Skip to main content

Advertisement

Log in

A study of software reliability on big data open source software

  • Original Article
  • Published:
International Journal of System Assurance Engineering and Management Aims and scope Submit manuscript

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.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5

Similar content being viewed by others

References

  • Apache Website (2018). https://issues.apache.org/jira/secure/Dashboard.jspa. Accessed 26 March 2018

  • Goel AL, Okumoto K (1979) Time dependent error detection rate model for software reliability and other performance measures. IEEE Trans Reliab 28:206211

    MATH  Google Scholar 

  • Kapur PK, Garg RB (1992) A software reliability growth model for error removal phenomenon. Softw Eng J 7:291–294

    Article  Google Scholar 

  • Kapur PK, Garg RB, Kumar S (1999) Contributions to hardware and software reliability. World Scientific, Singapore

    Book  MATH  Google Scholar 

  • Kapur PK, Pham H, Gupta A, Jha PC (2011) Software reliability assessment with OR applications. Springer, London

    Book  MATH  Google Scholar 

  • Lai R, Garg M (2012) A detailed study of NHPP software reliability models. J Softw 7(6):1296–1306

    Article  Google Scholar 

  • Li Q, Pham H (2017) A testing-coverage software reliability model considering fault removal efficiency and error generation. PLoS ONE 12(7):e0181524. https://doi.org/10.1371/journal.pone.0181524

    Article  Google Scholar 

  • Li X et al (2011) Reliability analysis and optimal release-updating for open source software. Inf Softw Technol 53:929936

    Article  Google Scholar 

  • Lyu MR (1996) Handbook of sofware reliability engineering. IEEE Computer Society Press, Los Alamitos

    Google Scholar 

  • Ohba M, Osaki S (1984) Inflexion S-shaped software reliability growth models, stochastic models in reliability theory. Springer, p 144162

  • Pham H, Nordmann L, Zhang X (1999) A general imperfect software debugging model with S-shaped fault detection rate. IEEE Trans Reliab 48:169175

    Google Scholar 

  • Pillai K, Nair VSS (1997) A model for software development effort and cost estimation. IEEE Transactions on Software Engineering 23(8):485–497

    Article  Google Scholar 

  • Rahmani C et al (2010) A comparative analysis of open source software reliability. J Softw 5(12):1384–1394

    Article  Google Scholar 

  • Rahmani C et al (2010) Exploratory failure analysis of open source software. In: 2nd International conference on software technology and engineering (ICSTE). IEEE Explore, vol 2, pp 51–56

  • Raymond ES (1999) The cathedral and the bazaar: musings on open source by an acci-dental revolutionary. OReilly & Associates, Sebastopol

    Book  Google Scholar 

  • Rossi B et al (2010) Modelling failures occurrences of open source software with reliability growth. J Open Source Softw New Horizons 268–280

  • Singh VB, Sujata K, Kapur PK (2010) A reliability growth model for object oriented software developed under concurrent distributed development environment. In: Proceedings of 2nd international conference on reliability safety and hazard, IEEE, pp 479–484

  • Singh VB, Kapur PK, Tandon A (2010) Measuring reliability growth of open source software using stochastic differential equations. In: Proceedings of second world congress on software engineering (WCSE) at Huwan, China, IEEE Xplore

  • Singh VB, Kapur PK, R Kumar (2010) Developing S-shaped software reliability growth model for open source software. In: Proceedings of IASTED international conference on software engineering at Austria, ACTA Press

  • SinghVB, Singh OP, Kumar R, Kapur PK (2010) A generalized reliability growth model for open source software. In: Proceedings of 2nd international conference on reliability safety and hazard, IEEE, pp 523–528

  • Stallman R (1998) The GNU project. http://www.gnu.org/gnu/thegnuproject.html

  • IEEE Std 1633-2008 (2008) IEEE recommended practice in software reliability

  • Syed-Mohamad SM et al (2008) Reliability growth of open source software using defect analysis. In: International conference on computer science and software engineering

  • Tamura Y, Yamada S (2009) Optimization analysis for reliability assessment based on stochastic differential equation modeling for open source software. Int J Syst Sci 40(4):429–438

    Article  MATH  Google Scholar 

  • Tamura Y, Yamada S (2010) Performance evaluation of reliability assessment method based on stochastic differential equation model for large-scale open source solution. Int J Syst Assur Eng Manag 1(4):324–329

    Article  Google Scholar 

  • van de Joode RW, de Bruijne M (2006) The organization of open source communities: towards a framework to analyze the relationship between openness and reliability. In: Proceedings of 39th Hawaii international conference on system sciences, pp 1–6

  • Ven K, Verelst J, Mannaert H (1998) Should you adopt open source soft-ware? IEEE Softw 25(3):54–59

    Article  Google Scholar 

  • Yamada S (2014) Software reliability modelling: fundamental and applications. Springer, Tokyo/Hiedelberg

    Book  Google Scholar 

  • Yamada S (2017) Elementary software reliability growth modelling. In: 6th International conference on reliability, Infocom technologies and optimization (ICRITO), Noida, pp 2–10

  • Yamada S, Tamura Y (2016) OSS Reliability Measurement and Assessment. Springer, Cham ISBN: 978-3-319-31818-9

    Book  Google Scholar 

  • Yamada S, Ohba M, Osaki S (1983) S-shaped reliability growth modeling for software fault detection. IEEE Trans Reliab 32:475484

    Google Scholar 

  • Zhou Y et al (2005) Open source software reliability model: an empirical method. In: ACM SIGSOFT software engineering notes

  • Zou F et al (2008) Analyzing and modeling open source software bug report data. In: 19th Australian conference on software engineering

  • Zou F, Davis J (2008) Analyzing and modeling open source software bug report data. In: 19th Australian conference on software, IEEE Computer Society. https://doi.org/10.1109/ASWEC.2008.13

Download references

Acknowledgements

The authors are very grateful and thankful to the anonymous Referees and the Editor, whose comments have helped greatly in the presentation of this manuscript. The authors gratefully acknowledge the assistance of Professor Priya Ranjan, Department of Electrical and Electronics Engineering, Amity University, Noida in providing valuable inputs.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Ranjan Kumar.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Kumar, R., Kumar, S. & Tiwari, S.K. A study of software reliability on big data open source software. Int J Syst Assur Eng Manag 10, 242–250 (2019). https://doi.org/10.1007/s13198-019-00777-x

Download citation

  • Received:

  • Revised:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s13198-019-00777-x

Keywords

Navigation