Test vectors reductoin for integrated circuit testing using horizontal hamming distance
In testing digital combinational logic for stuck-at faults, it is required to determine the most appropriate test sequence needed to detect the required number of possible faults. The exhaustive test pattern generation method is the simplest approach to implement as it produces test patterns consist...
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| Main Author: | |
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| Format: | Thesis |
| Language: | English |
| Published: |
2016
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| Subjects: | |
| Online Access: | http://eprints.utm.my/id/eprint/77590/1/ArbabAlamgirMFKE2016.pdf |
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| Summary: | In testing digital combinational logic for stuck-at faults, it is required to determine the most appropriate test sequence needed to detect the required number of possible faults. The exhaustive test pattern generation method is the simplest approach to implement as it produces test patterns consisting of all possible input combinations of the circuit under test. However, a consequence of this approach is that it results in a large test set when the number of circuit inputs is large. This can take an unnecessarily long time to apply on the circuit under test as during the test process, only a small fraction of all possible test vectors is actually required to produce high percentage of fault coverage. As an alternative, random test pattern generation applies a random set of test patterns which can be used to reduce the number of test patterns compared to exhaustive test. However, both test pattern generation approaches generate unnecessary test vectors to apply to the circuit as multiple patterns typically detect the same fault. Antirandom testing on the other hand ensures that the identified test vectors to use do not detect the same fault by introducing the concept of Hamming distance between test vectors and this distance is be maximized. This results in a reduction in the number of required test vectors when compared to an exhaustive test. However, the algorithm for Antirandom test vector generation is computation intensive and vague in its definition when there are more than one possible next test vectors. In this study, efficient calculation of Hamming distance has been proposed, moreover the choice of the next test vector is addressed by using the proposed Horizontal Hamming distance method which has not yet been explored. The approach effectively detects faults at a much faster rate and produces a much higher fault coverage than the existing Antirandom method. |
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