Demo Data from EDBT 2026 / reviewers in the wild / expert
K. Mohanram
dblp:91/6363
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2000
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Systems, architecture and hardware · 1
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% | |
| Theoretical computer science
1 paper |
Automated reasoning and model checking · 100% |
Topics — the 3 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Electronic design automation › logic synthesis
boolean function representation |
0.0 | 1 | 2000 | Analysis of composition complexity and how to obtain smaller canonical graphs · DAC 2000 |
Electronic design automation
hardware verification and test |
0.0 | 1 | 2000 | Analysis of composition complexity and how to obtain smaller canonical graphs · DAC 2000 |
Electronic design automation › logic synthesis › switching theory
finite state machine analysis |
0.0 | 1 | 2000 | Analysis of composition complexity and how to obtain smaller canonical graphs · DAC 2000 |
Methods — techniques the papers use, named apart from their topics
dynamic partitioning · 0.1composition · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2000 | Analysis of composition complexity and how to obtain smaller canonical graphsabstractWe discuss an open problem in ROBDD construction using composition and prove that the worst case complexity of the construction is truly cubic. With this insight we show that the process of composition naturally leads to construction of (even exponentially) compact partitioned-OBDDs (POBDDs)[17]. Our algorithm which incorporates dynamic partitioning, leads to the most general (and compact) form of POBDDs - graphs with multiple root variables. To show our algorithm is robust and practical, we have analyzed some well known problems in Boolean function representation, verification and finite state machine analysis where our approach generates graphs which are even orders of magnitude smaller. Jawahar Jain, K. Mohanram, Dinos Moundanos, Ingo Wegener, Yuan Lu 0004 |
DAC | 2 |