ICSE 2023 (series) / Artifact Evaluation /
Learning Graph-based Code Representations for Source-level Functional Similarity Detection
This artifact provides the source code of Tailor and scripts to reproduce the experimental results from the ICSE 2023 paper — Learning Graph-based Code Representations for Source-level Functional Similarity Detection'' by Jiahao Liu, Jun Zeng, Xiang Wang, and Zhenkai Liang. All the benchmarks that are used in our evaluation are also included in the artifact. To facilitate the artifact evaluation, we further include the experimental logs when we performed the evaluation. We also provide a docker image that has set up the environment and installed all the dependencies, so the results can be reproduced easily. In this artifact, we apply for the
Artifact Available'', Artifact Functional'', and
Artifact Reproduced'' badges.