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Clone detection plays an important role in software engineering. Findingclones within a single project introduces possible refactoring opportunities,and between different projects it could be used for detecting code reuse orpossible licensing violations.  In this paper, we propose a modification to bag-of-tokens based clonedetection that allows detecting more clone pairs of greater diversity withoutlosing precision by implementing a multi-threshold search, i.e. conducting thesearch several times, aimed at different groups of clones. To combat theincrease in operation time that this approach brings about, we propose anoptimization that allows to significantly decrease the overlap in detectedclones between the searches.  We evaluate the method for two different popular clone detection tools on twodatasets of different sizes. The implementation of the technique allows toincrease the number of detected clones by 40.5-56.6% for different datasets.BigCloneBench evaluation also shows that the recall of detecting StronglyType-3 clones increases from 37.5% to 59.6%.

Multi-threshold token-based code clone detection