An Analysis of the New Reliability Model Based on Bathtub-Shaped Failure Rate Distribution with Application to Failure Data

Author:

Sindhu Tabassum Naz1,Anwar Sadia2ORCID,Hassan Marwa K. H.3,Lone Showkat Ahmad4ORCID,Abushal Tahani A.5ORCID,Shafiq Anum67ORCID

Affiliation:

1. Department of Statistics, Quaid-i-Azam University, Islamabad 45320, Pakistan

2. Department of Mathematics, College of Arts and Sciences, Wadi Ad Dawasir, Prince Sattam Bin Abdul Aziz University, Al-Kharj 11991, Saudi Arabia

3. Department of Mathematics, Faculty of Education, Ain Shams University, Cairo 11566, Egypt

4. Department of Basic Sciences, College of Science and Theoretical Studies, Saudi Electronic University, Riyadh 11673, Saudi Arabia

5. Department of Mathematical Science, Faculty of Applied Science, Umm Al-Qura University, Mecca 24382, Saudi Arabia

6. School of Mathematics and Statistics, Nanjing University of Information Science and Technology, Nanjing 210044, China

7. Jiangsu International Joint Laboratory on System Modeling and Data Analysis, Nanjing University of Information Science and Technology, Nanjing 210044, China

Abstract

The reliability of software has a tremendous influence on the reliability of systems. Software dependability models are frequently utilized to statistically analyze the reliability of software. Numerous reliability models are based on the nonhomogeneous Poisson method (NHPP). In this respect, in the current study, a novel NHPP model established on the basis of the new power function distribution is suggested. The mathematical formulas for its reliability measurements were found and are visually illustrated. The parameters of the suggested model are assessed utilizing the weighted nonlinear least-squares, maximum-likelihood, and nonlinear least-squares estimation techniques. The model is subsequently verified using a variety of reliability datasets. Four separate criteria were used to assess and compare the estimating techniques. Additionally, the effectiveness of the novel model is assessed and evaluated with two foundation models both objectively and subjectively. The implementation results reveal that our novel model performed well in the failure data that we examined.

Funder

Deanship of Scientific Research at Umm Al-Qura University

Publisher

MDPI AG

Subject

General Mathematics,Engineering (miscellaneous),Computer Science (miscellaneous)

Reference46 articles.

1. Gokhale, S.S., Lyu, M.R., and Trivedi, K.S. (1998, January 4–7). Software reliability analysis incorporating fault detection and debugging activities. Proceedings of the Ninth International Symposium on Software Reliability Engineering (Cat. No. 98TB100257), IEEE, Paddeborn, Germany.

2. Xie, M. (1991). Software Reliability Modelling, World Scientific.

3. Some graphical aids for deciding when to stop testing software;Dalal;IEEE J. Sel. Areas Commun.,1990

4. Software-reliability growth model: Primary-failures generate secondary-faults under imperfect debugging;Zeephongsekul;IEEE Trans. Reliab.,1994

5. Jones, W.D. (1991, January 17–18). Reliability models for very large software systems in industry. Proceedings of the 1991 International Symposium on Software Reliability Engineering, IEEE Computer Society, Austin, TX, USA.

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