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A study of software reliability on big data open source software

Author

Listed:
  • Ranjan Kumar

    (Aryabhatta College (University of Delhi))

  • Subhash Kumar

    (Acharya Narendra Dev College (University of Delhi))

  • Sanjay K. Tiwari

    (Magadh University)

Abstract

With the increasing use of Open Source Software (OSS) in high speed networking, parallel processing and distributed computing, OSS has emerged as mainstream in the last decade and is now being broadly accepted even by the traditional proprietary software development companies. The major advantages of OSS over traditional software development are less development cost, availability of source code, quality and security. Software reliability—an important attribute of software quality, is defined as the probability that a software will operate free of failures or breakdown for a specified time under specified conditions (IEEE Std. 1633-2016). Investigation of Software reliability with the help of software reliability models (SRM) undertakes the estimation and prediction of the failure phenomenon of a software. In this paper we have investigated whether Non-homogeneous Poisson process (NHPP) based software reliability models fit in the big data open source software fault/bug data. We have extracted real and latest bug/fault data of Hadoop and Spark–open source big data applications, from bug tracking/management tool Jira. For this purpose, we have also compared these models on different goodness-of-fit and prediction criteria based on collected failure data to ascertain whether a best fitted model can also be a best predictor. It is found that the best model fitting the failure data is not a best predictor model.

Suggested Citation

  • 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.
    • Handle: RePEc:spr:ijsaem:v:10:y:2019:i:2:d:10.1007_s13198-019-00777-x
    DOI: 10.1007/s13198-019-00777-x
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    References listed on IDEAS

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    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. Shigeru Yamada & Yoshinobu Tamura, 2016. "OSS Reliability Measurement and Assessment," Springer Series in Reliability Engineering, Springer, edition 1, number 978-3-319-31818-9, July.
    3. 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, July.
    4. Yoshinobu Tamura & Shigeru Yamada, 2009. "Flexible Stochastic Differential Equation Modeling For Open-Source-Software Reliability Assessment," World Scientific Book Chapters, in: Tadashi Dohi & Shunji Osaki & Katsushige Sawaki (ed.), Recent Advances In Stochastic Operations Research II, chapter 20, pages 285-300, World Scientific Publishing Co. Pte. Ltd..
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    Keywords

    Bug; Goodness of fit; NHPP; OSS;
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