Certifying the reliability of software
IEEE Transactions on Software Engineering
Functional program testing and analysis
Functional program testing and analysis
Software reliability: measurement, prediction, application
Software reliability: measurement, prediction, application
A formal approach to software error removal
Journal of Systems and Software
Evaluation of safety-critical software
Communications of the ACM
Software safety in embedded computer systems
Communications of the ACM
Art of Software Testing
Stopping Rules for the Operational Testing of Safety-Critical Software
FTCS '95 Proceedings of the Twenty-Fifth International Symposium on Fault-Tolerant Computing
High quality behavioral verification using statistical stopping criteria
Proceedings of the conference on Design, automation and test in Europe
Stopping Criteria Comparison: Towards High Quality Behavioral Verification
ISQED '01 Proceedings of the 2nd International Symposium on Quality Electronic Design
Achieving the Quality of Verification for Behavioral Models with Minimum Effort
ISQED '00 Proceedings of the 1st International Symposium on Quality of Electronic Design
EUC'06 Proceedings of the 2006 international conference on Embedded and Ubiquitous Computing
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In this work a binary Markov process model is proposed for random testing for software. This model is suggested to replace the standard binomial distribution model, which is based on the easily-violated assumption of test runs being statistically independent of each other. In addition to a general result on the probability of having any specific number of software failures during testing, practical implications of the new model are also discussed. In particular, we demonstrate that in general the effect of possible correlation between test runs cannot be ignored in estimating software reliability.