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Painless Parse Errors

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If you have a question about this talk, please contact Christian Steinruecken .

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 Inference Group series.

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King Richard Room, Darwin College Lombard Room, Hotel Du Vin Webinar & FW11, Computer Laboratory, William Gates Building.

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