IDEAS home Printed from https://ideas.repec.org/a/spr/ijsaem/v13y2022i3d10.1007_s13198-021-01449-5.html
   My bibliography  Save this article

A generalized prediction model for improving software reliability using time-series modelling

Author

Listed:
  • Kamlesh Kumar Raghuvanshi

    (University of Delhi)

  • Arun Agarwal

    (University of Delhi)

  • Khushboo Jain

    (DIT University)

  • V. B. Singh

    (JNU)

Abstract

The primary goal of any prediction model is an accurate estimation. Software reliability is one of the software organization's major research priorities. One of the quantitative indicators of software quality is software reliability. The Software Reliability Model is used to assess the reliability at various stages of testing. The purpose of this work is to investigate the software's dependability using time-series modeling, which is the most efficient tool for evaluating its predictive power. A fault prediction model based on categorizing faults for measuring software reliability known as Seasonal-ARIMA (S-ARIMA) is proposed in this work. The significant attribute for complex software applications is to ensure software reliability and fault tolerance. However, these attributes would inculcate additional overheads such as added costs, implementation delay, and the representation of software solution providers. Therefore, the corporation needs to ensure the reliability of the software before delivering it to the clients. Finding the mistake with a decent degree of precision at the right time aims to limit the consequences. We have analyzed and evaluated three real-time data sets to measure software reliability by the proposed prediction model for software reliability. Based on the results of these datasets, the proposed S-ARIMA model has achieved high reliability and improved accuracy when compared with the ARIMA model in terms of different parameters like mean square error ( $$MSE$$ MSE ), Relative Prediction Accuracy Improvement $$\left( { RPAI_{MSE} } \right)$$ R P A I MSE , and Akanke's Information Criteria ( $$AIC$$ AIC ).

Suggested Citation

  • Kamlesh Kumar Raghuvanshi & Arun Agarwal & Khushboo Jain & V. B. Singh, 2022. "A generalized prediction model for improving software reliability using time-series modelling," 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(3), pages 1309-1320, June.
    • Handle: RePEc:spr:ijsaem:v:13:y:2022:i:3:d:10.1007_s13198-021-01449-5
    DOI: 10.1007/s13198-021-01449-5
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s13198-021-01449-5
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s13198-021-01449-5?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. P.K. Kapur & Hoang Pham & A. Gupta & P.C. Jha, 2011. "Software Reliability Assessment with OR Applications," Springer Series in Reliability Engineering, Springer, number 978-0-85729-204-9, February.
    2. Jeske D. R. & Pham H., 2001. "On the Maximum Likelihood Estimates for the Goel-Okumoto Software Reliability Model," The American Statistician, American Statistical Association, vol. 55, pages 219-222, August.
    Full references (including those not matched with items on IDEAS)

    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. Yoshinobu Tamura & Shoichiro Miyamoto & Lei Zhou & Adarsh Anand & P. K. Kapur & Shigeru Yamada, 2024. "OSS reliability assessment method based on deep learning and independent Wiener data preprocessing," 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(6), pages 2668-2676, June.
    2. Viral Gupta & P. K. Kapur & Deepak Kumar, 2019. "Prioritizing and Optimizing Disaster Recovery Solution using Analytic Network Process and Multi Attribute Utility Theory," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 18(01), pages 171-207, January.
    3. Snigdha Malhotra & Vernika Agarwal & P. K. Kapur, 2022. "Hierarchical framework for analysing the challenges of implementing industrial Internet of Things in manufacturing industries using ISM 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. 13(5), pages 2356-2370, October.
    4. 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.
    5. 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.
    6. Yeh, Wei-Chang, 2017. "Evaluation of the one-to-all-target-subsets reliability of a novel deterioration-effect acyclic multi-state information network," Reliability Engineering and System Safety, Elsevier, vol. 166(C), pages 132-137.
    7. Subhashis Chatterjee & Ankur Shukla, 2016. "Change point–based software reliability model under imperfect debugging with revised concept of fault dependency," Journal of Risk and Reliability, , vol. 230(6), pages 579-597, December.
    8. 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.
    9. Avinash K. Shrivastava & Vivek Kumar & P. K. Kapur & Ompal Singh, 2020. "Software release and testing stop time decision with 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. 11(2), pages 196-207, July.
    10. Avinash K. Shrivastava & Armaan Singh Ahluwalia & P. K. Kapur, 0. "On interdisciplinarity between product adoption and vulnerability discovery modeling," 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. 0, pages 1-12.
    11. Avinash K. Shrivastava & Armaan Singh Ahluwalia & P. K. Kapur, 2021. "On interdisciplinarity between product adoption and vulnerability discovery modeling," 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. 12(1), pages 176-187, February.
    12. Yoshinobu Tamura & Shigeru Yamada, 2022. "Prototype of 3D Reliability Assessment Tool Based on Deep Learning for Edge OSS Computing," Mathematics, MDPI, vol. 10(9), pages 1-20, May.
    13. Vikas Dhaka & Nidhi Nijhawan, 2024. "Effect of change in environment on reliability growth modeling integrating fault reduction factor and change point: a general approach," Annals of Operations Research, Springer, vol. 340(1), pages 181-215, September.
    14. Ankur Choudhary & Anurag Singh Baghel & Om Prakash Sangwan, 2017. "An efficient parameter estimation of software reliability growth models using gravitational search algorithm," 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. 8(1), pages 79-88, March.
    15. Yoshinobu Tamura & Shigeru Yamada, 2022. "Maintenance effort management based on double jump diffusion model for OSS project," Annals of Operations Research, Springer, vol. 312(1), pages 411-426, May.
    16. Ranjan Kumar & Subhash Kumar & Sanjay K. Tiwari, 2019. "A study of software reliability on big data open source software," 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. 10(2), pages 242-250, April.
    17. Misbah Anjum & Vernika Agarwal & P. K. Kapur & Sunil Kumar Khatri, 2020. "Two-phase methodology for prioritization and utility assessment of software vulnerabilities," 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 289-300, July.
    18. Anshul Tickoo & P. K. Kapur & A. K. Shrivastava & Sunil K. Khatri, 2016. "Testing effort based modeling to determine optimal release and patching time of software," 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. 7(4), pages 427-434, December.
    19. Avinash K. Shrivastava & Vivek Kumar & P. K. Kapur & Ompal Singh, 0. "Software release and testing stop time decision with 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. 0, pages 1-12.
    20. Yogita Kansal & Gurinder Singh & Uday Kumar & P. K. Kapur, 2016. "Optimal release and patching time of software with warranty," 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. 7(4), pages 462-468, December.

    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:spr:ijsaem:v:13:y:2022:i:3:d:10.1007_s13198-021-01449-5. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.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.