Final published version
Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review
Publication date | 23/11/2021 |
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Host publication | Product-Focused Software Process Improvement - 22nd International Conference, PROFES 2021, Proceedings: 22nd International Conference, PROFES 2021, Turin, Italy, November 26, 2021, Proceedings |
Editors | Luca Ardito, Andreas Jedlitschka, Maurizio Morisio, Marco Torchiano |
Place of Publication | Cham |
Publisher | Springer |
Pages | 199-206 |
Number of pages | 8 |
ISBN (Electronic) | 9783030914523 |
ISBN (Print) | 9783030914516 |
<mark>Original language</mark> | English |
Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
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Volume | 13126 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.