Skip to main content
SpringerLink
Log in

Prediction and Ranking of Fault-Prone Software Modules

  • Chapter
  • First Online:
Early Software Reliability Prediction

Part of the book series: Studies in Fuzziness and Soft Computing ((STUDFUZZ,volume 303))

Abstract

Large and complex software systems are developed by integrating various independent modules. It is important to ensure quality of these modules through independent testing where modules are tested and faults are removed as soon as failures are experienced. System failures due to the software failure are common and result in undesirable consequences. Moreover, it is difficult to produce fault-free software due to problem complexity, complexity of human behavior, and the resource constrains. This chapter presents a noval approach for prediction and ranking of the software module using classification and fuzzy ordering algoritms.

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

Access this chapter

Log in via an institution
eBook
USD 16.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 109.99
Price excludes VAT (USA)
  • Durable hardcover 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

  • Catal, C., & Diri, B. (2008). A fault prediction model with limited fault data to improve test process. In Proceedings of the 9th International Conference on Product Focused Software Process Improvement (pp. 244–257).

    Google Scholar 

  • El-Emam, K., Melo, W., & Machado, J. C. (2001). The prediction of faulty classes using object-oriented design metrics. Journal of Systems and Software, 56(1), 63–75.

    Article  Google Scholar 

  • Elish, K. O., & Elish, M. O. (2008). Predicting defect-prone software modules using support vector machines. Journal of Systems and Software, 81(2008), 649–660.

    Article  Google Scholar 

  • Fenton, N. (1991). Software metrics: a rigorous approach. London: Chapmann & Hall.

    MATH  Google Scholar 

  • Fenton, N. E., & Neil, M. (1999). A critique of software defect prediction models. IEEE Transaction on Software Engineering, 25(5), 675–689.

    Article  Google Scholar 

  • Fenton, N. E., & Neil, M. (2000). Software metrics: roadmap. In Proceedings of the Conference on The Future of Software Engineering (pp. 375–370). Limerick, Ireland.

    Google Scholar 

  • Han, J., & Kamber, M. (2001). Data mining: concepts and techniques. USA: Morgan Kaufmann Publishers.

    Google Scholar 

  • Khoshgoftaar, T. M., & Allen, E. B. (1999). A comparative study of ordering and classification of fault-prone software modules. Empirical Software Engineering, 4, 159–186.

    Article  Google Scholar 

  • Khoshgoftaar, T. M., & Allen, E. B. (2003). Ordering fault–prone software modules. Software Quality Journal, 11, 19–37.

    Article  Google Scholar 

  • Khoshgoftaar, T. M., & Munson, J. C. (1990). Predicting software development errors using complexity metrics. IEEE Journal on Selected Areas in Communication, 8(2), 253–261.

    Article  Google Scholar 

  • Khoshgoftaar, T. M., & Seliya, N. (2003). Fault prediction modeling for software quality estimation: comparing commonly used techniques. Empirical Software Engineering, 8, 255–283.

    Article  Google Scholar 

  • Kumar, K. S. (2009). Early Software Reliability and Quality Prediction, Ph.D. Thesis, IIT Kharagpur, Kharagpur, India.

    Google Scholar 

  • Kumar, K. S., Misra, R. B., & Goyal, N. K. (2008). Development of fuzzy software operational profile. International Journal of Reliability, Quality and Safety Engineering, 15(6), 581–597.

    Article  Google Scholar 

  • Musa, J. D., Iannino, A., Okumoto, K. (1987). Software reliability: measurement, prediction, and application. New York: McGraw–Hill Publication.

    Google Scholar 

  • NASA (2004). NASA metrics data program, http://mdp.ivv.nasa.gov/.

  • Ohlsson, N., & Alberg, H. (1996). Predicting fault–prone software modules in telephone switches. IEEE Transaction on Software Engineering, 22(12), 886–894.

    Article  Google Scholar 

  • Quinlan, J. R. (1986). Induction of decision trees. Machine Learning, 1, 81–106.

    Google Scholar 

  • Ross, T. J. (2005). Fuzzy logic with engineering applications (2nd ed.). India: Willy.

    Google Scholar 

  • Schneidewind, N. F. (1992). Methodology for validating software metrics. IEEE Transactions on Software Engineering, 18(5), 410–422.

    Article  Google Scholar 

  • Yadav, O. P., Singh, N., Chinnam, R. B., & Goel, P. S. (2003). A fuzzy logic based approach to reliability improvement during product development. Reliability Engineering and System Safety, 80, 63–74.

    Article  Google Scholar 

  • Zadeh, L. A. (1965). Fuzzy Sets: Information and Control, 8(3), 338–353.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. AECOM India Private Limited, DLF Building, Plot no 129-132, APHB Colo, Gachibowli, Hyderabad, Andra Pradesh, India

    Ajeet Kumar Pandey

  2. Reliability Engineering Centre, Indian Institute of Technology Kharagpur, IIT Kharagpur, Kharagpur, 721302, West Bengal, India

    Neeraj Kumar Goyal

Authors
  1. Ajeet Kumar Pandey
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Neeraj Kumar Goyal
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Ajeet Kumar Pandey .

Rights and permissions

Reprints and permissions

Copyright information

© 2013 Springer India

About this chapter

Cite this chapter

Pandey, A.K., Goyal, N.K. (2013). Prediction and Ranking of Fault-Prone Software Modules. In: Early Software Reliability Prediction. Studies in Fuzziness and Soft Computing, vol 303. Springer, India. https://doi.org/10.1007/978-81-322-1176-1_5

Download citation

  • DOI: https://doi.org/10.1007/978-81-322-1176-1_5

  • Published:

  • Publisher Name: Springer, India

  • Print ISBN: 978-81-322-1175-4

  • Online ISBN: 978-81-322-1176-1

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation