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Michael Bienek

dblp:64/2904 · DBLP profile ↗
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2ranked-venue papers
0as first author
0since 2021 · last 2009
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Systems, architecture and hardware · 2

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer architecture, parallel and distributed computing, and storage systems
1 paper
Electronic design automation · 100%

Topics — the 4 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Electronic design automation › hardware verification and test
fault coverage
0.112009
Deviation-Based LFSR Reseeding for Test-Data Compression · IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 2009
Electronic design automation
hardware verification and test
0.112009
Deviation-Based LFSR Reseeding for Test-Data Compression · IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 2009
Electronic design automation › hardware verification and test › test data compression
LFSR reseeding
0.112009
Deviation-Based LFSR Reseeding for Test-Data Compression · IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 2009
Electronic design automation › hardware verification and test
test data compression
0.112009
Deviation-Based LFSR Reseeding for Test-Data Compression · IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 2009

Methods — techniques the papers use, named apart from their topics

seed selection · 0.1output deviation metric · 0.1linear feedback shift register reseeding · 0.1
YearPublicationVenuePosition
2009 Deviation-Based LFSR Reseeding for Test-Data Compression
abstract
Linear feedback shift register (LFSR) reseeding forms the basis for many test-compression solutions. A seed can be computed for each test cube by solving a system of linear equations based on the feedback polynomial of the LFSR. Despite the availability of numerous LFSR-reseeding-based compression methods in the literature, relatively little is known about the effectiveness of these seeds for unmodeled defects, particularly since there are often several candidate seeds for a test cube. We use the recently proposed output deviation measure of the resulting patterns as a metric to select appropriate LFSR seeds. Experimental results are reported using test patterns for stuck-at and transition faults derived from selected seeds for the ISCAS-89 and the IWLS-05 benchmark circuits. These patterns achieve higher coverage for transition and stuck-open faults than patterns obtained using other seed-generation methods for LFSR reseeding. Given a pattern pair (p1,p2) for transition faults, we also examine the transition-fault coverage for launch on capture by usingp1andp2to separately compute output deviations. Results show thatp1tends to be better when there is a high proportion of do-not-care bits in the test cubes, whilep2is a more appropriate choice when the transition-fault coverage is high.
Zhanglei Wang, Hongxia Fang, Krishnendu Chakrabarty, Michael Bienek
IEEE Trans. Comput. Aided Des. Integr. Circuits Syst.4
2007 A Seed-Selection Method to Increase Defect Coverage for LFSR-Reseeding-Based Test Compression
abstract
LFSR reseeding forms the basis for many test compression solutions. A seed can be computed for each test cube by solving a system of linear equations based on the feedback polynomial of the LFSR. Despite the availability of numerous LFSR-reseeding-based compression methods in the literature, relatively little is known about the effectiveness of these seeds for unmodeled defects. We use the recently proposed output deviation measure of the resulting patterns as a metric to select appropriate LFSR seeds. Experimental results are reported using test patterns for stuck-at faults derived from selected seeds. These patterns achieve higher coverage for stuck-open and transition faults than patterns obtained using other methods.
Zhanglei Wang, Krishnendu Chakrabarty, Michael Bienek
ETS3