Growth model for detection and removal of faults having different severity with single change point and imperfect debugging

被引：0
作者：
Tiwari A. [1 ]
Sharma A. [1 ]
机构：
[1] Department of Computer Engineering & Applications, GLA University, Mathura, Uttar Pradesh, Mathura
来源：
International Journal of Reliability and Safety | 2024年 / 18卷 / 01期
关键词：
change point; fault detection process; mean squared error; non-homogeneous Poisson process; root mean square error; root mean square prediction error; software reliability; software reliability growth model; sum of squared error;
D O I：
10.1504/IJRS.2024.139202
中图分类号：
学科分类号：
摘要：
Throughout the last decades, researchers have modelled a variety of software reliability growth models for estimating measures of reliability. In the present paper, we have classified faults into four divergent types as per their easiness and hardness in detection and removal. Also, variations in fault detection and correction rates can be because of the testing strategy, changing testing environment, motivation, proficiency and organisation of the debugging and testing teams, etc. In the present paper, a change point has been applied to four types of faults along with imperfect debugging during the correction of faults. This paper comprises two proposed software reliability growth models, which are compared on the basis of rate of detection as well as correction. All the model parameters are evaluated by the method of least squares. These models are assessed using various comparison measures like SSE, MSE, RMSE, Bias, variance and RMSPE. Copyright © 2024 Inderscience Enterprises Ltd.
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页码：86 / 101
页数：15
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