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Source Code Analytics With Roslyn and JavaScript Data Visualization by Sudipta Mukherjee

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© Sudipta Mukherjee 2016

Sudipta Mukherjee, Source Code Analytics With Roslyn and JavaScript Data Visualization, 10.1007/978-1-4842-1925-6_6

6. Code Forensics

Sudipta Mukherjee

(1)Varthur Hobli, India

In Chapter 5 you saw how to detect plagiarized code. This chapter is an extension to that. As I proposed in that chapter, imagine that two students submit code that looks plagiarized. Should credit be given for originality, and if so, who should get it? Who might be the original author and who might have been plagiarizing content?

The only way to know is to look at their submissions historically. The credit for originality should be given to the student whose code remains faithfully similar in patterns, historically. Techniques for determining this ...

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