How to cite this paper
Yeh, C & Fang, C. (2024). Software testing and release decision at different statistical confidence levels with consideration of debuggers’ learning and negligent factors.International Journal of Industrial Engineering Computations , 15(1), 105-126.
Refrences
Akaike, H. (1973) Information theory and an extension of the maximum likelihood principle. Second International Symposium on Information Theory, 267-281.
Ahmad, N., Khan, M. G. M., & Rafi, L.S. (2010) A Study of Testing-Effort Dependent Inflection S-Shaped Software Reliability Growth Models with Imperfect Debugging. International Journal of Quality & Reliability Management, 27(1), 89-110.
Aktekin, T., & Caglar, T. (2013). Imperfect debugging in software reliability: A Bayesian approach. European Journal of Operational Research, 227, 112-121.
Awad, M. (2016) Economic allocation of reliability growth testing using Weibull distributions. Reliability Engineering and System Safety, 152, 273–280.
Cao, P., Yang, K., & Liu, K. (2020). Optimal selection and release problem in software testing process: a continuous time stochastic control approach. European Journal of Operational Research, 285(1), 211-222. https://doi.org/10.1016/j.ejor.2019.01.075.
Chiu, K.C., Huang, Y.S., & Huang, I.C. (2019) A Study of Software Reliability Growth with Imperfect Debugging for Time-Dependent Potential Errors. International Journal of Industrial Engineering, 26(3), 376-393.
Chiu, K.C., Huang, Y.S. and Lee, T.Z. (2008) A Study of Software Reliability Growth from the Perspective of Learning Effects. Reliability Engineering and System Safety, 93(10), 1410-1421.
Cortellessa, V., Mirandola, R., & Potena, P. (2015) Managing the evolution of a software architecture at minimal cost under performance and reliability constraints. Science of Computer Programming Volume, 98(41), 439-463.
Fang, C. C., & Yeh, C. W. (2016) Effective confidence interval estimation of fault-detection process of software reliability growth models. International Journal of Systems Science, 47(12), 2878-2892.
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.
Hsu, C.J., Huang, C.Y., & Chang, J.R. (2011) Enhancing Software Reliability Modeling and Prediction through the Introduction of Time-Variable Fault Reduction Factor. Applied Mathematical Modelling, 35(1), 506-521.
Huang, C.Y. (2005) Performance analysis of software reliability growth models with testing-effort and change-point. Journal of Systems and Software, 76(2), 181-194.
Huang, C.Y., Kuo, S.Y., & Michael, R.L. (2007) An assessment of testing-effort dependent software reliability growth models. IEEE Transactions on Reliability, 56(2), 198–211.
Huang, Y.S., Chiu, K. C., & Chen, W.M. (2022) A software reliability growth model for imperfect debugging. Journal of Systems and Software, 188, 111267.
Huang, Y.S., Fang, C.C., Chou, C.C., & Tseng, T.L. (2023) A Study on Optimal Release Schedule for Multiversion Software. INFORMS Journal on Computing, DOI: 10.1287/ijoc.2021.0141.
Jin, C., & Jin, S.W. (2016) Parameter optimization of software reliability growth model with S-shaped testing-effort function using improved swarm intelligent optimization. Applied Soft Computing, 40, 283-291.
Kapur, P.K., Gupta, D., Gupta, A., & Jha, P.C. (2008) Effect of introduction of faults and imperfect debugging on release time. Ratio Mathematica, 18, 62–90.
Kapur, P.K., Pham, H., Anand, S., & Yadav, K. (2011) 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.
Ke, S.Z., & Huang, C.Y. (2020) Software reliability prediction and management: A multiple change‐point model approach. Quality and Reliability Engineering International, 36(5), 1678-1707.
Kooli, M., Kaddachi, F., Natale, G.D., Bosio, A., Benoit, P., & Torres, L. (2017) Computing reliability: On the differences between software testing and software fault injection techniques. Microprocessors and Microsystems, 50, 102-112.
