VLDB 2026 Research / reviewers in the wild / expert
Jeewoong Kim
dblp:337/2974
· DBLP profile ↗
3ranked-venue papers
3as first author
3since 2021 · last 2024
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Software engineering, systems software and programming languages · 3 · 3 first-author · 3 since 2021
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2024 | BugOss: A benchmark of real-world regression bugs for empirical investigation of regression fuzzing techniques
Jeewoong Kim, Shin Hong |
J. Syst. Softw. | 1 |
| 2023 | Poster: BugOss: A Regression Bug Benchmark for Empirical Study of Regression Fuzzing TechniquesabstractThis paper presents BugOss, a benchmark of real-world regression bugs found in OSS-Fuzz for experimenting with regression fuzzing techniques. To reproduce the real project context where the bugs were introduced, each study artifact of BugOss indicates the exact bug-inducing commit, and provides the information about the target bug, together with the existing bugs in the same commit. The experiment results with five fuzzing techniques show that the 18 C/C++ artifacts currently registered for BugOss encompass various cases of regression bugs in real-world. We believe that BugOss offers a useful basis for empirically investigating regression fuzzing techniques. Jeewoong Kim, Shin Hong |
ICST | 1 |
| 2022 | Inferring Fine-grained Traceability Links between Javadoc Comment and JUnit Test CodeabstractThis work presents DOTELINK, a technique that infers fine-grained traceability links between Javadoc comments and JUnit test code. To resolve the limitation of method-level traceability links, DOTELINK establishes links in sentence-level for Javadoc comments and code region-level for JUnit test methods. DOTELINK first segregates each Javadoc comment into multiple sentences, and each JUnit test method into coherent code snippets. And then, DOTELINK associates a Javadoc sentence with a code snippet if their lexical similarity is high. DOTELINK identifies 62.4% of the true fine-grained traceability links in the experiments with 5 real-world projects. We believe that DOTELINK effectively helps developers utilize the duality of the two sorts of requirement representations to improve test quality. Jeewoong Kim, Shin Hong |
ICSME | 1 |