Mathematical statistics (4th ed.)
Mathematical statistics (4th ed.)
Software reliability: measurement, prediction, application
Software reliability: measurement, prediction, application
Information Processing Letters
Partition Testing Does Not Inspire Confidence (Program Testing)
IEEE Transactions on Software Engineering
Analyzing Partition Testing Strategies
IEEE Transactions on Software Engineering
X-Ware Reliability and Availability Modeling
IEEE Transactions on Software Engineering
Estimating the Probability of Failure When Testing Reveals No Failures
IEEE Transactions on Software Engineering
Validation of ultrahigh dependability for software-based systems
Communications of the ACM
New statistics for demand-based software testing
Information Processing Letters
Art of Software Testing
Are We Testing for True Reliability?
IEEE Software
Planning and Certifying Software System Reliability
IEEE Software
The Infeasibility of Quantifying the Reliability of Life-Critical Real-Time Software
IEEE Transactions on Software Engineering
Structural Software Reliability Estimation
SAFECOMP '99 Proceedings of the 18th International Conference on Computer Computer Safety, Reliability and Security
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A statistical software testing model is proposed in which white box factors have a role. The model combines test adequacy notions with statistical analysis, and in so doing provides a rudimentary treatment of dependencies between test results caused by the execution of common code during the tests. The model is used to estimate the probability of failure on demand for software performing safety shutdown functions on large plants and concerns the case where extensive test results are available on the latest version of the software, none of which have resulted in software failure. According to the model, there are circumstances in which some current statistical models for dynamic software testing are too conservative, and others are not conservative, depending on the software architecture.