Demo Data from EDBT 2026 / reviewers in the wild / expert
Puneet Nemade
dblp:334/3742
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2022
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Systems, architecture and hardware · 1 · 1 since 2021
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 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Electronic design automation › hardware verification and test › debugging
bug localization |
0.6 | 1 | 2022 | Aries: A Semiformal Technique for Fine-Grained Bug Localization in Hardware Designs · IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 2022 |
Electronic design automation
hardware verification and test |
0.6 | 1 | 2022 | Aries: A Semiformal Technique for Fine-Grained Bug Localization in Hardware Designs · IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 2022 |
Electronic design automation
model checking |
0.2 | 1 | 2022 | Aries: A Semiformal Technique for Fine-Grained Bug Localization in Hardware Designs · IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 2022 |
Methods — techniques the papers use, named apart from their topics
model checking · 0.6binning · 0.6assertion mining · 0.6
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2022 | Aries: A Semiformal Technique for Fine-Grained Bug Localization in Hardware DesignsabstractEffective bug localization during verification is a challenging step in the development cycle of complex hardware designs. While meeting different coverage goals is possible in the verification process, yet bug localization cannot be directly related to such goals. We propose a two-step methodology to achieve fine-grained design bug localization. First, we obtain multiple error traces based on a failing property. Starting from an initial error trace, we employ model checking to generate supportive error traces that are utilized to mine important assertions. In the second step, we utilize these assertions for fine-grained design bug localization. The mapping of the assertions leads to specific regions in register transfer level descriptions that are highly probable to be the root cause of the design bug. Specifically, we devise a binning methodology to categorize multiple suspects in different bins that need to be investigated by the design engineer for arriving at the correction for corresponding bugs. Experiments on multiple designs illustrate the efficacy of the proposed methodology in comparison to previous work and state-of-the-art industrial tool. Binod Kumar 0001, Vineesh V. S., Puneet Nemade, Masahiro Fujita 0004 |
IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. | 3 |