1. 1 Welcome to CptS 317 Background Course Outline Textbook Syllabus (see class web site to important information on disabilities, cheating and safety) Grades

2. Nuts and Bolts 2 CptS 317 Automata Theory, Languages and Computation Fall 2014 Instructor: John Miller, West 134E jhmiller@tricity.wsu.edu Class web page can be found at http://www/tricity.wsu.edu/~jhmiller

3. 3 Background uIn 1930s A.Turing studied abstract machines (Turing machine) with properties like modern computers. uHis objective was to discover what computers could and could not do. uThis subject now called “deciability” uIf problem can be solved by computer, it is “decidable”

4. 4 Background (2) uIn 40s and 50s, simple machines called “finite automata” were studied as models of brain function. uAlthough not good brain models, they turned out to be useful for other reasons. uIn 1950s, N. Chomsky introduced the concept of “grammars” that is closely related to finite automata.

5. 5 Background (3) uIn 1969 S. Cook extended Turing work. uHe devised ways to separate computer problems into those that could be solved efficiently (tractable) from those that took so much time that computers are useless (intractable or NP-hard). uCptS 317 is about these classical issues in the theory of computing.

6. 6 Course Outline uRegular Languages and their descriptors: wFinite automata, nondeterministic finite automata, regular expressions. wAlgorithms to decide questions about regular languages, e.g., is it empty? wClosure properties of regular languages.

7. 7 Course Outline – (2) uContext-free languages and their descriptors: wContext-free grammars, pushdown automata. wDecision and closure properties.

8. 8 Course Outline – (3) uRecursive and recursively enumerable languages. wTuring machines, decidability of problems. wThe limit of what can be computed. uIntractable problems. wProblems that (appear to) require exponential time. wNP-completeness and beyond.

9. 9 Text uIntroduction to Automata Theory, Languages, and Computation 3 rd Edition, Hopcroft, Motwani, Ullman,

10. 10 Likely course content Chapter 1: Introduction Chapter 2: Finite Automata Chapter 3: Regular Expressions and Languages Chapter 4: Properties of Regular Languages Midterm exam Chapter 5: Context-Free Grammars and Languages Chapter 6: Pushdown Automata Chapter 7: Properties of Context-Free Languages Chapter 8: Introduction to Turing Machines Final exam

11. 11 Grades uHomework 25% uWeekly quizzes 25%: uMidterm exam 25% uFinal exam 25%

12. 12 Comments About Homework uThe intent is that everyone will get homework 100% correct. uYou are allowed to try as many times as you like. wOnly the last try counts. uDon’t be afraid to guess and try again. uYou’ll get some advice if you make a mistake.

13. 13 Quizzes: when and why uEnd of class on Fridays wQuestions about the material covered in during that week wOpen textbook and lecture slides uReward students who come to class, read text and review lecture slides

14. 14 Why Study Automata? uFinite automata are models for protocols, electronic circuits, etc. uRegular expressions are essential for all types of computing uContext-free grammars are used to describe the syntax of almost every programming language.

15. 15 Why? – (2) uWhen developing solutions to real problems, we often confront the limitations of what software can do. wUndecidable things no program can do wIntractable things programs can do but but no fast programs exist.

16. 16 Practical Application u“Intractable” problems should not be addressed “head on” (i.e. write code based on rigorous step-by-step method) uLook for an approximate method uTry “heuristic” approach (likely to give the correct answer by no guarantee)

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18. 18 Gradiance Problems uThe “class token” is 8E58F2FF. uRegister it at www.gradiance.com/service uSee Texts p35 for discussion and 1 st set of problems uPearson no longer supports Gradiance uJeffery Ullman offers service free of charge uFind Ullman’s online course at infolab.stanford.edu/~ullman/ialc.html uMy lecture slides were developed from his