Approach to Context Computation for Implicit Context-sensitive Graph Grammars
Yang Zou, Xiaoqin Zeng, Yufeng Liu, Huiyi Liu · Proceedings · 2019
Context-sensitive graph grammars are appropriate formalisms for specifying visual programming languages, as they are intuitive, rigorous, and expressive.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 or limitations in parsing efficiency.Context tends to be a conceivable way to address this issue.Based on the formalization of context, this paper proposes an approach to the computation of context for implicit context-sensitive graph grammars.Moreover, the complexity of the four algorithms comprising the approach is analyzed and the applicability of the approach is discussed.The proposed approach paves the way for the applications of context in implicit graph grammar formalisms, such as facilitating comprehension of graph grammars and improving efficiency of general parsing algorithms.