DocumentCode
786811
Title
SPIRIT: a highly robust combinational test generation algorithm
Author
Gizdarski, Emil ; Fujiwara, Hideo
Author_Institution
Synopsys Inc., Mountain View, CA, USA
Volume
21
Issue
12
fYear
2002
fDate
12/1/2002 12:00:00 AM
Firstpage
1446
Lastpage
1458
Abstract
In this paper, an efficient test pattern generation (TPG) algorithm for combinational circuits based on the Boolean satisfiability method (SAT) is presented. The authors propose a new data structure for the complete implication graph that increases the precision of implication process. Next, they examine approaches like a single-cone processing, single path-oriented propagation, and backward justification and show that they are efficient to improve robustness of TPG algorithms. Finally, the authors propose efficient techniques and heuristics for these approaches. The resultant automatic test pattern generation system, called SPIRIT (Satisfiability Problem Implementation for Redundancy Identification and Test generation), combines the flexibility of the SAT-based TPG algorithms with the efficiency of the structural TPG algorithms. Experimental results demonstrate the robustness of the proposed TPG algorithm. Without fault simulation, SPIRIT is able to achieve 100% fault efficiency for a large set of benchmark circuits in a reasonable amount of time.
Keywords
automatic test pattern generation; combinational circuits; computability; logic testing; redundancy; Boolean satisfiability; SPIRIT; backward justification; combinational circuit; data structure; dynamic learning; implication graph; redundancy identification; single path-oriented propagation; single-cone processing; static learning; test pattern generation algorithm; Automatic test pattern generation; Automatic testing; Circuit faults; Circuit testing; Combinational circuits; Data structures; Redundancy; Robustness; System testing; Test pattern generators;
fLanguage
English
Journal_Title
Computer-Aided Design of Integrated Circuits and Systems, IEEE Transactions on
Publisher
ieee
ISSN
0278-0070
Type
jour
DOI
10.1109/TCAD.2002.804387
Filename
1097864
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