A testing-coverage software reliability model with the uncertainty of operating environments

References

• Ehrlich, W., Prasanna, B., Stampfel, J., & Wu, J. (1993). Determining the cost of a stop testing decision. IEEE Software, 10(2), 33–42.
   Web of Science ®Google Scholar
• Gao, J., Esponoza, R., & He, J. (2005). Testing coverage analysis for software validation. In Proceedings of the 29th Annual International Computer Software Applications Conference. Hong Kong.
   Google Scholar
• Goel, A.L., & Okumoto, K. (1979). Time dependent error detection rate model for software reliability and other performance measures. IEEE Transactions on Reliability, 28(3), 206–211.
   Web of Science ®Google Scholar
• Gokhale, S.S., & Mullen, R.E. (2004). From test count to code coverage using the lognormal failure rate. In Proceeding of the 15th IEEE International Symposium on Software Reliability Engineering (pp. 295–305). Piscataway, NJ: IEEE Computer Society.
   Google Scholar
• Inoue, S., & Yamada, S. (2008). Two-dimensional software reliability assessment with testing-coverage. The Second International Conference on Secure System Integration and Reliability Improvement (pp. 150–157). Piscataway, NJ: IEEE Computer Society.
   Google Scholar
• Jelinski, Z., & Moranda, P.B. (1972). Software reliability research. In W. Freiberger (Ed.), Statistical computer performance evaluation (pp. 465–497). New York, NY: Academic Press.
   Google Scholar
• Kapur, P.K., & Garg, R.B. (1992). A software reliability growth model for an error removal phenomenon. Software Engineering Journal, 7, 291–294.
   Web of Science ®Google Scholar
• Kapur, P.K., Garg, R.B., & Kumar, S. (1999). Contributions to hardware and software reliability. Singapore: World Scientific.
   Google Scholar
• Kapur, P.K., Pham, H., Aggarwal, A.G., & Kaur, G. (2012, September). Two dimensional multi-release software reliability modeling and optimal release planning. IEEE Transactions on Reliability, 61(3), 758–768.
   Web of Science ®Google Scholar
• Kapur, P.K., Pham, H., Anand, S., & Yadav, K. (2011, March). A unified approach for developing software reliability growth models in the presence of imperfect debugging and error generation. IEEE Transactions on Reliability, 60(1), 331–340.
   Web of Science ®Google Scholar
• Musa, J.D., Iannino, A., & Okumoto, K. (1987). Software reliability: Measurement, prediction, and application. New York, NY: McGraw-Hill.
   Google Scholar
• Ohba, M. (1984). Inflexion S-shaped software reliability growth models. In S. Osaki & Y. Hatoyama (Eds.), Stochastic models in reliability theory (pp. 144–162). Berlin: Springer-Verlag.
   Google Scholar
• Pham, H. (1993). Software reliability assessment: Imperfect debugging and multiple failure types in software development ( EG&G-RAAM-10737). Idaho Falls, Idaho: Idaho National Engineering Laboratory.
   Google Scholar
• Pham, H. (1996). A software cost model with imperfect debugging, random life cycle and penalty cost. International Journal of Systems Science, 27(5), 455–463.
   Web of Science ®Google Scholar
• Pham, H. (1999). Software reliability. In J.G. Webster (Ed.), Wiley encyclopedia of electrical and electronics engineering (Vol. 19, pp. 565–578). New York, NY: John Wiley and Sons.
   Google Scholar
• Pham, H. (2000). Software reliability. Singapore: Springer.
   Google Scholar
• Pham, H. (2006). System software reliability (pp. 149–150). London: Springer.
   Google Scholar
• Pham, H. (2013, August). A software reliability model with vtub-shaped fault-detection rate subject to operating environments. In Proceedings of the 19th ISSAT International Conference on Reliability and Quality in Design (pp. 33–37). Piscataway, NJ: ISSAT Press.
   Google Scholar
• Pham, H. (2014). A new software reliability model with vtub-shped fault detection rate and the uncertainty of operating environments. Optimization, 63, 1481–1490.
   Web of Science ®Google Scholar
• Pham, H., Nordmann, L., & Zhang, X. (1999). A general imperfect software debugging model with s-shaped fault detection rate. IEEE Transactions on Reliability, 48(2), 169–175.
   Google Scholar
• Pham, H., & Zhang, X. (1997). An NHPP software reliability models and its comparison. International Journal of Reliability, Quality and Safety Engineering, 4(3), 269–282.
   Google Scholar
• Pham, H., & Zhang, X. (2003). NHPP software reliability and cost models with testing coverage. European Journal of Operational Research, 145(2), 443–454.
   Web of Science ®Google Scholar
• Pham, L., & Pham, H. (2000). Software reliability models with time dependent hazard function based on Bayesian approach. IEEE Transactions on Systems, Man, and Cybernetics – Part A, 30(1), 25–35.
   PubMed Web of Science ®Google Scholar
• Teng, X., & Pham, H. (2004). Software cost model for quantifying the gain with considerations of random field environments. IEEE Transactions on Computers, 53(3), 380–384.
   Google Scholar
• Teng, X., & Pham, H. (2006). A new methodology for predicting software reliability in the random field environments. IEEE Transactions on Reliability, 55(3), 458–468.
   Web of Science ®Google Scholar
• Yamada, S., Ohba, M., & Osaki, S. (1983). S-shaped reliability growth modeling for software fault detection. IEEE Transactions on Reliability, 32(5), 475–484.
   Web of Science ®Google Scholar
• Yamada, S., & Osaki, S. (1985). Software reliability growth modeling: Models and applications. IEEE Transactions on Software Engineering, 11(12), 1431–1437.
   Web of Science ®Google Scholar
• Yamada, S., Tokuno, K., & Osaki, S. (1992). Imperfect debugging models with fault introduction rate for software reliability assessment. International Journal of Systems Science, 23(12), 2241–2252.
   Web of Science ®Google Scholar
• Wood, A. (1996). Predicting software reliability. IEEE Computer, 11, 69–77.
   Web of Science ®Google Scholar