  In this paper, we describe and present the first dataset of source code
plagiarism specifically aimed at contest plagiarism. The dataset contains 251
pairs of plagiarized solutions of competitive programming tasks in Java, as
well as 660 non-plagiarized ones, however, the described approach can be used
to extend the dataset in the future. Importantly, each pair comes in two
versions: (a) "raw" and (b) with participants' repeated template code removed,
allowing for evaluating tools in different settings. We used the collected
dataset to compare the available source code plagiarism detection tools,
including state-of-the-art ones, specifically in their ability to detect
contest plagiarism. Our results indicate that the tools show significantly
worse performance on the contest plagiarism because of the template code and
the presence of other misleadingly similar code. Of the tested tools,
token-based ones demonstrated the best performance in both variants of the
dataset.
