IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v7y2019i5p450-d232726.html
   My bibliography  Save this article

A Testing Coverage Model Based on NHPP Software Reliability Considering the Software Operating Environment and the Sensitivity Analysis

Author

Listed:
  • Kwang Yoon Song

    (Department of Industrial and Systems Engineering, Rutgers University, 96 Frelinghuysen Road, Piscataway, NJ 08855, USA)

  • In Hong Chang

    (Department of Computer Science and Statistics, Chosun University, 309 Pilmun-daero Dong-gu, Gwangju 61452, Korea)

  • Hoang Pham

    (Department of Industrial and Systems Engineering, Rutgers University, 96 Frelinghuysen Road, Piscataway, NJ 08855, USA)

Abstract

We have been attempting to evaluate software quality and improve its reliability. Therefore, research on a software reliability model was part of the effort. Currently, software is used in various fields and environments; hence, one must provide quantitative confidence standards when using software. Therefore, we consider the testing coverage and uncertainty or randomness of an operating environment. In this paper, we propose a new testing coverage model based on NHPP software reliability with the uncertainty of operating environments, and we provide a sensitivity analysis to study the impact of each parameter of the proposed model. We examine the goodness-of-fit of a new testing coverage model based on NHPP software reliability and other existing models based on two datasets. The comparative results for the goodness-of-fit show that the proposed model does significantly better than the existing models. In addition, the results for the sensitivity analysis show that the parameters of the proposed model affect the mean value function.

