Efficient parameter estimation of software reliability growth models using harmony search

• Published in: IET software Vol. 11; no. 6; pp. 286 - 291
• Main Authors: Choudhary, Ankur, Baghel, Anurag Singh, Sangwan, Om Prakash
• Format: Journal Article
• Language: English
• Published: The Institution of Engineering and Technology 01.12.2017
• Subjects: Cuckoo search; harmony search; mean square error; mean square error methods; orthogonal array; parameter estimation; Research Article; software metrics; software reliability; software reliability growth models; statistical testing; statistical tests; Taguchi method; Taguchi methods; Theil's statistics; orthogonal array; Cuckoo search; software reliability growth models; software reliability; harmony search; mean square error; statistical tests; Theil's statistics; parameter estimation; Taguchi methods; mean square error methods; statistical testing; software metrics; Taguchi method
• DOI: 10.1049/iet-sen.2015.0171
• ISSN: 1751-8806; 1751-8814

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.