Using Shannon entropy over source-code tokens and AST edges, the paper finds weak correlations with classic complexity metrics and achieves 37-83% precision in detecting unusual commits across 95 Java projects.
In: Submitted to The Thirteenth International Conference on Learning Representations, ://openreview.net/forum?id=AjXkRZIvjB, under review
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Information-Theoretic Detection of Unusual Source Code Changes
Using Shannon entropy over source-code tokens and AST edges, the paper finds weak correlations with classic complexity metrics and achieves 37-83% precision in detecting unusual commits across 95 Java projects.