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Painless Parse Errors

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If you have a question about this talk, please contact Dominic Orchard.

With a familiar language, programmers require little assistance to correct syntactic errors. But with unfamiliar languages, correcting syntactic errors without expert guidance, in the form of error messages, can be a frustrating experience. Crafting these error messages using traditional techniques requires extensive effort beyond building a parser and is rarely undertaken. Instead of building error messages manually, we are inspired by natural language processing techniques to use Bayesian statistical analysis to automatically produce high-quality parse error messages with almost no implementation effort. Our technique directly applies to combinator parsers, GLR parsers and Earley parsers. We exemplify our technique with a combinator parser for Java, where our automatically generated messages are of similar or superior quality to those created by existing techniques.

This talk is part of the Computer Laboratory Programming Research Group Seminar series.

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