Evaluation in built-in self-test
Date
2017-08-21
Authors
Zhang, Shujian
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Abstract
This dissertation addresses two major issues associated with a built-in self-test environment: (1) how to measure whether a given test vector generator is suitable for testing faults with sequential behavior, and (2) how to measure the safety of self-checking circuits.
Measuring the two-vector transition capability for a given test vector generator is a key to the selection of the generators for stimulating sequential faults. The dissertation studies general properties for the transitions and presents a novel, comprehensive analysis for the linear feedback shift registers and the linear hybrid cellular automata. As a result, the analysis solves the open problem as to “how to properly separate the inputs when the LHCA-based generator is used for detecting delay faults”.
In general, a self-checking circuit has additional hardware redundancy than the original circuit and as a result, the self-checking circuit may have a higher failure rate than the original one. The dissertation proposes a fail-safe evaluation to predict the probability of the circuit not being in the fail-state. Compared with existing evaluation methods, the fail-safe evaluation is more practical because it estimates the safety of the circuit, which is decreasing as time goes on, instead of giving a constant probability measure.
Various other results about improving fault coverage for transition delay faults and testing in macro-based combinational circuits are derived as well.
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Keywords
Generators (Computer programs), Sequential processing (Computer science)