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

  • 1191: Sentient Multimedia Systems
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Abstract

Context-sensitive graph grammars have been intuitive and rigorous formalisms for specifying visual programming languages, as they are sufficient expressive and equipped with parsing mechanisms. Parsing has been a fundamental issue in the research of context-sensitive graph grammars. However, the existent parsing algorithms are either inefficient or confined to a minority of graph grammars. This paper proposes a general parsing algorithm with two embedded strategies, context matching and production-set partitioning. The two strategies can greatly narrow down the search space of redexes and thus significantly improve parsing efficiency, even though the worst-case time complexity is not theoretically reduced. Moreover, a detailed case study and an experiment are provided accordingly to demonstrate the paring process and performance of the proposed algorithm.

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Acknowledgments

This work is supported in part by the National Science Foundation of China under grant 61170089.

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Authors and Affiliations

  1. Institute of Intelligence Science and Technology, School of Computer and Information, Hohai University, Nanjing, China

    Yang Zou, Xiaoqin Zeng & Yun Zhu

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  1. Yang Zou
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  2. Xiaoqin Zeng
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  3. Yun Zhu
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Correspondence to Yang Zou.

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Zou, Y., Zeng, X. & Zhu, Y. A general parsing algorithm with context matching for context-sensitive graph grammars. Multimed Tools Appl 81, 273–297 (2022). https://doi.org/10.1007/s11042-021-11076-8

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  • DOI: https://doi.org/10.1007/s11042-021-11076-8

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