Demo Data from EDBT 2026 / reviewers in the wild / expert
Kevin Qiao
dblp:317/1933
· 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% | |
| Software engineering, system software, and programming languages
1 paper |
Program analysis · 100% | |
| Computer architecture, parallel and distributed computing, and storage systems
1 paper |
Performance modeling and evaluation · 100% |
Topics — the 2 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Program analysis
symbolic execution |
0.4 | 1 | 2019 | Efficient systematic testing of network protocols with temporal uncertain events · INFOCOM 2019 |
Performance modeling and evaluation › simulation › communication system simulation
network simulation |
0.1 | 1 | 2019 | Efficient systematic testing of network protocols with temporal uncertain events · INFOCOM 2019 |
Methods — techniques the papers use, named apart from their topics
symbolic execution · 1.1interval branching · 1.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2019 | Efficient systematic testing of network protocols with temporal uncertain eventsabstractThe correctness of network protocol implementations is difficult to test mainly because of the temporal uncertain nature of network events. In order to test the correctness of a network protocol implementation using network simulators, we need to systematically simulate the behavior of the network protocol under all possible cases of temporal uncertain events, which is very time consuming. The recently proposed Symbolic Execution based Interval Branching (SEIB) simulates a group of uncertain cases together in a single simulation branch, and thus is more efficient than brute force testing. In this paper, we argue that the efficiency of SEIB could be further exponentially improved by eliminating unnecessary comparisons of the event timestamps. Specifically, we summarize and present three general types of unnecessary comparisons when SEIB is applied to a general network simulator, and then correspondingly propose three novel techniques to eliminate them. Our extensive simulations show that our techniques can improve the efficiency of SEIB by several orders of magnitude, such as from days to minutes. Minh Vu 0003, Lisong Xu, Sebastian G. Elbaum, Wei Sun 0044, Kevin Qiao |
INFOCOM | 5 |