Towards Syntax-Aware Editors for Visual Languages

AbstractEditors for visual languages should provide a user-friendly environment supporting end users in the composition of visual sentences in an effective way. Syntax-aware editors are a class of editors that prompt users into writing syntactically correct programs by exploiting information on the visual language syntax. In particular, they do not constrain users to enter only correct syntactic states in a visual sentence. They merely inform the user when visual objects are syntactically correct. This means detecting both syntax and potential semantic errors as early as possible and providing feedback on such errors in a non-intrusive way during editing. As a consequence, error handling strategies are an essential part of such editing style of visual sentences.In this work, we develop a strategy for the construction of syntax-aware visual language editors by integrating incremental subsentence parsers into free-hand editors. The parser combines the LR-based techniques for parsing visual languages with the more general incremental Generalized LR parsing techniques developed for string languages. Such approach has been profitably exploited for introducing a noncorrecting error recovery strategy, and for prompting during the editing the continuation of what the user is drawing

Integrated speech and morphological processing in a connectionist continuous speech understanding for Korean

A new tightly coupled speech and natural language integration model is presented for a TDNN-based continuous possibly large vocabulary speech recognition system for Korean. Unlike popular n-best techniques developed for integrating mainly HMM-based speech recognition and natural language processing in a {\em word level}, which is obviously inadequate for morphologically complex agglutinative languages, our model constructs a spoken language system based on a {\em morpheme-level} speech and language integration. With this integration scheme, the spoken Korean processing engine (SKOPE) is designed and implemented using a TDNN-based diphone recognition module integrated with a Viterbi-based lexical decoding and symbolic phonological/morphological co-analysis. Our experiment results show that the speaker-dependent continuous {\em eojeol} (Korean word) recognition and integrated morphological analysis can be achieved with over 80.6% success rate directly from speech inputs for the middle-level vocabularies.Comment: latex source with a4 style, 15 pages, to be published in computer processing of oriental language journa

CHR Grammars

A grammar formalism based upon CHR is proposed analogously to the way Definite Clause Grammars are defined and implemented on top of Prolog. These grammars execute as robust bottom-up parsers with an inherent treatment of ambiguity and a high flexibility to model various linguistic phenomena. The formalism extends previous logic programming based grammars with a form of context-sensitive rules and the possibility to include extra-grammatical hypotheses in both head and body of grammar rules. Among the applications are straightforward implementations of Assumption Grammars and abduction under integrity constraints for language analysis. CHR grammars appear as a powerful tool for specification and implementation of language processors and may be proposed as a new standard for bottom-up grammars in logic programming. To appear in Theory and Practice of Logic Programming (TPLP), 2005Comment: 36 pp. To appear in TPLP, 200

Typing rule-based transformations over topological collections

Pattern-matching programming is an example of a rule-based programming style developed in functional languages. This programming style is intensively used in dialects of ML but is restricted to algebraic data-types. This restriction limits the field of application. However, as shown by Giavitto and Michel at RULE'02, case-based function definitions can be extended to more general data structures called topological collections. We show in this paper that this extension retains the benefits of the typed discipline of the functional languages. More precisely, we show that topological collections and the rule-based definition of functions associated with them fit in a polytypic extension of mini-ML where type inference is still possible

Syntax Error Handling in Scannerless Generalized LR Parsers

This thesis is about a master's project as part of the one year master study 'Software-engineering'. This project is about methods for improving the quality of reporting and handling of syntax errors that are produced by a scannerless generalized left-to-right rightmost (SGLR) parser, and is done at Centrum voor Wiskunde en Informatica (CWI) in Amsterdam. SGLR is a parsing algorithm developed as part of Generic Language Technol- ogy Project at SEN1, one of the themes at CWI. SGLR is based on the GLR algorithm developed by Tomita. SGLR parsers are able to recognize arbitrary context-free grammars, which enables grammar modularization. Because SGLR does not use a separate scan- ner, also layout and comments are incorporated into the parse tree. This makes SGLR a powerful tool for code analysis and code transformations. A drawback is the way SGLR handles syntax errors. When a syntax error is detected, the current implementation of SGLR halts the parsing process and reports back to the user the point of error detection only. The text at the point of error detection is not necessarily the text that has to be changed to repair the error. This thesis describes three kinds of information that could be reported to the user, and how they could be derived from the parse process when an error is detected. These are: - The structure of the already parsed part of the input in the form of a partial parse tree. - A listing of expected symbols; those tokens or token sequences that are accept- able instead of the erroneous text. - The current parser state which could be translated into language dependent informative messages. Also two ways of recovering from an error condition are described. These are non-correcting recovery methods that enable SGLR to always return a parse tree that can be unparsed into the original input sentence. - A method that halts parsing but incorporates the remainder of the input into the parse tree. - A method that resumes parsing by means of substring parsing. During the course of the project the described approaches have been imple- mented and incorporated in the implementation of SGLR as used by the Meta- Environment, some fully, some more or less prototyped

The Mystro system: A comprehensive translator toolkit

Mystro is a system that facilities the construction of compilers, assemblers, code generators, query interpretors, and similar programs. It provides features to encourage the use of iterative enhancement. Mystro was developed in response to the needs of NASA Langley Research Center (LaRC) and enjoys a number of advantages over similar systems. There are other programs available that can be used in building translators. These typically build parser tables, usually supply the source of a parser and parts of a lexical analyzer, but provide little or no aid for code generation. In general, only the front end of the compiler is addressed. Mystro, on the other hand, emphasizes tools for both ends of a compiler