Research group

Machine Learning Methods in Software Engineering

Authorship Attribution of Source Code

Bryksin Timofey, Kovalenko VladimirActive

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.

Participants

Bryksin Timofey
Bryksin Timofey
Bogomolov Egor
Bogomolov Egor
Kovalenko Vladimir
Kovalenko Vladimir

Publications

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

February 2020

Egor Bogomolov, Vladimir Kovalenko, Alberto Bacchelli, Timofey Bryksin

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