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Digital Systems Testing and Testable Design
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TLDR
The new edition of Breuer-Friedman's Diagnosis and Reliable Design ofDigital Systems offers comprehensive and state-ofthe-art treatment of both testing and testable design.Abstract:
For many years, Breuer-Friedman's Diagnosis and Reliable Design ofDigital Systems was the most widely used textbook in digital system testing and testable design. Now, Computer Science Press makes available a new and greativ expanded edition. Incorporating a significant amount of new material related to recently developed technologies, the new edition offers comprehensive and state-ofthe-art treatment of both testing and testable design.read more
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Proceedings ArticleDOI
On generating high quality tests for transition faults
TL;DR: Experimental results show that POTENT generates higher quality transition fault test sets than the conventional test generation method.
Proceedings ArticleDOI
Multiple error diagnosis based on xlists
TL;DR: This paper presents multiple error diagnosis algorithms to overcome two significant problems associated with current error diagnosis techniques targeting large circuits: their use of limited error models and a lack of solutions that scale well for multiple errors.
Proceedings ArticleDOI
On Compacting Test Response Data Containing Unknown Values
TL;DR: In this article, the Block Compactors are proposed as an instance of finite memory compactors, which can generate a signature of response data in several scan cycles and provide better test quality and higher data compaction than earlier works on test response compactors.
Book ChapterDOI
Satisfiability on reconfigurable hardware
Miron Abramovici,Daniel G. Saab +1 more
TL;DR: A new approach to implement satisfiability (SAT) on reconfigurable hardware that relies on fine-grain massive parallelism and a major novel feature is that both the next variable to assign and its value are dynamically determined by a backward model traversal done in hardware.
Proceedings ArticleDOI
Learning from BDDs in SAT-based bounded model checking
TL;DR: This paper explores the use of learning from BDDs, where learned clauses generated by BDD-based analysis are added to the SAT solver, to supplement its other learning mechanisms.