Abstract
Software developed for mission-critical systems employ rigorous verification and validation techniques to achieve good quality. Traditional software reliability models use execution time during software testing for reliability estimation. Although testing duration is an important factor in reliability, it is possible to improve the accuracy of estimation by factoring other techniques that influence the final software quality. In this paper, we propose a novel method to utilize the effectiveness of the verification and validation process to predict reliability. The main idea is that failure detection is not only related to the time that the software experiences under testing, but also to different levels of review rigors the software has undergone. Our experimental results with multi-version software used in mission-critical systems show our model achieves substantial reliability estimate.
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References
RTCA, Inc., December 1992, RTCA/DO-178B, Software Considerations in Airborne Systems and Equipment Certification, Washington, DC
D.R. Wallace, R.U. Fujii, Software Verification and Validation: An Overview. IEEE Software (May, 1989)
I. Musa, K. Okumoto, Software Reliability Engineering: Measurement, Prediction, Application (McGraw Hill, 1987)
A.L. Goel, Software reliability models: assumptions, limitations, and applicability. IEEE Trans. Software Eng. 11(12), 1411–1423 (1985)
M.R. Lyu (ed.), Handbook of Software Reliability Engineering (McGraw Hill, 1996)
Y.K. Maliya, N. Li, J. Bieman, R. Karcich, Software reliability growth with test coverage. IEEE Trans. Reliab. 51(4), 420–426 (2002)
M.H. Chen, M.R. Lyu, Effect of code coverage on software reliability measurement. IEEE Trans. Reliab. 50(1), 165 (2001)
C. Senthil Kumar, Hybrid approach for estimation of software reliability in nuclear safety systems, in AERB Newsletter, vol. 26, No. 1 (June 2013)
M. Kersken, The role of static analysis in software reliability assessment, in 11th Advances in Reliability Technology Symposium, pp 169–182 (1990)
N.E. Rallis, Z.F. Landsdowne, Reliability estimation for a software system with sequential independent reviews. IEEE Trans. Software Eng. 27(12), 1057 (2001)
J. Jheng, N. Nagappan, J.P. Hudepohl, M.A. Vouk, On the value of static analysis on fault detection of software. IEEE Trans. Software Eng. 32(4), 240 (2006)
W.W. Schilling, M. Alam, Modeling the reliability of existing software using static analysis, in Proceedings of the. IEEE International Conference on Electro/Information Technology, pp. 366–371 (May 2006)
P. Emanuelsson, U. Nilsson, A comparative study of industrial static analysis tools, in Technical reports in Computer and Information Science (Linkoping University, Sweden, January 2008)
N. Rutar, C.B. Almazan, J.S. Foster, A comparison of bug finding tools for java, in Proceedings if the ISSRE, pp. 245–256 (2004)
H. Koziolek, Operational profiles for software reliability, in Seminar of Dependability Engineering (Carl von Ossietzky University of Oldenburg, July 2005)
A. Das, M. Venkat, Missile software early reliability prediction using fuzzy logic, in Proceedings of the DRDO Technical Seminar (2008)
LDRA. http://www.ldra.com
Coverity: Software Testing and Static Analysis Tools. http://www.coverity.com
Klocwork: Source Code Analysis Tools for Security & Reliability. http://www.klocwork.com
Astree Runtime Error Analyzer-AbsInt. https://www.absint.com/astree
M. Rausand, A. Hoyland, System Reliability Theory Models, Statistical Methods, and Applications, 2nd edn. (Wiley Series)
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Das, A., Tiwari, M.K., Nayak, D.R. (2020). Software Reliability Growth as an Offshoot of Verification and Validation Process. In: Varde, P., Prakash, R., Vinod, G. (eds) Reliability, Safety and Hazard Assessment for Risk-Based Technologies. Lecture Notes in Mechanical Engineering. Springer, Singapore. https://doi.org/10.1007/978-981-13-9008-1_21
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DOI: https://doi.org/10.1007/978-981-13-9008-1_21
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