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Zhuqi Jin

dblp:304/2580 · DBLP profile ↗
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2ranked-venue papers
0as first author
2since 2021 · last 2023
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Software engineering, systems software and programming languages · 2 · 2 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
2 papers
Debugging and program repair · 49% Software maintenance and evolution · 37% Program analysis · 15%
Computer architecture, parallel and distributed computing, and storage systems
2 papers
Distributed systems · 100%

Topics — the 4 heaviest of 5, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Debugging and program repair
performance debugging		 0.712023
Relational Debugging - Pinpointing Root Causes of Performance Problems · OSDI 2023
Distributed systems
root cause analysis		 0.712023
Relational Debugging - Pinpointing Root Causes of Performance Problems · OSDI 2023
Software maintenance and evolution
software updates		 0.512021
Understanding and Detecting Software Upgrade Failures in Distributed Systems · SOSP 2021
Distributed systems
fault tolerance		 0.512021
Understanding and Detecting Software Upgrade Failures in Distributed Systems · SOSP 2021

Methods — techniques the papers use, named apart from their topics

empirical study · 1.0
YearPublicationVenuePosition
2023 Relational Debugging - Pinpointing Root Causes of Performance Problems
Xiang Ren 0003, Sitao Wang, Zhuqi Jin, David Lion, Adrian Chiu, Tianyin Xu, Ding Yuan 0004
 OSDI3
2021 Understanding and Detecting Software Upgrade Failures in Distributed Systems
abstract
Upgrade is one of the most disruptive yet unavoidable maintenance tasks that undermine the availability of distributed systems. Any failure during an upgrade is catastrophic, as it further extends the service disruption caused by the upgrade. The increasing adoption of continuous deployment further increases the frequency and burden of the upgrade task. In practice, upgrade failures have caused many of today's high-profile cloud outages. Unfortunately, there has been little understanding of their characteristics.
Yongle Zhang 0007, Zhuqi Jin, Utsav Sethi, Kirk Rodrigues, Shan Lu 0001, Ding Yuan 0004
 SOSP3