215,674 research outputs found
Modelling Open-Source Software Reliability Incorporating Swarm Intelligence-Based Techniques
In the software industry, two software engineering development best practices
coexist: open-source and closed-source software. The former has a shared code
that anyone can contribute, whereas the latter has a proprietary code that only
the owner can access. Software reliability is crucial in the industry when a
new product or update is released. Applying meta-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 is
predicted by estimating the parameters of the software reliability models. As
software reliability models are inherently nonlinear, traditional approaches
make estimating the appropriate parameters difficult and ineffective.
Consequently, software reliability models necessitate a high-quality parameter
estimation technique. These objectives dictate the exploration of potential
applications of meta-heuristic swarm intelligence optimization algorithms for
optimizing the parameter estimation of nonhomogeneous Poisson process-based
open-source software reliability modelling. The optimization algorithms are
firefly, social spider, artificial bee colony, grey wolf, particle swarm, moth
flame, and whale. The applicability and performance evaluation of the
optimization modelling approach is demonstrated through two real open-source
software reliability datasets. The results are promising.Comment: 14 pages, 11 figures, 7 table
Software reliability and dependability: a roadmap
Shifting the focus from software reliability to user-centred measures of dependability in complete software-based systems. Influencing design practice to facilitate dependability assessment. Propagating awareness of dependability issues and the use of existing, useful methods. Injecting some rigour in the use of process-related evidence for dependability assessment. Better understanding issues of diversity and variation as drivers of dependability. Bev Littlewood is founder-Director of the Centre for Software Reliability, and Professor of Software Engineering at City University, London. Prof Littlewood has worked for many years on problems associated with the modelling and evaluation of the dependability of software-based systems; he has published many papers in international journals and conference proceedings and has edited several books. Much of this work has been carried out in collaborative projects, including the successful EC-funded projects SHIP, PDCS, PDCS2, DeVa. He has been employed as a consultant t
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