Reliability of Software System: A Particle Swarm Approach

Abstract

Abstract

Software reliability engineering is focused on engineering techniques for developing and maintaining software systems whose reliability can be quantitatively evaluated. In order to estimate and predict the reliability of software system, failure data needs to be properly measured by various means during software development operational phases. Moreover, software reliability models are required to track underlying software failure processes for accurate reliability analysis and forecasting. Generally, software reliability is indicated by user feedback including problem reports, system outages and complaints and compliments and so on. However it is too late to get the information from user’s feedback. Although the traditional methods like MLE and LSE are capable of evaluating the reliability but normally these parameters possess non-linear relationship which becomes problematic in finding optimal parameters to tune the model for better predictions. A swarm based stochastic search techniques named particle swarm optimization has been adopted for the evaluation of growth models which presents better and optimized results; also, it helps in avoiding the problems that used to occur while estimating software reliability growth parameters using traditional methods.

Keywords: Software reliability, support vector machine software reliability growth models, maximum likelihood estimation, particle swarm intelligence, parameter estimation.

Cite this Article

Bisma Gulzar Mir, Sheikh Riyaz-ul-Haq. Reliability of Software System: A Particle Swarm Approach. Journal of Multimedia Technology & Recent Advancements. 2019; 6(1): 7–12p.