Pascal user manual and report; 3rd ed.
Pascal user manual and report; 3rd ed.
Locally Least-Cost Error Recovery in Earley's Algorithm
ACM Transactions on Programming Languages and Systems (TOPLAS)
Syntax-directed least-errors analysis for context-free languages: a practical approach
Communications of the ACM
Bounded context syntactic analysis
Communications of the ACM
Error Recovery and Correction - An Introduction to the Literature
Compiler Construction, An Advanced Course, 2nd ed.
Error recovery for Simple LR(k) parsers
ACM '76 Proceedings of the 1976 annual conference
An LR substring parser for noncorrecting syntax error recovery
PLDI '89 Proceedings of the ACM SIGPLAN 1989 Conference on Programming language design and implementation
Substring parsing for arbitrary context-free grammars
ACM SIGPLAN Notices
A bibliography on syntax error handling in context free languages
ACM SIGPLAN Notices
Recognizing substrings of LR(k) languages in linear time
POPL '92 Proceedings of the 19th ACM SIGPLAN-SIGACT symposium on Principles of programming languages
Recognizing substrings of LR(k) languages in linear time
ACM Transactions on Programming Languages and Systems (TOPLAS)
Linear-time suffix parsing for deterministic languages
Journal of the ACM (JACM)
Proceedings of the 26th ACM SIGPLAN-SIGACT symposium on Principles of programming languages
On parsing and condensing substrings of LR languages in linear time
Theoretical Computer Science
On Parsing and Condensing Substrings of LR Languages in Linear Time
WIA '98 Revised Papers from the Third International Workshop on Automata Implementation
Fast parallel recognition of LR language suffixes
Information Processing Letters
Fast parallel recognition of LR language suffixes
Information Processing Letters
LR techniques for handling syntax errors
Computer Languages
Error handling in a parallel LR substring parser
Computer Languages
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A parser must be able to continue parsing after encountering a syntactic error to check the remainder of the input. To achieve this, it is not necessary to perform corrections on either the input text or the stack contents. A formal framework is provided in which noncorrecting syntax error recovery concepts are defined and investigated. The simplicity of these concepts allows the statement of provable properties, such as the absence of spurious error messages or the avoidance of skipping input text. These properties are due to the fact that no assumptions about the nature of the errors need be made to continue parsing.