Frequency Distribution of Error Messages
Which programming error messages are the most common? We investigate this question, motivated by writing error explanations better suited to novices. We consider two very large data sets, one in Python and the other in Java, both combining syntax and run-time errors. We group essentially identical messages and then determine the most common ones. In both data sets, we find that the error message frequencies empirically resemble Zipf-Mandelbrot distributions. We use a maximum-likelihood approach to select the distribution parameters. This gives one possible way to contrast languages or compilers quantitatively.
|Frequency Distribution of Error Messages (plateau2015-pritchard.pdf)||960KiB|
David Pritchard studied computer science and mathematics at MIT and the University of Waterloo, obtaining his PhD in 2010. He taught at Waterloo, EPFL (Switzerland), Princeton University, and the University of Southern California, while developing free software for students to practice and learn introductory programming online. He is currently employed at Google Los Angeles, and continues to volunteer for the Computer Science Circles project, which is hosted by the Center for Education in Mathematics and Computer Science in Waterloo.
Mon 26 OctDisplayed time zone: Eastern Time (US & Canada) change
10:30 - 12:00
|Frequency Distribution of Error Messages|
David Pritchard University of Waterloo, CanadaFile Attached
|An Evaluation of the DiaSuite Toolset by Professional Developers|
Milan Kabáč University of Bordeaux / Inria Bordeaux / LaBRI, Nic Volanschi Inria Bordeaux, Charles Consel University of BordeauxFile Attached
|Aiding Programmers using Lightweight Integrated Code Visualization|
|Towards moldable development tools|
Andrei Chiş University of Bern, Switzerland, Tudor Gîrba tudorgirba.com, Switzerland, Oscar Nierstrasz University of Bern, SwitzerlandPre-print Media Attached File Attached
|Understanding the Effects of Code Presentation|