IDEAS home Printed from https://ideas.repec.org/a/sae/risrel/v230y2016i6p579-597.html
   My bibliography  Save this article

Change point–based software reliability model under imperfect debugging with revised concept of fault dependency

Author

Listed:
  • Subhashis Chatterjee
  • Ankur Shukla

Abstract

A detailed study about the characteristics of different types of faults is necessary to enhance the accuracy of software reliability estimation. Over the last three decades, some software reliability growth models have been proposed considering the possibility of existence of two types of faults in a software: (1) independent and (2) dependent faults. In these software reliability growth models, it is considered that the removal of a leading fault or independent fault causes detection of corresponding dependent faults. In practical, it is noticed that some dependent faults are possible in a software which are removed during the removal of other faults. Moreover, dependent faults may have different characteristics, which cannot be ignored. Considering these facts, a detailed study about the different characteristics of both dependent and independent faults has been performed, and based on this study, dependent faults have been categorized into different categories. Furthermore, a new software reliability growth model has been proposed with revised concept of fault dependency under imperfect debugging by introducing the fault removal proportionality. In addition, the effect of change point on model’s parameters due to different environmental factors has been considered. The fault reduction factor is considered as a proportionality function. Experimental results establish the fact that the performance of the proposed model is better with respect to estimated and predicted cumulative number of faults on some real software failure datasets.

Suggested Citation

  • 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.
    • Handle: RePEc:sae:risrel:v:230:y:2016:i:6:p:579-597
    DOI: 10.1177/1748006X16673767
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/1748006X16673767
    Download Restriction: no
    File URL: https://libkey.io/10.1177/1748006X16673767?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
    ---><---

    References listed on IDEAS

    as
    1. 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.
    2. 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.
    3. Killick, Rebecca & Eckley, Idris A., 2014. "changepoint: An R Package for Changepoint Analysis," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 58(i03).
    4. 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, March.
    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. Subhashis Chatterjee & Ankur Shukla & Hoang Pham, 2019. "Modeling and analysis of software fault detectability and removability with time variant fault exposure ratio, fault removal efficiency, and change point," Journal of Risk and Reliability, , vol. 233(2), pages 246-256, April.
    2. Subhashis Chatterjee & Ankur Shukla, 2017. "An Ideal Software Release Policy for an Improved Software Reliability Growth Model Incorporating Imperfect Debugging with Fault Removal Efficiency and Change Point," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 34(03), pages 1-21, June.
    3. Subhashis Chatterjee & Deepjyoti Saha & Akhilesh Sharma & Yogesh Verma, 2022. "Reliability and optimal release time analysis for multi up-gradation software with imperfect debugging and varied testing coverage under the effect of random field environments," Annals of Operations Research, Springer, vol. 312(1), pages 65-85, May.
    4. Petter Arnesen & Odd A. Hjelkrem, 2018. "An Estimator for Traffic Breakdown Probability Based on Classification of Transitional Breakdown Events," Transportation Science, INFORMS, vol. 52(3), pages 593-602, June.
    5. Malte Willmes & Katherine M Ransom & Levi S Lewis & Christian T Denney & Justin J G Glessner & James A Hobbs, 2018. "IsoFishR: An application for reproducible data reduction and analysis of strontium isotope ratios (87Sr/86Sr) obtained via laser-ablation MC-ICP-MS," PLOS ONE, Public Library of Science, vol. 13(9), pages 1-15, September.
    6. 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.
    7. Salvatore Fasola & Vito M. R. Muggeo & Helmut Küchenhoff, 2018. "A heuristic, iterative algorithm for change-point detection in abrupt change models," Computational Statistics, Springer, vol. 33(2), pages 997-1015, June.
    8. 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.
    9. Hui Zhang & Minna Väliranta & Graeme T. Swindles & Marco A. Aquino-López & Donal Mullan & Ning Tan & Matthew Amesbury & Kirill V. Babeshko & Kunshan Bao & Anatoly Bobrov & Viktor Chernyshov & Marissa , 2022. "Recent climate change has driven divergent hydrological shifts in high-latitude peatlands," Nature Communications, Nature, vol. 13(1), pages 1-7, December.
    10. 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.
    11. Dehler-Holland, Joris & Okoh, Marvin & Keles, Dogan, 2022. "Assessing technology legitimacy with topic models and sentiment analysis – The case of wind power in Germany," Technological Forecasting and Social Change, Elsevier, vol. 175(C).
    12. Manfren, Massimiliano & Nastasi, Benedetto, 2023. "Interpretable data-driven building load profiles modelling for Measurement and Verification 2.0," Energy, Elsevier, vol. 283(C).
    13. Li, Boyan & Diao, Xundi, 2023. "Structural break in different stock index markets in China," The North American Journal of Economics and Finance, Elsevier, vol. 65(C).
    14. 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.
    15. Ibrar ul Hassan Akhtar, 2023. "Exploring Covid-19 Pandemic Initial 2020 Curve Based On Statistical Evaluation," Acta Scientifica Malaysia (ASM), Zibeline International Publishing, vol. 7(1), pages 08-16, February.
    16. 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.
    17. Jaller, Miguel & Pineda, Leticia, 2017. "Warehousing and Distribution Center Facilities in Southern California: The Use of the Commodity Flow Survey Data to Identify Logistics Sprawl and Freight Generation Patterns," Institute of Transportation Studies, Working Paper Series qt5dz0j1gg, Institute of Transportation Studies, UC Davis.
    18. 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.
    19. Sevvandi Kandanaarachchi & Rob J Hyndman & Kate Smith-Miles, 2020. "Early classification of spatio-temporal events using partial information," PLOS ONE, Public Library of Science, vol. 15(8), pages 1-39, August.
    20. 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.

    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:sae:risrel:v:230:y:2016:i:6:p:579-597. 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: SAGE Publications (email available below). General contact details of provider: .

    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.