Abstract
Reliability is one of the most relevant software quality attributes. The literature offers a variety of mathematical models - namely, software reliability growth models (SRGMs) - to estimate the reliability of a software product at a given time, as well as to predict the reliability that will be achieved as testing activities progress. One of the typical assumptions of SRGMs is the immediate debugging of detected faults. In reality, the impact of the debugging process cannot be neglected at all. This paper reports the results of a real-world case-study in which we analyze the debugging process of a Customer Relationship Management (CRM) system, and study its impact on SRGM-based reliability estimation and prediction.
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References
Stringfellow, C., Amschler Andrews, A.: An Empirical Method for Selecting Software Reliability Growth Models. Empirical Software Engineering 7(4) (2002)
Farr, W.: Software Reliability Modeling Survey. In: Lyu, M.R. (ed.) Handbook of Software Reliability Engineering, pp. 71–117. McGraw-Hill (1996)
Musa, J.D., Okumoto, K.: A logarithmic Poisson execution time model for software reliability measurement. In: Proc. 7th Int. Conf. on Software Engineering (ICSE), pp. 230–238 (1984)
Zachariah, B., Rattihalli, R.N.: Failure Size Proportional Models and an Analysis of Failure Detection Abilities of Software Testing Strategies. IEEE Trans. on Reliability 56(2) (2007)
Dugan, J.B.: Automated Analysis of Phase-Mission Reliability. IEEE Trans. on Reliability 40, 45–52 (1991)
Garzia, M.R.: Assessing the Reliability of Windows Servers. In: Proc. of IEEE Dependable Systems and Networks Conference, DSN 2002 (2002)
Pietrantuono, R., Russo, S., Trivedi, K.S.: Online Monitoring of Software System Reliability. In: Proc. of the European Dependable Computing Conference (EDCC), pp. 209–218 (2010)
Cotroneo, D., Pietrantuono, R., Russo, S.: Combining Operational and Debug Testing for Improving Reliability. IEEE Trans. on Reliability 62(2), 408–423 (2013)
Goel, A.L., Okumoto, K.: Time-dependent error-detection rate model for software reliability and other performance measures. IEEE Trans. on Reliability 28(3) (1979)
Yamada, S., Ohba, M., Osaki, S.: S-Shaped Reliability Growth Modeling for Software Error Detection. IEEE Trans. on Reliability 32(5) (1983)
Gokhale, S.S., Trivedi, K.S.: Log-logistic software reliability growth model. In: Proc. 3rd Int. High-Assurance Systems Engineering Symposium, pp. 34–41 (1998)
Yamada, S., Ohtera, H., Narihisa, H.: Software reliability growth models with testing effort. IEEE Trans. on Reliability R-35 (1986)
Goel, A.L.: Software Reliability Models: Assumptions, Limitations and Applicability. IEEE Trans. on Software Engineering SE-11(12) (1985)
Okamura, H., Watanabe, Y., Dohi, T.: An iterative scheme for maximum likelihood estimation in software reliability modeling. In: Proc. 14th Int. Symposium on Software Reliability Engineering (ISSRE), pp. 246–256 (2003)
Ohishi, K., Okamura, H., Dohi, T.: Gompertz software reliability model: Estimation algorithm and empirical validation. Journal of Systems and Software 82(3) (2009)
Jain, M., Manjula, T.: Software reliability growth model (SRGM) with imperfect debugging, fault reduction factor and multiple change-point. In: Deep, K., Nagar, A., Pant, M., Bansal, J.C. (eds.) Proceedings of the International Conf. on SocProS 2011. AISC, vol. 131, pp. 1027–1037. Springer, Heidelberg (2012)
Musa, J.D., Iannino, A., Okumoto, K.: Software Reliability, Measurement, Prediction and Application. McGraw Hill (1987)
Huang, C.-Y., Huang, W.-C.: Software Reliability Analysis and Measurement Using Finite and Infinite Server Queueing Models. IEEE Trans. on Reliability 57(1), 192–203 (2008)
Nguyen, T.T., Nguyen, T.N., Duesterwald, E., Klinger, T., Santhanam, P.: Inferring developer expertise through defect analysis. In: 34th International Conference on Software Engineering (ICSE), pp. 1297–1300 (2012)
Zhang, F., Khomh, F., Zou, Y., Hassan, A.E.: An empirical study on factors impacting bug fixing time. In: 19th Working Conference on Reverse Engineering, WCRE (2012)
Ihara, A., Ohira, M., Matsumoto, K.: An analysis method for improving a bug modification process in open source software development. In: Proc. of the Joint International Annual ERCIM Workshops on Principles of Software Evolution (IWPSE) and Software Evolution (Evol), pp. 135–144 (2009)
Pietrantuono, R., Russo, S., Trivedi, K.S.: Software Reliability and Testing Time Allocation: An Architecture-Based Approach. IEEE Trans. on Software Engineering 36(3), 323–337 (2010)
Cinque, M., Cotroneo, D., Pecchia, A.: Event Logs for the Analysis of Software Failures: A Rule-Based Approach. IEEE Trans. on Software Engineering 39(6), 806–821 (2013)
Frattini, F., Ghosh, R., Cinque, M., Rindos, A., Trivedi, K.S.: Analysis of bugs in Apache Virtual Computing Lab. In: 43rd Annual IEEE/IFIP International Conference on Dependable Systems and Networks, DSN (2013)
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Cinque, M., Gaiani, C., De Stradis, D., Pecchia, A., Pietrantuono, R., Russo, S. (2014). On the Impact of Debugging on Software Reliability Growth Analysis: A Case Study. In: Murgante, B., et al. Computational Science and Its Applications – ICCSA 2014. ICCSA 2014. Lecture Notes in Computer Science, vol 8583. Springer, Cham. https://doi.org/10.1007/978-3-319-09156-3_33
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DOI: https://doi.org/10.1007/978-3-319-09156-3_33
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