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Title:Techniques for sequential circuit automatic test generation
Author(s):Niermann, Thomas Michael
Doctoral Committee Chair(s):Patel, Janak H.
Department / Program:Electrical and Computer Engineering
Discipline:Electrical and Computer Engineering
Degree Granting Institution:University of Illinois at Urbana-Champaign
Subject(s):Engineering, Electronics and Electrical
Abstract:Test pattern generation has progressed to a stage at which automatic test generation gives satisfactory fault coverage on almost any combinational circuit. However, the same is not true of sequential circuit test generation. While scan-based approaches can convert the sequential circuit into a combinational circuit for testing purposes, the cost of a complete scan design methodology can be prohibitive in both area overhead and performance degradation. Therefore, an efficient sequential circuit test generation system which generates tests for all detectable faults and identifies all untestable faults in the original design is necessary. The information on untestable faults could be used to add minimal design for test hardware to make these faults testable.
This thesis presents several new techniques to improve the performance of sequential circuit test generators. Among the concepts presented are unnecessary state elimination, and the use of fault simulation knowledge to increase test coverage during a second phase of test generation, a targeted D element technique for D propagation, and the use of the good circuit state knowledge. The concepts presented in the thesis were implemented and tested on the ISCAS sequential benchmark circuits.
This thesis presents an improved fault simulation algorithm based on a combination of the parallel, concurrent and differential fault simulation algorithms. This fault simulator is shown to require much less memory while being 6 to 67 times faster than a traditional concurrent fault simulator.
Issue Date:1991
Rights Information:Copyright 1991 Niermann, Thomas Michael
Date Available in IDEALS:2011-05-07
Identifier in Online Catalog:AAI9136684
OCLC Identifier:(UMI)AAI9136684

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