PPT-1 Finite Automata Reading: Chapter 2

2 Finite Automaton FA Informally a state diagram that comprehensively captures all possible states and transitions that a machine can take while responding to a stream or sequence of input symbols. Rational . A. utomata. : . a . bridge unifying . 1d and. . 2d. language. . theory. Marcella Anselmo Dora . Giammarresi. Maria . Madonia. . Univ. . . of. Salerno. . . Univ. . Roma . Great Theoretical Ideas In Computer Science. Anupam. Gupta. Danny Sleator. CS 15-251 . Fall . 2010. Lecture 20. Oct 28, 2010. Carnegie Mellon University. A machine so simple that you can understand it in less than one minute. THEORY. I. Introduction. What is Automata. Automaton and types of automata. History, Turing Machine. Why study Automata Theory. e) Applications & Uses. Dept. of Computer Science & IT, FUUAST Automata Theory . Introduce finite state automata. Able to capture state, events and dynamic behavior of “man-made systems”. Present logical properties. Textbook :. C. . Cassandras. and S. . Lafortune. , Introduction to Discrete Event Systems, Springer, 2007. Zhe. Dang. Dmitry . Dementyev. Thomas R. Fischer. William J. Hutton, III. Washington State University – Pullman, WA USA. Overview. Introduction. Mathematical foundation for computer security. The “CIA” triad. Reading: Chapter 1. 2. What is Automata Theory?. Study of abstract computing devices, or “machines”. Automaton = an abstract computing device. Note:. A “device” need not even be a physical hardware!. 29-September-2011. Modeling Temporal Behavior of Component. Component behaves with Environment. Traditional (pessimistic) approach. Environment is free to behave as it wants to. Two components are compatible if . Reading: Chapter 2. 2. Finite Automaton (FA). Informally, a state diagram that comprehensively captures all possible states and transitions that a machine can take while responding to a stream or sequence of input symbols. Ashish Srivastava. Harshil Pathak. Introduction to Probabilistic Automaton. Deterministic Probabilistic Finite Automata. Probabilistic Finite Automaton. Probably Approximately Correct (PAC) learnability. Sambhav. . Jain. IIIT Hyderabad. Think !!!. How to store a dictionary in computer?. How to search for an entry in that dictionary?. Say you have each word length exactly equal to 10 characters and can take any letter from ‘a-z’. . Characterization. of. Context-Free. . Trace. . Languages. Benedek Nagy. Friedrich Otto. Department. of Computer Science . Fachbereich. . Elektrotechnik. /. Informatik. Faculty. of . Pierre Bourhis . CNRS . CRIStAL. , Equipe LINKS. Joint . works. . with. . M.Benedikt. , . M.Krötzsch. , S. Rudolph, P. Senellart, M. Van Den Boom. 1. Querying a database . Database : a labelled graph or hypergraph. Ruby Regular Expressions. Why Learn Regular Expressions?. RegEx. are part of many programmer’s tools. vi, . grep. , PHP, Perl. They provide powerful search (via pattern matching) capabilities. Simple regex are easy, but more advanced patterns can be created as needed (use with care, may not be efficient). Learning . Objectives. At the conclusion of the chapter, the student will be able to:. Describe the components of a deterministic finite accepter (. dfa. ). State whether an input string is accepted by a dfa.