Demo Data from EDBT 2026 / reviewers in the wild / expert
Hung-Mao Lin
dblp:45/1530
· DBLP profile ↗
3ranked-venue papers
1as first author
0since 2021 · last 2007
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Systems, architecture and hardware · 3 · 1 first-author
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 · 93% Hardware reliability and fault tolerance · 7% |
Topics — the 4 heaviest of 5, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Electronic design automation › hardware verification and test › design for testability › built-in self-test
BIST diagnosis |
0.1 | 1 | 2007 | Column Parity Row Selection (CPRS) BIST Diagnosis Technique: Modeling and Analysis · IEEE Trans. Computers 2007 |
Electronic design automation › hardware verification and test › design for testability
built-in self-test |
0.1 | 1 | 2007 | Column Parity Row Selection (CPRS) BIST Diagnosis Technique: Modeling and Analysis · IEEE Trans. Computers 2007 |
Electronic design automation
hardware verification and test |
0.1 | 1 | 2007 | Column Parity Row Selection (CPRS) BIST Diagnosis Technique: Modeling and Analysis · IEEE Trans. Computers 2007 |
Electronic design automation › hardware verification and test › fault diagnosis › logic diagnosis
scan chain diagnosis |
0.1 | 1 | 2007 | Column Parity Row Selection (CPRS) BIST Diagnosis Technique: Modeling and Analysis · IEEE Trans. Computers 2007 |
Methods — techniques the papers use, named apart from their topics
error distribution modeling · 0.1column parity row selection · 0.1LFSR-based row selection · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2007 | Cyclic-CPRS : A Diagnosis Technique for BISTed Circuits for Nano-meter TechnologiesabstractA cyclic-CPRS (column parity row selection) technique is presented to diagnose built-in self tested (BISTed) circuits, even in the presence of many unknowns and transient errors. The novel cyclic scan chains retain the transient errors and unknowns in the CUT until they are fully diagnosed. Instead of masking the unknowns, Cyclic-CPRS directly diagnoses the unknowns as if they were errors. Direct diagnosis of unknowns not only eliminates the masking circuitry but also enhances the diagnosis resolution. Experimental results show that Cyclic-CPRS is very successful even in the presence of 10% errors and unknowns. The proposed technique is especially suitable for nanometer technologies, in which transient errors and systematic defects are becoming serious problems. Chun-Yi Lee, Hung-Mao Lin, Fang-Min Wang, Chien-Mo James Li |
ASP-DAC | 2 |
| 2007 | Column Parity Row Selection (CPRS) BIST Diagnosis Technique: Modeling and AnalysisabstractColumn selection row parity (CPRS) diagnosis is an X-tolerant and low aliasing technique that is suitable for the BIST environment. A row selection LFSR randomly selects outputs of multiple scan chains so that unknowns can be tolerated. Column and row parities of selected outputs are observed to solve linear equations for the error positions. Experimental data show that CPRS achieves nearly perfect diagnosis, even in the presence of 1 percent unknowns. CPRS compresses the diagnosis data because only parities of circuit responses, instead of responses themselves, are observed. Two error distribution models (scattered and clustered) are developed and analyzed to show the effectiveness of CPRS. The analytical results are demonstrated to be accurate by more than 10,000 experiments Chien-Mo James Li, Hung-Mao Lin, Fang-Min Wang |
IEEE Trans. Computers | 2 |
| 2005 | Column parity and row selection (CPRS): a BIST diagnosis technique for multiple errors in multiple scan chainsabstractA BIST diagnosis technique is presented to diagnose multiple errors in multiple scan chains. An LFSR randomly selects outputs of multiple scan chains every scan cycle. The column parity and row parity of the selected scan outputs are observed every scan cycle and every scan unload, respectively. Compared with other techniques, which diagnose no more than 15% errors, CPRS correctly diagnoses all errors in the presence of 1% unknowns. The cost of this technique is area overhead and one additional output observed every scan cycle. Hung-Mao Lin, Chien-Mo James Li |
ITC | 1 |