Global Context Recovery: A New Strategy for Syntactic Error Recovery by Table-Drive Parsers

Abstract

Described is a method for syntactic error recovery that is compatible with deterministic parsing methods and that is able to recover from many errors more quickly than do other schemes because it performs global context recovery. The method relies on fiducial symbols, which are typically reserved key words of a language, to provide mileposts for error recovery. The method has been applied to LL(1) parsers, for which a detailed algorithm is given, and informally proved correct. The algorithm will always recover and return control to the parser if the text being analyzed satisfies only minimal requirements: that it contains one or more occurrences of fiducial symbols following the point at which an error is detected. Tables needed for error recovery have been automatically generated, along with parsing tables, by a parser constructor for the LL(1) grammars.A theoretical characterization of fiducial symbols is given, and the utility of this characterization in practice is discussed. It has been applied to a grammar for the programming language Pascal to aid in selection of a set of fiducial symbols. The error recovery scheme has been tested on a set of studentwritten Pascal program texts and is compared with other error recovery strategies.

Declarative specification of template-based textual editors

“…We believe this can be attributed to the fact that the language consists mainly of identifier-like tokens, partly because the identifier sublanguage is larger than in many DSLs, and partly because many language constructs consist of Dutch words with only minimal punctuation. This means it may be expensive for the parser to get back "in sync" with the stream of characters after a parse error, unless statements happen to be separated, terminated, or preceded by a fiducial symbol [43] such as the newline character.…”

Natural and Flexible Error Recovery for Generated Modular Language Environments

“…Following these criteria, an excellent recovery is one that is exactly the same as the intended program, a good recovery is one that results in a reasonable program without spurious or missed errors, and a poor recovery is a recovery that introduces spurious errors or involves excessive token deletion. The Pennello and DeRemer criteria represent the state of the art evaluation method for syntactic error recovery applied in, amongst others, [Pennello and DeRemer 1978;Pai and Kieburtz 1980;Degano and Priami 1995;Corchuelo et al 2002].…”

“…The problem of handling syntax errors during parsing has been widely studied [Lévy 1971;Mauney and Fischer 1988;Pai and Kieburtz 1980;Barnard and Holt 1982;Tai 1978;Fischer et al 1980;Degano and Priami 1995;McKenzie et al 1995;Corchuelo et al 2002]. We focus on LR parsing for which there are several different error recovery techniques [Degano and Priami 1995].…”

“…Regional error recovery methods [Lévy 1971;Mauney and Fischer 1988;Pai and Kieburtz 1980;Barnard and Holt 1982] select a region that encloses the point of detection of an error. Typically, these regions are selected based on nearby marker tokens (also called fiducial tokens [Pai and Kieburtz 1980], or synchronizing symbols [Barnard and Holt 1982]), which are languagedependent.…”

“…Typically, these regions are selected based on nearby marker tokens (also called fiducial tokens [Pai and Kieburtz 1980], or synchronizing symbols [Barnard and Holt 1982]), which are languagedependent. In our approach, we assign regions based on layout instead.…”