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» Using Model Counting to Find Optimal Distinguishing Tests
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AAAI
2010
14 years 10 months ago
Computing Cost-Optimal Definitely Discriminating Tests
The goal of testing is to discriminate between multiple hypotheses about a system--for example, different fault diagnoses--by applying input patterns and verifying or falsifying t...
Anika Schumann, Jinbo Huang, Martin Sachenbacher
CN
1999
100views more  CN 1999»
14 years 9 months ago
Testing protocols modeled as FSMs with timing parameters
An optimization method is introduced for generating minimum-length test sequences taking into account timing constraints for FSM models of communication protocols. Due to active t...
M. Ümit Uyar, Mariusz A. Fecko, Adarshpal S. ...
GECCO
2005
Springer
113views Optimization» more  GECCO 2005»
15 years 3 months ago
Search-based mutation testing for Simulink models
The efficient and effective generation of test-data from high-level models is of crucial importance in advanced modern software engineering. Empirical studies have shown that muta...
Yuan Zhan, John A. Clark
DATE
1998
IEEE
106views Hardware» more  DATE 1998»
15 years 1 months ago
March Tests for Word-Oriented Memories
Most memory test algorithms are optimized tests for a particular memory technology and a particular set of fault models, under the assumption that the memory is bit-oriented; i.e....
A. J. van de Goor, Issam B. S. Tlili
COCOA
2010
Springer
14 years 7 months ago
Bounds for Nonadaptive Group Tests to Estimate the Amount of Defectives
The classical and well-studied group testing problem is to find d defectives in a set of n elements by group tests, which tell us for any chosen subset whether it contains defectiv...
Peter Damaschke, Azam Sheikh Muhammad