Cai, K.Y., Hu, D.B., C.G., Bai, H.H., & Jing, T. (2008) Does Software Reliability Growth Behavior Follow a Non-homogeneous Poisson Process? Information and Software Technology, 50(12), 1232-1247.
Levitin, G., Xing, L., & Xiang, Y. (2020) Cost minimization of real-time mission for software systems with rejuvenation. Reliability Engineering and System Safety, 193, https://doi.org/10.1016/j.ress.2019.106593.
Li, Q., & Pham, H. (2017) NHPP software reliability model considering the uncertainty of operating environments with imperfect debugging and testing coverage. Applied Mathematical Modelling, 51, 68-85.
Li, Q., & Pham, H. (2019) A Generalized Software Reliability Growth Model With Consideration of the Uncertainty of Operating Environments, IEEE Access, 7, 84253-84267.
Pachauri, B., Dhar, J., & Kumar, A. (2015) Incorporating Inflection S-Shaped Fault Reduction Factor to Enhance Software Reliability Growth. Applied Mathematical Modelling, 39(5), 1463-1469.
Peng, R., Li, Y.F., Zhang, W.J., & Hu, Q.P. (2014) Testing Effort Dependent Software Reliability Model for Imperfect Debugging Process Considering Both Detection and Correction. Reliability Engineering and System Safety, 126, 37-43.
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.
Ramsamy, S., Govindasamy, G., & Kapur, P.K. (2012) A Software Reliability Growth Model for Estimating Debugging and the Learning Indices. International Journal of Perform ability Engineering, 8(5), 539- 549.
Saraf, I., & Iqbal, J. (2019). Generalized multi‐release modelling of software reliability growth models from the perspective of two types of imperfect debugging and change point. Quality and Reliability Engineering International, 35(7), 2358-2370. https://doi.org/10.1002/qre.2516.
Shyur, H.J. (2003) A stochastic software reliability model with imperfect-debugging and change-point. Journal of Systems and Software, 66(2), 135-141.
Shrivastava, A. K., & Kapur, P. K. (2021). Change‐points‐based software scheduling. Quality and Reliability Engineering International, 37(8), 3282-3296.
Singpurwalla, N.D., & Wilson, S.P. (1999) Statistical Methods in Software Engineering. Springer-Verlang, New York, Inc.
Tian, Q., Fang, C. C., & Yeh, C. W. (2022). Software release assessment under multiple alternatives with consideration of debuggers’ learning rate and imperfect debugging environment. Mathematics, 10(10), 1744.
Wang, J., & Wu. Z. (2016) Study of the nonlinear imperfect software debugging model. Reliability Engineering and System Safety, 153, 180-192.
Wang, J., Wu, Z., Shu, Y., & Zhang, Z. (2015) An imperfect software debugging model considering log-logistic distribution fault content function. The Journal of Systems and Software, 100, 167–181.
Wang, L., Hu, Q., & Liu, J. (2016) Software Reliability Growth Modeling and Analysis with Dual Fault Detection and Correction Processes. IIE Transactions, 48(4), 359-370.
Yamada, S., & Osaki, S. (1985) Software reliability growth modeling: Models and applications. IEEE Transactions on Software Engineering, 11(12), 1431-1437.
Yang, J., Liu, Y., Xie, M., & Zhao, M. (2016) Modeling and Analysis of Reliability of Multi-Release Open Source Software Incorporating Both Fault Detection and Correction Processes. Journal of Systems and Software, 115, 102-110.
Zhang, X., & Pham, H. (1998) A software cost model with error removal times and risk costs. International Journal of Systems Science, 29(4), 435-442.
Zhang, X., & Pham, H. (2006) Software field failure rate prediction before software deployment. The Journal of Systems and Software, 79, 291-300.
Zhao, X., Littlewood, B., Povyakalo, A., Strigini, L., & Wright, D. (2018) Conservative claims for the probability of perfection of a software-based system using operational experience of previous similar systems. Reliability Engineering and System Safety, 175, 265–282.
