
doi: 10.2139/ssrn.3696046
Plagiarism of code is a serious issue in today’s era. Plagiarism refers to the use of someone’s data, language and writing without proper acknowledgement of the original source. Our project basically aims to detect plagiarism in subsequent code submissions made by students. We are hosting a front-end website from where the user will be uploading the source code, after this in the website the code submissions will be made to check the extent of plagiarism in the code submissions made by students. We will check the extent of plagiarism by checking multiple parameters like number of lines of code, number of functions used, number of loops used and the extent to which keywords match in subsequent codes.
| 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). | 0 | |
| 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). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
