Communications for Statistical Applications and Methods

  • 제15권6호
  • /
  • Pages.875-881
  • /
  • 2008
  • /
  • 2287-7843(pISSN)
  • /
  • 2383-4757(eISSN)
한국통계학회 (The Korean Statistical Society)
권호 표지
DOI QR코드

DOI QR Code

A General Coverage-Based NHPP SRGM Framework

  • Park, Joong-Yang (Department of Information and Statistics, College of Natural Science, RINS and RICI, Gyeosangsang National University) ;
  • Lee, Gye-Min (Department of Information and Statistics, College of Natural Science, RINS and RICI, Gyeosangsang National University) ;
  • Park, Jae-Heung (Department of Computer Science, College of Natural Science, RINS and RICI, Gyeosangsang National University)
  • 발행 : 2008.11.30
PDF 다운로드
⟨ 이전 논문 다음 논문 ⟩

초록

This paper first discusses the existing non-homogeneous Poisson process(NHPP) software reliability growth model(SRGM) frameworks with respect to capability of representing software reliability growth phenomenon. As an enhancement of representational capability a new general coverage-based NHPP SRGM framework is developed. Issues associated with application of the new framework are then considered.

키워드

참고문헌

  1. Goel, A. L. and Okumoto, K. (1979). Time-dependent error-detection rate model for software rliability and other performance measures, IEEE Transactions on Reliability, 28, 206-211 https://doi.org/10.1109/TR.1979.5220566
  2. Gokhale, S. S. and Mullen, R. E. (2004). From test count to code coverage using the lognormal failture rate, In Proceedings of the 15th International Symposium on Software Reliability Engineering, 295-305
  3. Gokhale, S. S. and Mullen, R. E. (2005). Dynamic code coveage metrics: A lognormal perspective, In Proceedings of the 11th IEEE International Software Metrics Symposium
  4. Gokhale, S. S., Philip, T., Marinos, P. N. and Trivedi, K. S. (1996). Unification of finite failure non-homogeneous Poisson process models through test coverage, In Proceedings of the 7th International Symposium on Software Reliability Engineering, 299-307
  5. Huang, C. Y., Lyu, M. R. and Kuo, S. Y. (2003). A unified scheme of some nonhomogeneous Poisson process models for software reliability estimation, IEEE Transactions of Software Engineering, 29, 261-269 https://doi.org/10.1109/TSE.2003.1183936
  6. Kuo, S. Y., Huang, C. Y. and Lyu, M. R. (2001). Framework for modeling software reliability, using various testing-efforts and fault-detection rates, IEEE Transactions on Reliability, 50, 310-320 https://doi.org/10.1109/24.974129
  7. Ohba, M. (1984). Inflection S-shaped software reliability growth models, Stochastic Models in Reliability Theory, Springer, Berlin, 144-162
  8. Park, J. Y. and Fujiwara, T. (2006). Coverage frowth functions for software reliability modeling, Proceedings of the 2nd AIWARM, Busan, 435-442
  9. Park, J. Y., Lee, G. and Park, J. H. (2007). A class of discrete time coverage growth functions for software reliability engineering, The Korean Communications in Statistics, 14, 497-506 https://doi.org/10.5351/CKSS.2007.14.3.497
  10. Park, J. Y., Lee, G. and Park, J. H. (2008). A class of coverage growth functions and its practical application, Journal of the Korean Statistical Society, 37, 241-247 https://doi.org/10.1016/j.jkss.2008.01.002
  11. Pham, H., Nordmann, L. and Zhang, X. (1999). A general imperfect software debugging model with S-shaped fault detection rate, IEEE Transactions on Reliability, 48, 169-175 https://doi.org/10.1109/24.784276
  12. Pham, H. and Zhang, X. (1997). An NHPP software reliability model and its comparison, International Journal of Reliability, Quality and Safety Engineering, 4, 269-282
  13. Pham, H. and Zhang, X. (2003). NHPP software reliability and cost models with testing coverage, European Journal of Operational Research, 145, 443-454 https://doi.org/10.1016/S0377-2217(02)00181-9
  14. Piwowarski, P., Ohba, M. and Caruso, J. (1993). Coverage measurement experience during function test, In Proceedings of the 15th International Conference on Software Engineering, 287-301
  15. Yamada, S., Ohba, M. and Osaki, S. (1983). S-shaped reliability growth modeling for software error detection, IEEE Transactions on Reliability, 32, 475-484 https://doi.org/10.1109/TR.1983.5221735
  16. Yamada, S., Ohtera, H. and Narihisa, H. (1986). Software reliability growth models with testing-effort, IEEE Transactions on Reliability, 35, 19-23 https://doi.org/10.1109/TR.1986.4335332
  17. Yamamoto, T., Inoue, S. and Yamada, S. (2004). A software reliability growth model with testing-coverage maturity process, In Proceedings of the 10th ISSAT International Conference on Reliability and Quality in Design, 299-303
  18. Zhang, X., Teng, X. and Pham, H. (2003). Considering fault removal efficiency in software reliability assessment, IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans, 33, 114-120

피인용 문헌

  1. Selection of a Predictive Coverage Growth Function vol.17, pp.6, 2010, https://doi.org/10.5351/CKSS.2010.17.6.909
  2. Estimation of Coverage Growth Functions vol.18, pp.5, 2011, https://doi.org/10.5351/CKSS.2011.18.5.667
  3. A NHPP based software reliability model and optimal release policy with logistic–exponential test coverage under imperfect debugging vol.5, pp.3, 2014, https://doi.org/10.1007/s13198-013-0181-6
  4. Virtual Coverage: A New Approach to Coverage-Based Software Reliability Engineering vol.20, pp.6, 2013, https://doi.org/10.5351/CSAM.2013.20.6.467