial Intelligence and Machine Learning
Volume: 7
Issue: 1
Submission Date: 7/1/2007 12:00:00 AM
Review Date: 8/1/2007 12:00:00 AM
Publishing Date: 9/1/2007 12:00:00 AM
Article Downloads: 578
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