Demo Data from SIGIR 2026 / reviewers in the wild / expert
Runchao Wu
dblp:319/2693
· DBLP profile ↗
2ranked-venue papers
0as first author
2since 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 · 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 |
Software testing · 100% | |
| Computer architecture, parallel and distributed computing, and storage systems
1 paper |
Cloud and datacenter computing · 100% |
Topics — the 6 heaviest of 7, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Software testing › API testing
REST API testing |
1.1 | 2 | 2022 | Morest: Industry Practice of Automatic RESTful API Testing · ASE 2022 Morest: Model-based RESTful API Testing with Execution Feedback · ICSE 2022 |
Software testing
API testing |
0.6 | 1 | 2022 | Morest: Industry Practice of Automatic RESTful API Testing · ASE 2022 |
Software testing › test generation
automated test generation |
0.6 | 1 | 2022 | Morest: Industry Practice of Automatic RESTful API Testing · ASE 2022 |
Software testing › test generation › test sequence generation
method call sequence generation |
0.6 | 1 | 2022 | Morest: Model-based RESTful API Testing with Execution Feedback · ICSE 2022 |
Software testing
model-based testing |
0.6 | 1 | 2022 | Morest: Model-based RESTful API Testing with Execution Feedback · ICSE 2022 |
Software testing › API testing
REST API test case generation |
0.6 | 1 | 2022 | Morest: Industry Practice of Automatic RESTful API Testing · ASE 2022 |
Methods — techniques the papers use, named apart from their topics
automatic test generation · 1.1model-based testing · 0.6execution feedback · 0.6
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2022 | Morest: Model-based RESTful API Testing with Execution FeedbackabstractRESTful APIs are arguably the most popular endpoints for accessing Web services. Blackbox testing is one of the emerging techniques for ensuring the reliability of RESTful APIs. The major challenge in testing RESTful APIs is the need for correct sequences of API operation calls for in-depth testing. To build meaningful operation call sequences, researchers have proposed techniques to learn and utilize the API dependencies based on OpenAPI specifications. However, these techniques either lack the overall awareness of how all the APIs are connected or the flexibility of adaptively fixing the learned knowledge. Yi Liu 0069, Yuekang Li, Gelei Deng, Yang Liu 0003, Ruiyuan Wan, Runchao Wu, Dandan Ji, Shiheng Xu, Minli Bao |
ICSE | 6 |
| 2022 | Morest: Industry Practice of Automatic RESTful API TestingabstractMany big companies are providing cloud services through RESTful APIs nowadays. With the growing popularity of RESTful API, testing RESTful API becomes crucial. To address this issue, researchers have proposed several automatic RESTful API testing techniques. At Huawei, we design and implement an automatic RESTful API testing framework named Morest. Morest has been used to test ten RESTful API services and helped to detected 83 previously unknown bugs which were all confirmed and fixed by the developers. On one hand, we find that Morest shows great capability of detecting bugs in RESTful API s. On the other hand, we also notice that human effort is inevitable and important when applying automatic RESTful API techniques in practice. Yi Liu 0069, Yuekang Li, Yang Liu 0003, Ruiyuan Wan, Runchao Wu, Qingkun Liu |
ASE | 5 |