Demo Data from VLDB 2026 / reviewers in the wild / expert
Guoqiang Duan
dblp:324/8228
· 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
Software engineering, systems software and programming languages · 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.
| Software engineering, system software, and programming languages
1 paper |
Debugging and program repair · 100% | |
| Computer architecture, parallel and distributed computing, and storage systems
1 paper |
Cloud and datacenter computing · 50% Electronic design automation · 50% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Debugging and program repair
fault localization |
0.6 | 1 | 2022 | Actionable and interpretable fault localization for recurring failures in online service systems · ESEC/SIGSOFT FSE 2022 |
Electronic design automation › hardware verification and test
fault diagnosis |
0.2 | 1 | 2022 | Actionable and interpretable fault localization for recurring failures in online service systems · ESEC/SIGSOFT FSE 2022 |
Cloud and datacenter computing › datacenter services
online service systems |
0.2 | 1 | 2022 | Actionable and interpretable fault localization for recurring failures in online service systems · ESEC/SIGSOFT FSE 2022 |
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2022 | Actionable and interpretable fault localization for recurring failures in online service systemsabstractFault localization is challenging in an online service system due to its monitoring data's large volume and variety and complex dependencies across/within its components (e.g., services or databases). Furthermore, engineers require fault localization solutions to be actionable and interpretable, which existing research approaches cannot satisfy. Therefore, the common industry practice is that, for a specific online service system, its experienced engineers focus on localization for recurring failures based on the knowledge accumulated about the system and historical failures. More specifically, 1) they can identify the underlying root causes and take mitigation actions when pinpointing a group of indicative metrics on the faulty component; 2) their diagnosis knowledge is roughly based on how one failure might affect the components in the whole system. Zeyan Li 0001, Nengwen Zhao, Mingjie Li 0005, Xianglin Lu, Dongdong Chang, Xiaohui Nie, Wenchi Zhang, Kaixin Sui, Guoqiang Duan, Dan Pei |
ESEC/SIGSOFT FSE | 13 |