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A key part of learning to program is learning to understand programming errormessages. They can be hard to interpret and identifying the cause of errors canbe time-consuming. One factor in this challenge is that the messages aretypically intended for an audience that already knows how to program, or evenfor programming environments that then use the information to highlight areasin code. Researchers have been working on making these errors more novicefriendly since the 1960s, however progress has been slow. The present workcontributes to this stream of research by using large language models toenhance programming error messages with explanations of the errors andsuggestions on how to fix the error. Large language models can be used tocreate useful and novice-friendly enhancements to programming error messagesthat sometimes surpass the original programming error messages ininterpretability and actionability. These results provide further evidence ofthe benefits of large language models for computing educators, highlightingtheir use in areas known to be challenging for students. We further discuss thebenefits and downsides of large language models and highlight future streams ofresearch for enhancing programming error messages.

Using Large Language Models to Enhance Programming Error Messages