2011Unpublished venueRequires access

An efficient test data reduction technique through dynamic pattern mixing across multiple fault models

Srinivasulu Alampally, Rakshith Thambehalli Venkatesh, Priyadharshini Shanmugasundaram, Rubin Parekhji, Vishwani D. Agrawal

Open publisher page 49 citations

Abstract

ATPG tool generated patterns are a major component of test data for large SOCs. With increasing sizes of chips, higher integration involving IP cores and the need for patterns targeting multiple fault models for better defect coverage in newer technologies, the issues of adequate coverage and reasonable test data volume and application time dominate the economics of test. We address the problem of generating compact set of test patterns across multiple fault models. Traditional approaches use separate ATPG for each fault models and minimize patterns either during pattern generation through static or dynamic compaction, or after pattern generation by simulating all patterns over all fault models for static compaction. We propose a novel ATPG technique where all fault models of interest are concurrently targeted in a single ATPG run. Patterns are generated in small intervals, each consisting of 16, 32 or 64 patterns. In each interval fault model specific ATPG setups generate separate pattern sets for their respective fault model. An effectiveness criterion then selects exactly one of those pattern sets. The selected set covers untargeted faults that would have required the most additional patterns. Pattern generation intervals are repeated until required coverage for faults of all models of interest is achieved. The sum total of all selected interval pattern sets is the overall test set for the DUT. Experiments on industrial circuits show pattern count reductions of 21% to 68%. The technique is independent of any special ATPG tool or scan compression technique and requires no change or additional support in an existing ATPG system.

About this research paper

What this paper is about

ATPG tool generated patterns are a major component of test data for large SOCs. With increasing sizes of chips, higher integration involving IP cores and the need for patterns targeting multiple fault models for better defect coverage in newer technologies, the issues of adequate coverage and reasonable test data volume and application time dominate the economics of test. We address the problem of generating compact set of test patterns across multiple fault models. Traditional approaches use separate ATPG for each fault models and minimize patterns either during pattern generation through static or dynamic compaction, or after pattern generation by simulating all patterns over all fault models for static compaction. We propose a novel ATPG technique where all fault models of interest are concurrently targeted in a single ATPG run. Patterns are generated in small intervals, each consisting of 16, 32 or 64 patterns. In each interval fault model specific ATPG setups generate separate pattern sets for their respective fault model. An effectiveness criterion then selects exactly one of those pattern sets. The selected set covers untargeted faults that would have required the most additional patterns. Pattern generation intervals are repeated until required coverage for faults of all models of interest is achieved. The sum total of all selected interval pattern sets is the overall test set for the DUT. Experiments on industrial circuits show pattern count reductions of 21% to 68%. The technique is independent of any special ATPG tool or scan compression technique and requires no change or additional support in an existing ATPG system.

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Available abstract

ATPG tool generated patterns are a major component of test data for large SOCs. With increasing sizes of chips, higher integration involving IP cores and the need for patterns targeting multiple fault models for better defect coverage in newer technologies, the issues of adequate coverage and reasonable test data volume and application time dominate the economics of test. We address the problem of generating compact set of test patterns across multiple fault models. Traditional approaches use separate ATPG for each fault models and minimize patterns either during pattern generation through static or dynamic compaction, or after pattern generation by simulating all patterns over all fault models for static compaction. We propose a novel ATPG technique where all fault models of interest are concurrently targeted in a single ATPG run. Patterns are generated in small intervals, each consisting of 16, 32 or 64 patterns. In each interval fault model specific ATPG setups generate separate pattern sets for their respective fault model. An effectiveness criterion then selects exactly one of those pattern sets. The selected set covers untargeted faults that would have required the most additional patterns. Pattern generation intervals are repeated until required coverage for faults of all models of interest is achieved. The sum total of all selected interval pattern sets is the overall test set for the DUT. Experiments on industrial circuits show pattern count reductions of 21% to 68%. The technique is independent of any special ATPG tool or scan compression technique and requires no change or additional support in an existing ATPG system.

Key concepts: Automatic test pattern generation, Fault coverage, Computer science, Fault (geology), Algorithm, Test compression, Reduction (mathematics), Set (abstract data type)

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