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YooccLa: a parser generator for L-attributed grammars
2022This paper argues that a parser generator can be developed that requires less knowledge of parser technology than most existing parser generators;that can bring parser technology within the reach of more software engineers;and that can allow a parser to be used where a designer might otherwise have chosen a fully procedural solution. A parser generator,
Butler, G, Mingins, C
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Teaching machines to write like humans using L-attributed grammar
Engineering Applications of Artificial Intelligence, 2020Abstract Reading and writing are easy for humans. The automatic reading of handwritten characters has been studied for several decades. Machine learning algorithms for reading tasks often require a huge amount of data to perform with similar accuracy to humans, yet it is also difficult to gain sufficient meaningful data.
Yunxue Shao, Cheng-Lin Liu
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YooccLa: a parser generator for L-attributed grammars
Proceedings 37th International Conference on Technology of Object-Oriented Languages and Systems. TOOLS-Pacific 2000, 2002Argues that a parser generator can be developed that: (1) can bring parser technology within the reach of more software engineers, (2) requires less knowledge of parser technology than most existing parser generators, and (3) can allow a parser to be used where a designer might otherwise have chosen a fully procedural solution.
G. Butler, C. Mingins
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L-attributed LL(1)-grammars are LR-attributed
Information Processing Letters, 1986Nakata, Ikuo, Sassa, Masataka
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Polygrammar: Grammar for Digital Polymer Representation and Generation
Advanced Science, 2022Minghao Guo, Wojciech Matusik
exaly
Attribute And-Or Grammar for Joint Parsing of Human Pose, Parts and Attributes
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2018Xiaohan Nie, Song-Chun Zhu
exaly