Functional program testing and analysis
Functional program testing and analysis
An Applicable Family of Data Flow Testing Criteria
IEEE Transactions on Software Engineering
Evaluation of safety-critical software
Communications of the ACM
Partition Testing Does Not Inspire Confidence (Program Testing)
IEEE Transactions on Software Engineering
IEEE Transactions on Software Engineering
A Markov Chain Model for Statistical Software Testing
IEEE Transactions on Software Engineering
Planning and Certifying Software System Reliability
IEEE Software
Reliability Testing of Rule-Based Systems
IEEE Software
On some reliability estimation problems in random and partition testing
IEEE Transactions on Software Engineering
High quality behavioral verification using statistical stopping criteria
Proceedings of the conference on Design, automation and test in Europe
Fast Anti-Random (FAR) Test Generation to Improve the Quality of Behavioral Model Verification
Journal of Electronic Testing: Theory and Applications
Statistical Constraints and Verification
Object Modeling with the OCL, The Rationale behind the Object Constraint Language
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
Test data variance as a test quality measure: exemplified for TTCN-3
TestCom'07/FATES'07 Proceedings of the 19th IFIP TC6/WG6.1 international conference, and 7th international conference on Testing of Software and Communicating Systems
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Coverage is often used to determine when unit modules have been sufficiently tested. It is difficult to apply the same approach to whole systems. An additional problem is that coverage has no obvious reliability interpretation. A form of coverage called statistical coverage is described that solves some of the problems of systems level coverage and which also has a reliability interpretation. Statistical coverage is based on ideas from statistical testing. Statistical testing is reviewed and new results are introduced that are needed for statistical coverage, and which can also be applied to statistical testing.