计算机科学
齐普夫定律
Python(编程语言)
语法
Java
编译程序
程序设计语言
算法
理论计算机科学
统计
人工智能
数学
标识
DOI:10.1145/2846680.2846681
摘要
Which programming error messages are the most common? We investigate this question, motivated by writing error explanations for novices. We consider large data sets in Python and Java that include both syntax and run-time errors. In both data sets, after grouping essentially identical messages, the error message frequencies empirically resemble Zipf-Mandelbrot distributions. We use a maximum-likelihood approach to fit the distribution parameters. This gives one possible way to contrast languages or compilers quantitatively.
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