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Qiankang Mao

dblp:349/5030 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2023
0009-0007-0637-3659ORCID · reported

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

Computer networks · 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
Performance modeling and evaluation · 100%
Software engineering, system software, and programming languages
1 paper
Empirical software engineering · 100%

Topics — the 2 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Performance modeling and evaluation
performance monitoring
0.712023
Demo: Domino: A High-Precision Performance Monitoring and Analysis Platform for Client Applications · MobiSys 2023
Empirical software engineering › software analytics
performance regression detection
0.212023
Demo: Domino: A High-Precision Performance Monitoring and Analysis Platform for Client Applications · MobiSys 2023

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

trace analysis · 1.3
YearPublicationVenuePosition
2023 Demo: Domino: A High-Precision Performance Monitoring and Analysis Platform for Client Applications
abstract
As client applications evolve with new businesses and features, new performance overheads may be introduced. For example, in the application startup scenario, the initialization of newly connected SDKs and the addition of disk access operations on the main thread can increase the startup time, leading to a decline in user experience. Traditional performance testing detects application indicators through automated testing, video frame splitting, or log tracking, but due to fluctuations in the offline environment, test results often fluctuate, and confidence is not high. To optimize performance in a more refined way, it is necessary to not only evaluate performance through indicators but also to pinpoint the cause of the problem accurately. Domino is a client-side performance testing platform based on Trace analysis. In this demonstration, we will provide two versions of AndroidDemo applications, simulate several performance issues, and use the Domino platform to more precisely locate performance problems and provide development repair suggestions.
Dongping Cao, Run Kang, Qiankang Mao
MobiSys6