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An NHPP SRGM with Change Point and Multiple Releases

An NHPP SRGM with Change Point and Multiple Releases

Abhishek Tandon, Anu G. Aggarwal, Nidhi Nijhawan
Copyright: © 2016 |Volume: 8 |Issue: 4 |Pages: 12
ISSN: 1935-5688|EISSN: 1935-5696|EISBN13: 9781466689817|DOI: 10.4018/IJISSS.2016100105
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MLA

Tandon, Abhishek, et al. "An NHPP SRGM with Change Point and Multiple Releases." IJISSS vol.8, no.4 2016: pp.57-68. http://doi.org/10.4018/IJISSS.2016100105

APA

Tandon, A., Aggarwal, A. G., & Nijhawan, N. (2016). An NHPP SRGM with Change Point and Multiple Releases. International Journal of Information Systems in the Service Sector (IJISSS), 8(4), 57-68. http://doi.org/10.4018/IJISSS.2016100105

Chicago

Tandon, Abhishek, Anu G. Aggarwal, and Nidhi Nijhawan. "An NHPP SRGM with Change Point and Multiple Releases," International Journal of Information Systems in the Service Sector (IJISSS) 8, no.4: 57-68. http://doi.org/10.4018/IJISSS.2016100105

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Abstract

In an environment of intense competition, software upgrades have become the necessity for the survival in software industry. In this paper, the authors propose a discrete Software Reliability Growth Model (SRGM) for the software with successive releases by taking into consideration the realistic assumption that Fault Removal Rate (FRR) may not remain constant during the testing process, it changes due to severity of faults detected and due to change in strategies adapted by testing team and the time point where FRR changes is called the Change Point. Many researchers have developed SRGMs incorporating the concept of Change Point for single release software. The proposed model aims to present multi release software reliability modeling with change point. Discrete logistic distribution function has been used to model relationship between features enhancement and fault removal. It is helpul in developing a flexible SRGM, which is S-shaped in nature. In order to evaluate the proposed SRGM, parameter estimation is done using the real life data set for software with four releases and the goodness-of-fit of this model is analyzed.

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