  Being able to duplicate published research results is an important process of
conducting research whether to build upon these findings or to compare with
them. This process is called "replicability" when using the original authors'
artifacts (e.g., code), or "reproducibility" otherwise (e.g., re-implementing
algorithms). Reproducibility and replicability of research results have gained
a lot of interest recently with assessment studies being led in various fields,
and they are often seen as a trigger for better result diffusion and
transparency. In this work, we assess replicability in Computer Graphics, by
evaluating whether the code is available and whether it works properly. As a
proxy for this field we compiled, ran and analyzed 151 codes out of 374 papers
from 2014, 2016 and 2018 SIGGRAPH conferences. This analysis shows a clear
increase in the number of papers with available and operational research codes
with a dependency on the subfields, and indicates a correlation between code
replicability and citation count. We further provide an interactive tool to
explore our results and evaluation data.
