Skip to main content
SpringerLink
Log in

How to Explain Empirical Distribution of Software Defects by Severity

  • Conference paper
  • First Online:
Recent Developments in Data Science and Intelligent Analysis of Information (ICDSIAI 2018)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 836))

  • 424 Accesses

Abstract

In the last decades, several tools have appeared that, given a software package, mark possible defects of different potential severity. Our empirical analysis has shown that in most situations, we observe the same distribution or software defects by severity. In this paper, we present this empirical distribution, and we use interval-related ideas to provide an explanation for this empirical distribution.

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

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Ackerman, A.F., Buchwald, L.S., Lewski, F.H.: Software inspections: an effective verification process. IEEE Softw. 6(3), 31–36 (1989)

    Article  Google Scholar 

  2. D’Ambros M., Bacchelli A., Lanza, M.: On the impact of design flaws on software defects. In: Proceedings of the 10th International Conference on Quality Software, QSIC 2010, Zhangjiajie, China, 14–15 July 2010, pp. 23–31 (2010)

    Google Scholar 

  3. Harter, D.E., Kemerer, C.F., Slaughter, S.A.: Does software process improvement reduce the severity of defects? A longitudinal field study. IEEE Trans. Softw. Eng. 38(4), 810–827 (2012)

    Article  Google Scholar 

  4. Javed, T., Durrani, Q.S.: A study to investigate the impact of requirements instability on software defects. ACM SIGSOFT Softw. Eng. Notes 29(3), 1–7 (2004)

    Article  Google Scholar 

  5. Jaynes, E.T., Bretthorst, G.L.: Probability Theory: The Logic of Science. Cambridge University Press, Cambridge (2003)

    Book  Google Scholar 

  6. Jaulin, L., Kiefer, M., Didrit, O., Walter, E.: Applied Interval Analysis, with Examples in Parameter and State Estimation, Robust Control, and Robotics. Springer, London (2001)

    MATH  Google Scholar 

  7. Kapur, P.K., Kumar, A., Yadav, K., Khatri, S.K.: Software reliability growth modelling for errors of different severity using change point. Int. J. Reliab. Qual. Saf. Eng. 14(4), 311–326 (2007)

    Article  Google Scholar 

  8. Mayer, G.: Interval Analysis and Automatic Result Verification. de Gruyter, Berlin (2017)

    Book  Google Scholar 

  9. The MITRE Corporation: Common weakness enumeration: a community-developed list of software weakness types. https://cwe.mitre.org/cwss/cwss_v1.0.1.html. Accessed 2 Mar 1018

  10. Moore, R.E., Kearfott, R.B., Cloud, M.J.: Introduction to Interval Analysis. SIAM, Philadelphia (2009)

    Book  Google Scholar 

  11. Ostrand, T.J., Weyuker, E.J.: The distribution of faults in a large industrial software system. ACM SIGSOFT Softw. Eng. Notes 27(4), 55–64 (2002)

    Article  Google Scholar 

  12. Sullivan, M., Chillarege, R.: Software defects and their impact on system availability – a study of field failures in operating systems. In: Proceedings of the 21st International Symposium on Fault-Tolerant Computing, Montreal, Canada, 25–27 June 1991, pp. 2–9 (1991)

    Google Scholar 

  13. Sullivan, M., Chillarege, R.: A comparison of software defects in database management systems and operating systems. In: Proceedings of the 22nd International Symposium on Fault-Tolerant Computing, Boston, Massachusetts, 8–10 July 1992, pp. 475–484 (1992)

    Google Scholar 

  14. Zheng, J., Williams, L., Nagappan, N., Snipes, W., Hudepohl, J.P., Vouk, M.A.: On the value of static analysis for fault detection in software. IEEE Trans. Softw. Eng. 32(4), 240–253 (2006)

    Article  Google Scholar 

Download references

Acknowledgments

This work was supported in part by the US National Science Foundation grant HRD-1242122.

The authors are greatly thankful to the anonymous referees for their valuable suggestions and to Dan Tavrov for his help.

Author information

Authors and Affiliations

  1. Department of Industrial, Manufacturing, and Systems Engineering, University of Texas at El Paso, El Paso, TX, 79968, USA

    Francisco Zapata

  2. Department of Teacher Education, University of Texas at El Paso, El Paso, TX, 79968, USA

    Olga Kosheleva

  3. Department of Computer Science, University of Texas at El Paso, El Paso, TX, 79968, USA

    Vladik Kreinovich

Authors
  1. Francisco Zapata
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Olga Kosheleva
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Vladik Kreinovich
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Vladik Kreinovich .

Editor information

Editors and Affiliations

  1. Applied Mathematics Department, Igor Sikorsky Kyiv Polytechnic Institute, Kyiv, Ukraine

    Oleg Chertov

  2. Department of Economics, University of Pittsburgh, Pittsburgh, Pennsylvania, USA

    Tymofiy Mylovanov

  3. Department of Intelligent Information Systems, Petro Mohyla Black Sea National University, Mykolaiv, Ukraine

    Yuriy Kondratenko

  4. Systems Research Institute, Polish Academy of Sciences, Warsaw, Poland

    Janusz Kacprzyk

  5. Department of Computer Science, University of Texas at El Paso, El Paso, Texas, USA

    Vladik Kreinovich

  6. Institute for Information Transmission Problems, Russian Academy of Sciences, Moscow, Russia

    Vadim Stefanuk

Rights and permissions

Reprints and permissions

Copyright information

© 2019 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Zapata, F., Kosheleva, O., Kreinovich, V. (2019). How to Explain Empirical Distribution of Software Defects by Severity. In: Chertov, O., Mylovanov, T., Kondratenko, Y., Kacprzyk, J., Kreinovich, V., Stefanuk, V. (eds) Recent Developments in Data Science and Intelligent Analysis of Information. ICDSIAI 2018. Advances in Intelligent Systems and Computing, vol 836. Springer, Cham. https://doi.org/10.1007/978-3-319-97885-7_10

Download citation

Publish with us

Policies and ethics

Search

Navigation