The art of computer programming, volume 2 (3rd ed.): seminumerical algorithms
The art of computer programming, volume 2 (3rd ed.): seminumerical algorithms
The Design and Analysis of Computer Algorithms
The Design and Analysis of Computer Algorithms
Analysis of polynomial approximation algorithms for constraint expressions
Proceedings of the 6th GI-Conference on Theoretical Computer Science
Monte-carlo methods for estimating system reliability
Monte-carlo methods for estimating system reliability
On computing optimized input probabilities for random tests
DAC '87 Proceedings of the 24th ACM/IEEE Design Automation Conference
A method for generating weighted random test pattern
IBM Journal of Research and Development
Parameterizing random test data according to equivalence classes
Proceedings of the 2nd international workshop on Random testing: co-located with the 22nd IEEE/ACM International Conference on Automated Software Engineering (ASE 2007)
Fault detection effectiveness of weighted random patterns
ITC'88 Proceedings of the 1988 international conference on Test: new frontiers in testing
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Random testing uses random inputs to test digital circuits. A major problem in random testing is the cost to compute the test length which is required for achieving an acceptable fault coverage. Different input distributions on the random inputs produce different fault detection probabilities. Therefore parameterized input distributions are analyzed and analytical methods are given for computing the fault coverage as a function of the parameters. The parameters are chosen so that the fault detection probability is maximized and the test pattern length is minimized. This analytical method of analyzing random test patterns tends to be faster than fault simulation.