Zhu, M., & Pham, H. (2018) A multi-release software reliability modeling for open source software incorporating dependent fault detection process. Annals of Operations Research, 269, 773–790.
Ahmad, N., Khan, M. G. M., & Rafi, L.S. (2010) A Study of Testing-Effort Dependent Inflection S-Shaped Software Reliability Growth Models with Imperfect Debugging. International Journal of Quality & Reliability Management, 27(1), 89-110.
Aktekin, T., & Caglar, T. (2013). Imperfect debugging in software reliability: A Bayesian approach. European Journal of Operational Research, 227, 112-121.
Awad, M. (2016) Economic allocation of reliability growth testing using Weibull distributions. Reliability Engineering and System Safety, 152, 273–280.
Cao, P., Yang, K., & Liu, K. (2020). Optimal selection and release problem in software testing process: a continuous time stochastic control approach. European Journal of Operational Research, 285(1), 211-222. https://doi.org/10.1016/j.ejor.2019.01.075.
Chiu, K.C., Huang, Y.S., & Huang, I.C. (2019) A Study of Software Reliability Growth with Imperfect Debugging for Time-Dependent Potential Errors. International Journal of Industrial Engineering, 26(3), 376-393.
Chiu, K.C., Huang, Y.S. and Lee, T.Z. (2008) A Study of Software Reliability Growth from the Perspective of Learning Effects. Reliability Engineering and System Safety, 93(10), 1410-1421.
Cortellessa, V., Mirandola, R., & Potena, P. (2015) Managing the evolution of a software architecture at minimal cost under performance and reliability constraints. Science of Computer Programming Volume, 98(41), 439-463.
Fang, C. C., & Yeh, C. W. (2016) Effective confidence interval estimation of fault-detection process of software reliability growth models. International Journal of Systems Science, 47(12), 2878-2892.
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.
Hsu, C.J., Huang, C.Y., & Chang, J.R. (2011) Enhancing Software Reliability Modeling and Prediction through the Introduction of Time-Variable Fault Reduction Factor. Applied Mathematical Modelling, 35(1), 506-521.
Huang, C.Y. (2005) Performance analysis of software reliability growth models with testing-effort and change-point. Journal of Systems and Software, 76(2), 181-194.
Huang, C.Y., Kuo, S.Y., & Michael, R.L. (2007) An assessment of testing-effort dependent software reliability growth models. IEEE Transactions on Reliability, 56(2), 198–211.
Huang, Y.S., Chiu, K. C., & Chen, W.M. (2022) A software reliability growth model for imperfect debugging. Journal of Systems and Software, 188, 111267.
Huang, Y.S., Fang, C.C., Chou, C.C., & Tseng, T.L. (2023) A Study on Optimal Release Schedule for Multiversion Software. INFORMS Journal on Computing, DOI: 10.1287/ijoc.2021.0141.
Jin, C., & Jin, S.W. (2016) Parameter optimization of software reliability growth model with S-shaped testing-effort function using improved swarm intelligent optimization. Applied Soft Computing, 40, 283-291.
Kapur, P.K., Gupta, D., Gupta, A., & Jha, P.C. (2008) Effect of introduction of faults and imperfect debugging on release time. Ratio Mathematica, 18, 62–90.
Kapur, P.K., Pham, H., Anand, S., & Yadav, K. (2011) 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.
Ke, S.Z., & Huang, C.Y. (2020) Software reliability prediction and management: A multiple change‐point model approach. Quality and Reliability Engineering International, 36(5), 1678-1707.
Kooli, M., Kaddachi, F., Natale, G.D., Bosio, A., Benoit, P., & Torres, L. (2017) Computing reliability: On the differences between software testing and software fault injection techniques. Microprocessors and Microsystems, 50, 102-112.
Cai, K.Y., Hu, D.B., C.G., Bai, H.H., & Jing, T. (2008) Does Software Reliability Growth Behavior Follow a Non-homogeneous Poisson Process? Information and Software Technology, 50(12), 1232-1247.
