Context-sensitive Graph Grammar Research Articles

A general parsing algorithm with context matching for context-sensitive graph grammars

A general parsing algorithm with context matching for context-sensitive graph grammars

Research on context of implicit context-sensitive graph grammars

Abstract Visual Programming Languages have been widely adopted in design and comprehension of sophisticated systems. Context-sensitive graph grammar formalisms are suitable tools for specifying these languages, since they are intuitive and possess sufficient expressive power and usability. Nevertheless, some of the formalisms whose contexts are implicitly or incompletely represented in productions, called implicit context-sensitive graph grammars, suffer inherent weakness in intuitiveness and limitations in parsing algorithms. To address these issues, this paper formally presents a notion of context on the underlying concepts of partial and total precedence relations, characterizes their fundamental properties, and establishes a connection between contexts and their instances (also called context graphs elsewhere), based on the Reserved Graph Grammar formalism, a representative of implicit graph grammars. Moreover, three typical applications of contexts are illustrated, which show that contexts can both facilitate the comprehension and design of implicit graph grammars so as to enhance their intuitiveness, and make the existent efficient parsing algorithms more widely applicable.

Graph Grammars, Insertion Lie Algebras, and Quantum Field Theory

Graph grammars extend the theory of formal languages in order to model distributed parallelism in theoretical computer science. We show here that to certain classes of context-free and context-sensitive graph grammars one can associate a Lie algebra, whose structure is reminiscent of the insertion Lie algebras of quantum field theory. We also show that the Feynman graphs of quantum field theories are graph languages generated by a theory dependent graph grammar.

On the Expressiveness of Context-Sensitive Graph Grammars

上下文相关图文法是描述可视化语言的形式化工具.为了直观地刻画并高效地分析可视化语言,已有图文法形式框架均着重于文法形式和分析算法的研究,而忽略了对它们之间表达能力的分析.在对已有上下文相关图文法形式框架的关键特征进行分析和归纳的基础上,通过构造不同形式框架之间的转换算法,揭示并形式化证明了它们表达能力之间的关系.而且,转换算法在不同形式框架之间建立了关联,使图文法的应用不必再局限于一个框架,而是可以选择不同框架分别进行图的描述和分析,从而提高了上下文相关图文法的易用性.;Context-Sensitive graph grammars are formal tools used for specifying visual languages. In order to intuitively describe and parse visual languages, current research has stressed the formalisms and algorithms of graph grammars, but has neglected the comparison of their expressiveness. Based on the analysis and induction of the key characteristics of context-sensitive graph grammar, the relationships between their expressiveness are uncovered and proved in this paper by constructing formalism-transforming algorithms. Moreover, the proposed algorithms correlate with these formalisms; thus, facilitating the usage of context-sensitive graph grammars, as alternative formalisms rather than merely one can be chosen to separately specify and parse visual objects in applications.

Improving the graph grammar parser of Rekers and Schürr

Graph grammars and graph grammar parsers are to visual languages what string grammars and parsers are to textual languages. A graph grammar specifies a set of valid graphs and can thus be used to formalise the syntax of a visual language. A graph grammar parser is a tool for recognising valid programs in such a formally defined visual language. A parser for context-sensitive graph grammars, which have proved to be suitable for formalising real-world visual languages, was developed by Rekers and Schürr. We propose three improvements of this parser. One of them enlarges the class of parsable graph grammars, while the other two increase the parser's computational efficiency. Experimental results show that for some (meaningful) graph grammars, our improvements can enhance the parser's performance by orders of magnitude. The proposed improvements will hopefully increase both the parser's applicability and the interest in visual language parsing in general.

Requirements Variability Support Through MDA™ and Graph Transformation

One of the most important factors of success in the development of a software product line is the elicitation, management, and representation of variability. Feature models, are used as a key artifact to express requirements variability and are the basis for the domain architecture design. In this context, this article explores the possible advantages of Model Driven Engineering (MDE) and shows an automated transformation from the feature model to the architecture model. This transformation is understood as a graph transformation process because it offers a natural way to represent model transformations. The transformation is applied by the definition of a simple context-sensitive graph grammar where production rules are obtained from metamodels of both feature and architecture models.

Syntactic Characterization of the Two-Dimensional Grid Graphs

Vigna and Ghezzi showed that the language of grid graphs could not be constructed by their context-free graph grammars [1]. In this paper, we construct a context-sensitive graph grammar for the two-dimensional grid graphs.

Attribute block diagram grammar and its application

An attribute block diagram grammar has been defined for supporting control system analysis and design using block diagrams on a computer. It consists of the block diagram grammar which we previously defined for the graph-syntax rules of block diagrams on the basts of a context-sensitive graph grammar, attributes attached to each node label, and semantic rules which are used to extract as attribute values a variety of information such as the system structure and the relationships between the signals running within a system. A parser-evaluator was implemented based on this attribute block diagram grammar. It decides whether or not a diagram is valid for the grammar, then returns attribute values for a valid diagram.

Block Diagram Grammar and Structure Recognition Based on Graph Rewriting

A block diagram grammar is presented that is a formal model generating block diagrams. It is formalized as a context-sensitive graph grammar with subgraph rewriting based on subgraph isomorphism. We implement a block diagram parser that decides whether a diagram is valid for the block diagram grammar in a bottomup-parallel method, and that returns the production instance sequence for a valid diagram. A function of structure recognition is also implemented into the parser by means of template matching and subgraph rewriting. This enables the parser to find and return the structure information of series connections, parallel connections, feedback connections and so forth, in the parsed diagram.