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Parsing Based on Multigeneration
Kyjovská, Linda ; Přikryl, Zdeněk (referee) ; Lukáš, Roman (advisor)
This work deals with syntax analysis problems based on multi-generation. The basic idea is to create computer program, which transforms one input string to n -1 output strings. An Input of this program is some plain text file created by user, which contains n grammar rules. Just one grammar from the input file is marked as an input grammar and others n -1 grammars are output grammars. This program creates list of used input grammar rules for an input string and uses corresponding output grammar rules for the creation of n -1 output strings. The program is written in C++ and Bison
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Visualization of Finite Automata, Pushdown Automata and Turing Machines Work
Syrový, Ondřej ; Láník, Aleš (referee) ; Zuzaňák, Jiří (advisor)
This bachelor`s thesis is focusing on concept and development of computer application for demonstration of finite automata, pushdown automata and Turing machines work. Theoretic volume of this work deals with theories of formal languages and grammars and automata theory. Created program allows to load deterministic and nondeterministic automata variants from the text file, their graphic representation by state diagram and stepping their calculation process.
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Parsing Based on Modified Pushdown Automata
Pluháček, David ; Lukáš, Roman (referee) ; Meduna, Alexandr (advisor)
The thesis introduces new models for formal languages, the m-limited state grammar and the deep pushdown automaton. Their basic definitions are presented, so is their mutual equivalence and the characteristics of the language family they describe. Following, a parsing method based on these models is presented. The method is an extension of a similar method used for context-free languages, the table driven parsing. The final part of the thesis describes the implementation of a parser based on the method.
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Machine Learning for Formal Language Model Inference
Bardonek, Petr ; Kocman, Radim (referee) ; Křivka, Zbyněk (advisor)
This bachelor thesis deals with the formal language model inference, which is a science discipline on the research field of artificial intelligence. The aim is to create an appliaction that allows the automatic inference of model, such as the finite state machine, for an unknown formal language from the set of the strings of the unknown formal language using the modified machine learning method.
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Demonstration of Tree Controlled Grammars Properties
Kunštátský, Martin ; Čermák, Martin (referee) ; Koutný, Jiří (advisor)
Tree controlled grammars are grammars regulated by restriction placed on its derivation trees. It is simple and natural extension of context-free grammars. There are several types of derivation tree control, two principles are mentioned in this work: horizontal and vertical control. Application demonstrating tree controlled grammars properties, implemented in Python programming language, is also part of this work.
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Modified Pushdown Automata
Hromádka, David ; Solár, Peter (referee) ; Meduna, Alexandr (advisor)
This work introduces limited Hromádka's automata as an extension of classical pushdown automata. This extension means that the automaton is able to create new pushdowns, insert input symbols into them, join them and compare with the input string in run time. The number of such pushdowns is limited by choosen constant n . This work also describes the implementation of the application, that realizes the activity of this automata and is looking for the sequence of derivational steps, by which the automaton accepts the input string.
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Semi-Parallel Deep Pushdown Transducers and Their Applications
Putala, Marek ; Dolejška, Daniel (referee) ; Meduna, Alexandr (advisor)
The goal of this work was to become familiar with deep stack automata and, based on the acquired knowledge, to further design, formally define and implement a partially parallel deep stack transducer. It is an extension of deep stack transducer that is capable of accessing non-terminal symbols simultaneously on the stack in one step. With a suitably chosen configuration in the form of rules, they can process the input string with fewer transitions and therefore have a higher speed compared to deep stack transducer.
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Modified Pushdown Automata
Hromádka, David ; Solár, Peter (referee) ; Meduna, Alexandr (advisor)
This work introduces limited Hromádka's automata as an extension of classical pushdown automata. This extension means that the automaton is able to create new pushdowns, insert input symbols into them, join them and compare with the input string in run time. The number of such pushdowns is limited by choosen constant n . This work also describes the implementation of the application, that realizes the activity of this automata and is looking for the sequence of derivational steps, by which the automaton accepts the input string.
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