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A Systematic Approach to Fuzzy Parsing
 Software Practice and Experience
, 1996
"... This paper presents a systematic approach to implementing fuzzy parsers. A fuzzy parser is a form of syntax analyzer that performs analysis on selected portions of its input rather than performing a detailed analysis of a complete source text. Fuzzy parsers are often components of software tools and ..."
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Cited by 24 (0 self)
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This paper presents a systematic approach to implementing fuzzy parsers. A fuzzy parser is a form of syntax analyzer that performs analysis on selected portions of its input rather than performing a detailed analysis of a complete source text. Fuzzy parsers are often components of software tools and also of program development environments that extract information from source texts. This paper clarifies the term fuzzy parser and introduces an objectoriented framework for implementing reusable and efficient fuzzy parsers. Applications of this framework are described via examples of two software tools. These tools exploit the facilities provided by fuzzy parsers for different purposes and also for different languages
Towards robustness in parsing  fuzzifying contextfree language recognition
 Developments in Language Theory II  At the Crossroad of Mathematics, Computer Science and Biology
, 1996
"... We discuss the concept of robustness with respect to parsing or recognizing a contextfree language. Our approach is based on the notions of fuzzy language, (generalized) fuzzy contextfree grammar, and parser/recognizer for fuzzy languages. As concrete examples we consider a robust version of Cocke– ..."
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Cited by 14 (4 self)
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We discuss the concept of robustness with respect to parsing or recognizing a contextfree language. Our approach is based on the notions of fuzzy language, (generalized) fuzzy contextfree grammar, and parser/recognizer for fuzzy languages. As concrete examples we consider a robust version of Cocke–Younger–Kasami’s algorithm and a robust kind of recursive descent recognizer.
Reveal: A Tool to Reverse Engineer Class Diagrams
 In Proceedings of TOOLS
, 2001
"... Many systems are constructed without the use of modeling and visualization artifacts, due to constraints imposed by deadlines or a shortage of manpower. Nevertheless, such systems might profit from the visualization provided by diagrams to facilitate maintenance of the constructed system. In this pa ..."
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Cited by 10 (6 self)
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Many systems are constructed without the use of modeling and visualization artifacts, due to constraints imposed by deadlines or a shortage of manpower. Nevertheless, such systems might profit from the visualization provided by diagrams to facilitate maintenance of the constructed system. In this paper, we present a tool, Reveal, to reverse engineer a class diagram from the C + + source code representation of the software. In Reveal, we remain faithful to the UML standard definition of a class diagram wherever possible. However, to accommodate the vagaries of the C + + language, we offer some extensions to the standard notation to include representations for namespaces, standalone functions and friend functions. We compare our representation to three other tools that reverseengineer class diagrams, for both compliance to the UML standard and for their ability to faithfully represent the software system under study.
The nonselfembedding property for generalized fuzzy contextfree grammars
 Publ. Math. Debrecen
, 1999
"... Abstract. A fuzzy contextfree Kgrammar is a fuzzy contextfree grammar with a countable rather than a finite number of rules satisfying the following condition: for each symbol α, the set containing all righthand sides of rules with lefthand side equal to α forms a fuzzy language that belongs to ..."
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Cited by 5 (5 self)
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Abstract. A fuzzy contextfree Kgrammar is a fuzzy contextfree grammar with a countable rather than a finite number of rules satisfying the following condition: for each symbol α, the set containing all righthand sides of rules with lefthand side equal to α forms a fuzzy language that belongs to a given family K of fuzzy languages. In this paper we study the effect of the nonselfembedding restriction on the generating power of fuzzy contextfree Kgrammars. Our main result shows that under weak assumptions on the family K, a fuzzy language is generated by a nonselfembedding fuzzy contextfree Kgrammar if and only if either it is a fuzzy regular language or it belongs to the substitution closure K ∞ of the family K. The proof heavily relies on the closure properties of the families K and K∞. 1
Fuzzy ContextFree Languages — Part 1: Generalized Fuzzy ContextFree Grammars Abstract
"... Motivated by aspects of robustness in parsing a contextfree language, we study generalized fuzzy contextfree grammars. These fuzzy contextfree Kgrammars provide a general framework to describe correctly as well as erroneously derived sentences by a single generating mechanism. They model the sit ..."
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Cited by 1 (1 self)
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Motivated by aspects of robustness in parsing a contextfree language, we study generalized fuzzy contextfree grammars. These fuzzy contextfree Kgrammars provide a general framework to describe correctly as well as erroneously derived sentences by a single generating mechanism. They model the situation of making a finite choice out of an infinity of possible grammatical errors during each contextfree derivation step. Formally, a fuzzy contextfree Kgrammar is a fuzzy contextfree grammar with a countable rather than a finite number of rules satisfying the following condition: for each symbol α, the set containing all righthand sides of rules with lefthand side equal to α forms a fuzzy language that belongs to a given family K of fuzzy languages. We investigate the generating power of fuzzy contextfree Kgrammars, and we show that under minor assumptions on the parameter K, the family of languages generated by fuzzy contextfree Kgrammars possesses closure properties very similar to those of the family of ordinary contextfree languages. Key words: formal language, fuzzy contextfree grammar, grammatical error, algebraic closure property 1
Controlled fuzzy parallel rewriting
 New Trends in Formal Languages — Control, Cooperation, and Combinatorics (1997), Lect. Notes. in Comp. Sci. 1218
"... Abstract. We study a Lindenmayerlike parallel rewriting system to model the growth of filaments (arrays of cells) in which developmental errors may occur. In essence this model is the fuzzy analogue of the derivationcontrolled iteration grammar. Under minor assumptions on the family of control lan ..."
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Cited by 1 (1 self)
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Abstract. We study a Lindenmayerlike parallel rewriting system to model the growth of filaments (arrays of cells) in which developmental errors may occur. In essence this model is the fuzzy analogue of the derivationcontrolled iteration grammar. Under minor assumptions on the family of control languages and on the family of fuzzy languages in the underlying iteration grammar, we show that (i) regular control does not provide additional generating power to the model, (ii) the number of fuzzy substitutions in the underlying iteration grammar can be reduced to two, and (iii) the resulting family of fuzzy languages possesses strong closure properties, viz. it is a full hyperAFFL, i.e., a hyperalgebraically closed full Abstract Family of Fuzzy Languages. 1.
Algebraic Aspects of Families of Fuzzy Languages
"... We study operations on fuzzy languages such as union, concatenation, Kleene ⋆, intersection with regular fuzzy languages, and several kinds of (iterated) fuzzy substitution. Then we consider families of fuzzy languages, closed under a fixed collection of these operations, which results in the concep ..."
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We study operations on fuzzy languages such as union, concatenation, Kleene ⋆, intersection with regular fuzzy languages, and several kinds of (iterated) fuzzy substitution. Then we consider families of fuzzy languages, closed under a fixed collection of these operations, which results in the concept of full Abstract Family of Fuzzy Languages or full AFFL. This algebraic structure is the fuzzy counterpart of full Abstract Family of Languages that has been encountered frequently in investigating families of crisp (i.e., nonfuzzy) languages. In the second part of the paper we focus our attention to full AFFL’s closed under iterated parallel fuzzy substitution, where the iterating process is prescribed by given crisp control languages. Proceeding inductively over the family of these control languages, yields an infinite sequence of full AFFLstructures with increasingly stronger closure properties.