Research group

Machine Learning Methods in Software Engineering

Authorship Attribution of Source Code

Timofey BryksinActive

We developed a language-agnostic approach to authorship attribution of source code, that improved over SOtA accuracy of some language-specific approaches on existing datasets. We also demonstrated that existing evaluation techniques of authorship attribution methods are misaligned with potential practical applications. Finally, we proposed a more realistic approach to building evaluation datasets.

The paper is under review for IEEE TSE.



Authorship Attribution of Source Code: A Language-Agnostic Approach and Applicability in Software Engineering

August 2021

Egor Bogomolov, Vladimir Kovalenko, Alberto Bacchelli, and Timofey Bryksin

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