Index-Based Type-3 Clone Detection

Context: Clone detection is a~common task in software engineering. Type-3 clones are fragments of code that can be slightly different in structure. Objective: The article presents a~new algorithm for Type-3 clone detection, its open-source implementation called emph DrDupLex3, and novel open-source tools that can be used for the automated assessment of Type-3 clones and to prepare training sets for machine learning-based clone detectors. Method: The algorithm for Type-3 clone detection builds upon the index of source code used in emph DrDupLex, the most accurate Type-2 clone detector to date. Results: A comparison with three state-of-the-art clone detectors (emph NiCad, emph CloneWorks, and emph SourcererCC) shows that emph DrDupLex3 is able to outperform them in precision, recall, and running time. It reported no false positives and found all clones reported by emph NiCad, emph CloneWorks, and emph SourcererCC. Conclusions: The presented clone detector outperforms three state-of-the-art competitors in a~scenario that can be easily repeated because it is based on tools for automated assessment of Type-3 clones.