Volume 15, Number 6

Modelling Open-Source Software Reliability Incorporating Swarm Intelligence-Based Techniques

  Authors

Omar Shatnawi, Al al-Bayt University, Jordan

  Abstract

In the software industry, two software engineeringdevelopment best practices coexist: open-source and closed-source software. The former has a shared code that anyone cancontribute,whereasthelatterhasaproprietarycodethat only the ownercanaccess.Softwarereliabilityiscrucial in the industry when a new product or update is released. Applyingmeta-heuristic optimization algorithms for closed-source software reliability prediction has produced significant and accurate results. Now, open-source software dominates the landscape of cloud-based systems. Therefore, providing results on open- source software reliability - as a quality indicator - would greatly help solve the open-source software reliability growth- modelling problem. The reliability ispredictedbyestimatingthe parameters of the software reliability models. As softwarereliabilitymodelsareinherentlynonlinear,traditionalapproaches make estimating the appropriate parameters difficult and ineffective. Consequently, software reliability models necessitate a high-quality parameter estimation technique. These objectives dictatethe explorationofpotentialapplicationsofmeta-heuristicswarmintelligence optimization algorithms for optimizing the parameter estimationofnonhomogeneousPoissonprocess-basedopen-sourcesoftware reliability modelling. The optimization algorithms arefirefly, social spider, artificial bee colony, grey wolf, particle swarm, moth flame,and whale.The applicability and performanceevaluation of the optimization modelling approach is demonstrated through two real open-source software reliability datasets.Theresultsare promising.

  Keywords

Swarm Intelligence, Open Source Software, Software Reliability Engineering.