Demo Data from EDBT 2026 / reviewers in the wild / expert
Amar Agrawal
dblp:23/4403
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2019
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Computer networks · 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 networks
1 paper |
Network management and operations · 100% | |
| Computer architecture, parallel and distributed computing, and storage systems
1 paper |
Cloud and datacenter computing · 100% |
Topics — the 2 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Network management and operations
network verification |
0.4 | 1 | 2019 | Validating datacenters at scale · SIGCOMM 2019 |
Cloud and datacenter computing › datacenter network
datacenter network operations |
0.1 | 1 | 2019 | Validating datacenters at scale · SIGCOMM 2019 |
Methods — techniques the papers use, named apart from their topics
formal methods · 0.8automated theorem proving · 0.8
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2019 | Validating datacenters at scaleabstractWe describe our experiences using formal methods and automated theorem proving for network operation at scale. The experiences are based on developing and applying the SecGuru and RCDC (Reality Checker for Data Centers) tools in Azure. SecGuru has been used since 2013 and thus, is arguably a pioneering industrial deployment of network verification. SecGuru is used for validating ACLs and more recently RCDC checks forwarding tables at Azure scale. A central technical angle is that we use local contracts and local checks, that can be performed at scale in parallel, and without maintaining global snapshots, to validate global properties of datacenter networks. Specifications leverage declarative encodings of configurations and automated theorem proving for validation. We describe how intent is automatically derived from network architectures and verification is incorporated as prechecks for making changes, live monitoring, and for evolving legacy policies. We document how network verification, grounded in architectural constraints, can be integral to operating a reliable cloud at scale. Karthick Jayaraman, Nikolaj S. Bjørner, Jitendra Padhye, Amar Agrawal, Ashish Bhargava, Paul-Andre C. Bissonnette, Shane Foster, Andrew Helwer, Mark Kasten, Anup Namdhari, Haseeb Niaz, Aniruddha Parkhi, Hanukumar Pinnamraju, Adrian Power, Neha Milind Raje, Parag Sharma |
SIGCOMM | 4 |