| Resumo: | We illustrate the state of the art in software plagiarism detection tools by comparing their features and testing them against a wide range of source codes. The source codes were edited according to several types of plagiarism to show the tools accuracy at detecting each type. The decision to focus our research on plagiarism of programming languages is two fold: on one hand, it is a challenging case-study since programming languages impose a structured writing style; on the other hand, we are looking for the integration of such a tool in an Automatic-Grading System (AGS) developed to support teachers in the context of Programming courses. Besides the systematic characterisation of the underlying problem domain, the tools were surveyed with the objective of identifying the most successful approach in order to design the aimed plugin for our AGS.
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