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Swarm Intelligence Algorithm: Developing a Social Spider to Enhance the Efficacious Selectivity of Software Reliability Growth Models

Gatik Gola

Student, King’s College, Taunton, UK

82-100

Vol: 8, Issue: 2, 2018

Receiving Date: 2018-03-02 Acceptance Date:

2018-05-06

Publication Date:

2018-05-25

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Abstract

Software Reliability is considered to be an essential part of software systems; it involves measuring the system’s probability of having failures; therefore, it is strongly related to Software Quality. Software Dependability Growing Models indicate the number of possible failures after the completion of the software; it is also an indicator of the software readiness to be delivered. I, hereby, present a study of selecting the best Software Reliability Growth Model according to the dataset at hand. Several Comparison Criteria are used to yield a ranking methodology to be used in pointing out best models. The Social Spider Algorithm (SSA), one of the newly introduced Swarm Intelligent Algorithms, is used for estimating the parameters of the SRGMs for two datasets. Results indicate that the use of SSA was efficient in assisting the process of criteria weighting to find the optimal model and the best overall ranking of employed models.

Keywords: Software Reliability; SRGMs; Models Ranking; Weighted Criteria; Social Spider Algorithm.

References

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