VLDB 2026 Research / reviewers in the wild / expert
Akasaka Isami
dblp:332/6209
· 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 |
Services computing and microservices · 38% Requirements engineering and software design · 38% Program analysis · 23% |
Topics — the 4 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Requirements engineering and software design › software architecture › software architecture evolution
architectural decay |
0.6 | 1 | 2022 | Trace analysis based microservice architecture measurement · ESEC/SIGSOFT FSE 2022 |
Services computing and microservices
microservice architecture |
0.6 | 1 | 2022 | Trace analysis based microservice architecture measurement · ESEC/SIGSOFT FSE 2022 |
Program analysis › dynamic analysis › trace analysis
execution trace analysis |
0.2 | 1 | 2022 | Trace analysis based microservice architecture measurement · ESEC/SIGSOFT FSE 2022 |
Program analysis › dynamic analysis
trace analysis |
0.2 | 1 | 2022 | Trace analysis based microservice architecture measurement · ESEC/SIGSOFT FSE 2022 |
Methods — techniques the papers use, named apart from their topics
trace data modeling · 0.6architectural metrics · 0.6
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2022 | Trace analysis based microservice architecture measurementabstractMicroservice architecture design highly relies on expert experience and may often result in improper service decomposition. Moreover, a microservice architecture is likely to degrade with the continuous evolution of services. Architecture measurement is thus important for the long-term evolution of microservice architectures. Due to the independent and dynamic nature of services, source code analysis based approaches cannot well capture the interactions between services. In this paper, we propose a trace analysis based microservice architecture measurement approach. We define a trace data model for microservice architecture measurement, which enables fine-grained analysis of the execution processes of requests and the interactions between interfaces and services. Based on the data model, we define 14 architectural metrics to measure the service independence and invocation chain complexity of a microservice system. We implement the approach and conduct three case studies with a student course project, an open-source microservice benchmark system, and three industrial microservice systems. The results show that our approach can well characterize the independence and invocation chain complexity of microservice architectures and help developers to identify microservice architecture issues caused by improper service decomposition and architecture degradation. Xin Peng 0001, Chenxi Zhang 0003, Akasaka Isami, Yunna Cui |
ESEC/SIGSOFT FSE | 4 |