Suggested Citation

  • Kwang Yoon Song & In Hong Chang & Hoang Pham, 2019. "A Testing Coverage Model Based on NHPP Software Reliability Considering the Software Operating Environment and the Sensitivity Analysis," Mathematics, MDPI, vol. 7(5), pages 1-21, May.
    • Handle: RePEc:gam:jmathe:v:7:y:2019:i:5:p:450-:d:232726
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/7/5/450/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2227-7390/7/5/450/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Qiuying Li & Hoang Pham, 2017. "A testing-coverage software reliability model considering fault removal efficiency and error generation," PLOS ONE, Public Library of Science, vol. 12(7), pages 1-25, July.
    2. P. K. Kapur & H. Pham & A. Gupta & P. C. Jha, 2011. "Software Reliability Growth Models," Springer Series in Reliability Engineering, in: Software Reliability Assessment with OR Applications, chapter 0, pages 49-95, Springer.
    3. Pham, Hoang & Zhang, Xuemei, 2003. "NHPP software reliability and cost models with testing coverage," European Journal of Operational Research, Elsevier, vol. 145(2), pages 443-454, March.
    4. Hoang Pham, 2006. "System Software Reliability," Springer Series in Reliability Engineering, Springer, number 978-1-84628-295-9, June.
    5. Xuemei Zhang & Daniel R. Jeske & Hoang Pham, 2002. "Calibrating software reliability models when the test environment does not match the user environment," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 18(1), pages 87-99, January.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Qing Tian & Chun-Wu Yeh & Chih-Chiang Fang, 2022. "Bayesian Decision Making of an Imperfect Debugging Software Reliability Growth Model with Consideration of Debuggers’ Learning and Negligence Factors," Mathematics, MDPI, vol. 10(10), pages 1-21, May.
    2. Hoang Pham, 2019. "A New Criterion for Model Selection," Mathematics, MDPI, vol. 7(12), pages 1-12, December.
    3. Shakshi Singhal & P. K. Kapur & Vivek Kumar & Saurabh Panwar, 2024. "Stochastic debugging based reliability growth models for Open Source Software project," Annals of Operations Research, Springer, vol. 340(1), pages 531-569, September.
    4. Tahere Yaghoobi & Man-Fai Leung, 2023. "Modeling Software Reliability with Learning and Fatigue," Mathematics, MDPI, vol. 11(16), pages 1-20, August.
    5. Congcong Zhou & Zhenzhong Shen & Liqun Xu & Yiqing Sun & Wenbing Zhang & Hongwei Zhang & Jiayi Peng, 2023. "Global Sensitivity Analysis Method for Embankment Dam Slope Stability Considering Seepage–Stress Coupling under Changing Reservoir Water Levels," Mathematics, MDPI, vol. 11(13), pages 1-24, June.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Da Hye Lee & In Hong Chang & Hoang Pham, 2020. "Software Reliability Model with Dependent Failures and SPRT," Mathematics, MDPI, vol. 8(8), pages 1-14, August.
    2. Hirose, Hideo, 2012. "Estimation of the number of failures in the Weibull model using the ordinary differential equation," European Journal of Operational Research, Elsevier, vol. 223(3), pages 722-731.
    3. Wang, Jinyong & Wu, Zhibo, 2016. "Study of the nonlinear imperfect software debugging model," Reliability Engineering and System Safety, Elsevier, vol. 153(C), pages 180-192.
    4. Hoang Pham, 2019. "A New Criterion for Model Selection," Mathematics, MDPI, vol. 7(12), pages 1-12, December.
    5. Tahere Yaghoobi & Man-Fai Leung, 2023. "Modeling Software Reliability with Learning and Fatigue," Mathematics, MDPI, vol. 11(16), pages 1-20, August.
    6. Zhiguo Wang & Jinde Wang & Xue Liang, 2007. "Non-parametric Estimation for NHPP Software Reliability Models," Journal of Applied Statistics, Taylor & Francis Journals, vol. 34(1), pages 107-119.
    7. Triet Pham & Hoang Pham, 2019. "A generalized software reliability model with stochastic fault-detection rate," Annals of Operations Research, Springer, vol. 277(1), pages 83-93, June.
    8. Min Xie & Chengjie Xiong & Szu-Hui Ng, 2014. "A study of N-version programming and its impact on software availability," International Journal of Systems Science, Taylor & Francis Journals, vol. 45(10), pages 2145-2157, October.
    9. Qing Tian & Chun-Wu Yeh & Chih-Chiang Fang, 2022. "Bayesian Decision Making of an Imperfect Debugging Software Reliability Growth Model with Consideration of Debuggers’ Learning and Negligence Factors," Mathematics, MDPI, vol. 10(10), pages 1-21, May.
    10. Chih-Chiang Fang & Chun-Wu Yeh, 2016. "Effective confidence interval estimation of fault-detection process of software reliability growth models," International Journal of Systems Science, Taylor & Francis Journals, vol. 47(12), pages 2878-2892, September.
    11. Anu Aggarwal & Sudeep Kumar & Ritu Gupta, 2024. "Testing coverage based NHPP software reliability growth modeling with testing effort and change-point," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 15(11), pages 5157-5166, November.
    12. Liviu Adrian COTFAS & Andreea DIOSTEANU, 2010. "Software Reliability in Semantic Web Service Composition Applications," Informatica Economica, Academy of Economic Studies - Bucharest, Romania, vol. 14(4), pages 48-56.
    13. Hiroyuki Okamura & Tadashi Dohi, 2016. "Phase-type software reliability model: parameter estimation algorithms with grouped data," Annals of Operations Research, Springer, vol. 244(1), pages 177-208, September.
    14. Vibha Verma & Sameer Anand & P. K. Kapur & Anu G. Aggarwal, 2022. "Unified framework to assess software reliability and determine optimal release time in presence of fault reduction factor, error generation and fault removal efficiency," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 13(5), pages 2429-2441, October.
    15. Adarsh Anand & Mohini Agarwal & Gunjan Bansal & A. H. S. Garmabaki, 2016. "Studying product diffusion based on market coverage," Journal of Marketing Analytics, Palgrave Macmillan, vol. 4(4), pages 135-146, December.
    16. Shivani Kushwaha & Ajay Kumar, 2024. "Optimizing software release decisions: a TFN-based uncertainty modeling approach," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 15(8), pages 3940-3953, August.
    17. Gaver, Donald P. & Jacobs, Patricia A., 2014. "Reliability growth by failure mode removal," Reliability Engineering and System Safety, Elsevier, vol. 130(C), pages 27-32.
    18. Shakshi Singhal & P. K. Kapur & Vivek Kumar & Saurabh Panwar, 2024. "Stochastic debugging based reliability growth models for Open Source Software project," Annals of Operations Research, Springer, vol. 340(1), pages 531-569, September.
    19. Chetna Choudhary & P. K. Kapur & Sunil K. Khatri & R. Muthukumar & Avinash K. Shrivastava, 2020. "Effort based release time of software for detection and correction processes using MAUT," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 11(2), pages 367-378, July.
    20. Subhashis Chatterjee & Shobhit Nigam & Jeetendra Bahadur Singh & Lakshmi Narayan Upadhyaya, 2012. "Effect of change point and imperfect debugging in software reliability and its optimal release policy," Mathematical and Computer Modelling of Dynamical Systems, Taylor & Francis Journals, vol. 18(5), pages 539-551, March.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jmathe:v:7:y:2019:i:5:p:450-:d:232726. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.