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access icon free Efficient parameter estimation of software reliability growth models using harmony search

© The Institution of Engineering and Technology
Received 28/11/2015, Accepted 22/05/2017, Revised 21/02/2017, Published 01/06/2017

The primary challenge of software reliability growth model is to find the unknown model parameters that are used to validate on software failure dataset. Though, numerical estimation technique plays a vital role in parameter estimation of software reliability growth models, they are not optimal as they suffer from constraints sucha as sample size, biasing, and initialisation of parameters. In this study, a parameter estimation of software reliability growth model that utilises a variant of harmony search is proposed. Extensive experiments are conducted on seven different software datasets of varying complexity. A robust experimental setup is developed employing an orthogonal array and Taguchi method. Two-fold performance comparisons are performed. First, the authors tested their proposed approach against Cuckoo search and numerical method (least square estimation) considering mean square error and Theil's statistics as a quality measure. Second, the authors applied statistical tests are performed that demonstrate the superiority of their approach over the others. The underlying motivation to conduct this study is to motivate researchers to utilise their approach for a better estimation of model parameters.

Inspec keywords: software reliability; parameter estimation; Taguchi methods; mean square error methods; statistical testing; software metrics

Other keywords: Taguchi method; Cuckoo search; software reliability growth models; mean square error; parameter estimation; harmony search; Theil's statistics; orthogonal array; statistical tests

Subjects: Software metrics; Interpolation and function approximation (numerical analysis); Software engineering techniques; Other topics in statistics

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