Abstract
Plagiarism and copyright infringement are major problems in academic and corporate environments. Importance of source code authorship attribution arises as it is the starting point of detection for plagiarism, copyright infringement and law suit prosecution etc. There have been many research regard to this topic. Majority of these researches are based on various algorithms which compute similarity amongst source code files. However, for this Paper we have proposed Deep Neural Network (DNN) based technique to be used for source code authorship attribution. Results proved that DNN based author identification brings promising results once compared the accuracy against previously published research.
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Bandara, U., Wijayarathna, G. (2013). Deep Neural Networks for Source Code Author Identification. In: Lee, M., Hirose, A., Hou, ZG., Kil, R.M. (eds) Neural Information Processing. ICONIP 2013. Lecture Notes in Computer Science, vol 8227. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-42042-9_46
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DOI: https://doi.org/10.1007/978-3-642-42042-9_46
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