Plagiarism detection and clone refactoring in software depend on one common concern: finding similar source chunks across large repositories. However, since code duplication in software is often the result of copy-paste behaviors, only minor modifications are expected between shared codes. On the contrary, in a plagiarism detection context, edits are more extensive and exact matching strategies show their limits.
Among the three main representations used by source code similarity detection tools, namely the linear token sequences, the Abstract Syntax Tree (AST) and the Program Dependency Graph (PDG), we believe that the AST could efficiently support the program analysis and transformations required for the advanced similarity detection process.
We present here a simple and scalable architecture based on syntax tree fingerprinting. Thanks to a study of several hashing strategies reducing false-positive collisions, we propose a framework that efficiently indexes AST representations in a database, that quickly detects exact (w.r.t source code abstraction) clone clusters and that easily retrieves their corresponding ASTs. Our aim is to allow further processing of neighboring exact matches in order to identify the larger approximate matches, dealing with the common modification patterns seen in the intra-project copy-pastes and in the plagiarism cases.