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


Nowadays, software is playing an ever increasing role in our daily lives, from listening music at homes to uninterrupted entertainment during travel, from driving car to ensuring safe air travel, and from variety of home appliances to safety critical medical equipments. It is virtually impossible to conduct many day-to-day activities without the aid of computer systems controlled by software. As more reliance is placed on these software systems, it is essential that they operate reliably. Failure to do so can result in high monetary, property, or human losses. Early sofware reliability prediction can help the developers to produce reliable software in lesser cost and time.


Fault Density Software Reliability Operational Profile Fault Prediction Software Metrics 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


  1. IEEE. (1991). IEEE standard glossary of software engineering terminology. STD-729-991, ANSI/IEEE.Google Scholar
  2. Musa, J. D., Iannino, A., & Okumoto, K. (1987). Software reliability: Measurement, prediction, and application. McGraw–Hill Publication.Google Scholar
  3. Lyu, M. R. (1996). Handbook of software reliability engineering. NY: McGraw–Hill/IEE Computer Society Press.Google Scholar
  4. Pham, H. (2006). System software reliability, reliability engineering series. London: Springer.Google Scholar
  5. Jelinski, Z., & Moranda, P. B. (1972). Software reliability research. In W. Freiberger (Ed.), Statistical computer performance evaluation (pp. 465–484). NY: Academic Press.Google Scholar
  6. Shooman, M. L. (1972). Probabilistic models for software reliability prediction. In W. Freiberger (Ed.), Statistical computer performance evaluation (pp. 485–502). NY: Academic Press.Google Scholar
  7. Littlewood, B., & Verrall, J. (1973). A bayesian reliability growth model for computer software. Journal of the Royal Statistical Society, series C, 22(3), 332–346.MathSciNetGoogle Scholar
  8. Musa, J. D. (1975). A theory of software reliability and its application. IEEE Transaction on Software Engineering, SE-1, 312–327.Google Scholar
  9. Schick, G. J., & Wolverton, R. W. (1978). An analysis of competing software reliability model. IEEE Transaction on Software Engineering, SE-4(2), 104–120.Google Scholar
  10. Goel, A. L., & Okumoto, K. (1979). A time-dependent error detection rate model for software reliability and other performance measure. IEEE Transaction on Reliability, R-28, 206–211.Google Scholar
  11. Kapur, P. K., & Garg, R. B. (1990). A software reliability growth model under imperfect debugging. RAIRO, 24, 295–305.MATHGoogle Scholar
  12. Chatterjee, S., Misra, R. B., & Alam, S. S. (1997). Joint effect of test effort and learning factor on software reliability and optimal release policy. International Journal of System Science, 28(4), 391–396.MATHCrossRefGoogle Scholar
  13. Gaffney, G. E., & Pietrolewiez, J. (1990). An automated model for software early error prediction (SWEEP). In Proceeding of 13th Minnow Brook Workshop on Software Reliability.Google Scholar
  14. Agresti, W. W., & Evanco, W. M. (1992). Projecting software defect from analyzing Ada design. IEEE Transaction on Software Engineering, 18(11), 988–997.CrossRefGoogle Scholar
  15. Rome Laboratory. (1992). Methodology for software reliability prediction and assessment (vol. 1–2). Technical Report RL-TR-92-52.Google Scholar
  16. Yamada, S., Ohba, M., & Osaki, S. (1983). S-shaped reliability growth modelling for software error detection. IEEE Transaction on Reliability, R-32, 475–478.Google Scholar
  17. IEEE. (1988). IEEE guide for the use of IEEE standard dictionary of measures to produce reliable software. IEEE Standard 982.2.Google Scholar
  18. Krishnan, M. S., & Kellner, M. I. (1999). Measuring process consistency: implications reducing software defects. IEEE Transaction on Software Engineering, 25(6), 800–815.CrossRefGoogle Scholar
  19. Diaz, M., & Sligo, J. (1997). How software process improvement helped Motorola. IEEE Software, 14(5), 75–81.CrossRefGoogle Scholar
  20. Harter, D. E., Krishnan, M. S., & Slaughter, S. A. (2000). Effects of process maturity on quality, cycle time and effort in software product development. Management Science, 46, 451–466.CrossRefGoogle Scholar
  21. Kumar, K. S., & Misra, R. B. (2008). An enhanced model for early software reliability prediction using software engineering metrics. In Proceedings of 2nd International Conference on Secure System Integration and Reliability Improvement (pp. 177–178).Google Scholar
  22. Li, M., & Smidts, C. (2003). A ranking of software engineering measures based on expert opinion. IEEE Transaction on Software Engineering, 29(9), 811–824.CrossRefGoogle Scholar
  23. Fenton, N., Neil, N., Marsh, W., Hearty, P., Radlinski, L., & Krause, P. (2008). On the effectiveness of early life cycle defect prediction with Bayesian Nets. Empirical of Software Engineering, 13, 499–537.CrossRefGoogle Scholar
  24. Pressman, R. S. (2005), Software engineering: A practitioner’s approach (6th ed.). New York: McGraw-Hill Publication.Google Scholar
  25. Fenton, N. E., & Neil, M. (1999). A critique of software defect prediction models. IEEE Transaction on Software Engineering, 25(5), 675–689.CrossRefGoogle Scholar
  26. Pandey, A. K., & Goyal, N. K. (2010). Fault prediction model by fuzzy profile development of reliability relevant software metrics. International Journal of Computer Applications, 11(6), 34–41.CrossRefGoogle Scholar
  27. Furuyama, A. Y., & Lio, K. (1997). Analysis of fault generation caused by stress during software development. The Journal of Systems and Software, 38, 13–25.CrossRefGoogle Scholar
  28. 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.CrossRefGoogle Scholar
  29. Khoshgoftaar, T. M., & Seliya, N. (2002). Tree-based software quality models for fault prediction. In Proceedings of 8th International Software Metrics Symposium, Ottawa, Ontario, Canada (pp. 203–214).Google Scholar

Copyright information

© Springer India 2013

Authors and Affiliations

  1. 1.AECOM India Private LimitedHyderabadIndia
  2. 2.Reliability Engineering CentreIndian Institute of Technology KharagpurKharagpurIndia

Personalised recommendations