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Enhancing the Learning Ability Using JFLAP for Theory of Computation Course


Affiliations
1 Information Technology, Walchand Institute of Technology, Solapur, Maharashtra, India
2 Computer Science & Engineering, Walchand Institute of Technology, Solapur, Maharashtra, India
     

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The theory of Computation course is the core subject for Computer Science disciplines. It is based on the automata theory and design of machines like Finite Automata (FA) for regular languages, Pushdown Automata (PDA) for Context-free languages and Turing Machine for Recursively Enumerable languages. Most of the part includes theoretical concepts like theorems, proofs and examples. The most promising part of this course is to solve examples according the given theory concept for a particular machine design. Teaching and learning this course is based on the imagination of theoretical concepts with the design of machine part. For a novice computer science student it is difficult to connect with the theory and a design for solving examples. The study proposes an effective way of teaching this course using Java Formal Languages and Automata Package (JFLAP) tool. It is a preexisting software tool created by Professor Susan Rodger and her students at Duke University. It allows designing and running machines like finite automata, pushdown automata and turing machine with the theorem proofs. It also focuses on conversions of languages from one form to another form easily.The experiment is conducted for the second year computer science and engineering students for the course of Theory of Computation (TOC). The results show that, the ability of problem solving among students increased effectively with more understanding level. The effectiveness of the experiment is verified by the feedback from students and the university results. It is observed that the learners can evaluate them selves for the problems using JFLAP.

Keywords

Theory of Computation, Automata Theory, Simulation, FA Design and Evaluation, Visualization.
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  • Enhancing the Learning Ability Using JFLAP for Theory of Computation Course

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Authors

Pratibha S. Yalagi
Information Technology, Walchand Institute of Technology, Solapur, Maharashtra, India
Rashmi K. Dixit
Computer Science & Engineering, Walchand Institute of Technology, Solapur, Maharashtra, India

Abstract


The theory of Computation course is the core subject for Computer Science disciplines. It is based on the automata theory and design of machines like Finite Automata (FA) for regular languages, Pushdown Automata (PDA) for Context-free languages and Turing Machine for Recursively Enumerable languages. Most of the part includes theoretical concepts like theorems, proofs and examples. The most promising part of this course is to solve examples according the given theory concept for a particular machine design. Teaching and learning this course is based on the imagination of theoretical concepts with the design of machine part. For a novice computer science student it is difficult to connect with the theory and a design for solving examples. The study proposes an effective way of teaching this course using Java Formal Languages and Automata Package (JFLAP) tool. It is a preexisting software tool created by Professor Susan Rodger and her students at Duke University. It allows designing and running machines like finite automata, pushdown automata and turing machine with the theorem proofs. It also focuses on conversions of languages from one form to another form easily.The experiment is conducted for the second year computer science and engineering students for the course of Theory of Computation (TOC). The results show that, the ability of problem solving among students increased effectively with more understanding level. The effectiveness of the experiment is verified by the feedback from students and the university results. It is observed that the learners can evaluate them selves for the problems using JFLAP.

Keywords


Theory of Computation, Automata Theory, Simulation, FA Design and Evaluation, Visualization.

References





DOI: https://doi.org/10.16920/jeet%2F2017%2Fv0i0%2F111735