Don't Panic! Better, Fewer, Syntax Errors for LR Parsers

Authors Lukas Diekmann, Laurence Tratt

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Lukas Diekmann
  • Software Development Team, King’s College London, United Kingdom
Laurence Tratt
  • Software Development Team, King’s College London, United Kingdom


We are grateful to the Blackbox developers for allowing us access to their data, and particularly to Neil Brown for help in extracting a relevant corpus. We thank Edd Barrett for helping to set up our benchmarking machine and for comments on the paper. We also thank Carl Friedrich Bolz-Tereick, Sérgio Queiroz de Medeiros, Sarah Mount, François Pottier, Christian Urban, and Naveneetha Vasudevan for comments.

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Lukas Diekmann and Laurence Tratt. Don't Panic! Better, Fewer, Syntax Errors for LR Parsers. In 34th European Conference on Object-Oriented Programming (ECOOP 2020). Leibniz International Proceedings in Informatics (LIPIcs), Volume 166, pp. 6:1-6:32, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2020)


Syntax errors are generally easy to fix for humans, but not for parsers in general nor LR parsers in particular. Traditional "panic mode" error recovery, though easy to implement and applicable to any grammar, often leads to a cascading chain of errors that drown out the original. More advanced error recovery techniques suffer less from this problem but have seen little practical use because their typical performance was seen as poor, their worst case unbounded, and the repairs they reported arbitrary. In this paper we introduce the CPCT+ algorithm, and an implementation of that algorithm, that address these issues. First, CPCT+ reports the complete set of minimum cost repair sequences for a given location, allowing programmers to select the one that best fits their intention. Second, on a corpus of 200,000 real-world syntactically invalid Java programs, CPCT+ is able to repair 98.37%±0.017% of files within a timeout of 0.5s. Finally, CPCT+ uses the complete set of minimum cost repair sequences to reduce the cascading error problem, where incorrect error recovery causes further spurious syntax errors to be identified. Across the test corpus, CPCT+ reports 435,812±473 error locations to the user, reducing the cascading error problem substantially relative to the 981,628±0 error locations reported by panic mode.

Subject Classification

ACM Subject Classification
  • Theory of computation → Parsing
  • Software and its engineering → Compilers
  • Parsing
  • error recovery
  • programming languages


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