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https://dx.doi.org/10.48550/ar...
Article . 2014
License: arXiv Non-Exclusive Distribution
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Functional Automata - Formal Languages for Computer Science Students

Authors: Marco T. Morazán; Rosario Antunez;

Functional Automata - Formal Languages for Computer Science Students

Abstract

An introductory formal languages course exposes advanced undergraduate and early graduate students to automata theory, grammars, constructive proofs, computability, and decidability. Programming students find these topics to be challenging or, in many cases, overwhelming and on the fringe of Computer Science. The existence of this perception is not completely absurd since students are asked to design and prove correct machines and grammars without being able to experiment nor get immediate feedback, which is essential in a learning context. This article puts forth the thesis that the theory of computation ought to be taught using tools for actually building computations. It describes the implementation and the classroom use of a library, FSM, designed to provide students with the opportunity to experiment and test their designs using state machines, grammars, and regular expressions. Students are able to perform random testing before proceeding with a formal proof of correctness. That is, students can test their designs much like they do in a programming course. In addition, the library easily allows students to implement the algorithms they develop as part of the constructive proofs they write. Providing students with this ability ought to be a new trend in the formal languages classroom.

In Proceedings TFPIE 2014, arXiv:1412.4738

Keywords

FOS: Computer and information sciences, Formal Languages and Automata Theory (cs.FL), Computer Science - Formal Languages and Automata Theory, QA75.5-76.95, Computer Science - Computers and Society, Electronic computers. Computer science, Computers and Society (cs.CY), QA1-939, Mathematics

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    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    15
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Average
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
15
Top 10%
Top 10%
Average
Green
gold