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Using Machine Learning to Recognise Novice and Expert Programmers

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Publication date23/11/2021
Host publicationProduct-Focused Software Process Improvement - 22nd International Conference, PROFES 2021, Proceedings: 22nd International Conference, PROFES 2021, Turin, Italy, November 26, 2021, Proceedings
EditorsLuca Ardito, Andreas Jedlitschka, Maurizio Morisio, Marco Torchiano
Place of PublicationCham
Number of pages8
ISBN (Electronic)9783030914523
ISBN (Print)9783030914516
<mark>Original language</mark>English

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume13126 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Understanding and recognising the difference between novice and expert programmers could be beneficial in a wide range of scenarios, such as to screen programming job applicants. In this paper, we explore the identification of code author attributes to enable novice/expert differentiation via machine learning models. Our iteratively developed model is based on data from HackerRank, a competitive programming website. Multiple experiments were carried using 10-fold cross-validation. Our final model performed well by differentiating novice coders from expert coders with 71.3% accuracy.