Levitin, G., Xing, L., & Xiang, Y. (2020) Cost minimization of real-time mission for software systems with rejuvenation. Reliability Engineering and System Safety, 193, https://doi.org/10.1016/j.ress.2019.106593.
Li, Q., & Pham, H. (2017) NHPP software reliability model considering the uncertainty of operating environments with imperfect debugging and testing coverage. Applied Mathematical Modelling, 51, 68-85.
Li, Q., & Pham, H. (2019) A Generalized Software Reliability Growth Model With Consideration of the Uncertainty of Operating Environments, IEEE Access, 7, 84253-84267.
Pachauri, B., Dhar, J., & Kumar, A. (2015) Incorporating Inflection S-Shaped Fault Reduction Factor to Enhance Software Reliability Growth. Applied Mathematical Modelling, 39(5), 1463-1469.
Peng, R., Li, Y.F., Zhang, W.J., & Hu, Q.P. (2014) Testing Effort Dependent Software Reliability Model for Imperfect Debugging Process Considering Both Detection and Correction. Reliability Engineering and System Safety, 126, 37-43.
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.
Ramsamy, S., Govindasamy, G., & Kapur, P.K. (2012) A Software Reliability Growth Model for Estimating Debugging and the Learning Indices. International Journal of Perform ability Engineering, 8(5), 539- 549.
Saraf, I., & Iqbal, J. (2019). Generalized multi‐release modelling of software reliability growth models from the perspective of two types of imperfect debugging and change point. Quality and Reliability Engineering International, 35(7), 2358-2370. https://doi.org/10.1002/qre.2516.
Shyur, H.J. (2003) A stochastic software reliability model with imperfect-debugging and change-point. Journal of Systems and Software, 66(2), 135-141.
Shrivastava, A. K., & Kapur, P. K. (2021). Change‐points‐based software scheduling. Quality and Reliability Engineering International, 37(8), 3282-3296.
Singpurwalla, N.D., & Wilson, S.P. (1999) Statistical Methods in Software Engineering. Springer-Verlang, New York, Inc.
Tian, Q., Fang, C. C., & Yeh, C. W. (2022). Software release assessment under multiple alternatives with consideration of debuggers’ learning rate and imperfect debugging environment. Mathematics, 10(10), 1744.
Wang, J., & Wu. Z. (2016) Study of the nonlinear imperfect software debugging model. Reliability Engineering and System Safety, 153, 180-192.
Wang, J., Wu, Z., Shu, Y., & Zhang, Z. (2015) An imperfect software debugging model considering log-logistic distribution fault content function. The Journal of Systems and Software, 100, 167–181.
Wang, L., Hu, Q., & Liu, J. (2016) Software Reliability Growth Modeling and Analysis with Dual Fault Detection and Correction Processes. IIE Transactions, 48(4), 359-370.
Yamada, S., & Osaki, S. (1985) Software reliability growth modeling: Models and applications. IEEE Transactions on Software Engineering, 11(12), 1431-1437.
Yang, J., Liu, Y., Xie, M., & Zhao, M. (2016) Modeling and Analysis of Reliability of Multi-Release Open Source Software Incorporating Both Fault Detection and Correction Processes. Journal of Systems and Software, 115, 102-110.
Zhang, X., & Pham, H. (1998) A software cost model with error removal times and risk costs. International Journal of Systems Science, 29(4), 435-442.
Zhang, X., & Pham, H. (2006) Software field failure rate prediction before software deployment. The Journal of Systems and Software, 79, 291-300.
Zhao, X., Littlewood, B., Povyakalo, A., Strigini, L., & Wright, D. (2018) Conservative claims for the probability of perfection of a software-based system using operational experience of previous similar systems. Reliability Engineering and System Safety, 175, 265–282.
Zhu, M., & Pham, H. (2018) A multi-release software reliability modeling for open source software incorporating dependent fault detection process. Annals of Operations Research, 269, 773–790.