
The paper describes similarity detection method for language independent source code similarity detection. It is based on idea of maximum reusability of standard Unix filters. This method was implemented and benchmarked with different datasets from real world (students' assignments) and also synthetic datasets (perfect plagiarism experiment). Our method achieved significantly better results than competitors, which are considered as gold standard in plagiarism detection.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 5 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
