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INF5: Computability & Network Technology 2004 (Computability part)
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Computability & Network Technology
Computability Part
INF5 Semester 2004

Syntax and Semantics

Course Tutors


Course Description

The goal of this course is to explain and illustrate one of the most important and fundamental facets of the world of computing --- its inherent limitations. We shall see that there are problems for which no algorithmic solution will ever exist, and realizing the existence of such inherently unsolvable problems has been one of the main achievements of 20th century science. Roughly speaking, the subject matter of the theory of computability is the precise definition of the informal concept of algorithm, and the characterization of those problems that can (or, perhaps more intriguingly, cannot) conceivably be solved by means of algorithms. In the process of having a glimpse of such a theory, we shall touch upon topics such as: The last part of the course will be devoted to a brief introduction to the theory of computational complexity. In a nutshell, one may say that, whereas computability theory is concerned with the class of problems that can or cannot be solved algorithmically, complexity theory aims at characterizing the problems for which efficient algorithmic solutions can conceivably be found. The key concept that we shall touch upon in this part of the course is that of NP-complete problem.

As an alternative, excellent description of this course I strongly recommend the preface of Computers Ltd.: What They Really Can't Do (Oxford University Press) by David Harel. This lovely little book by one of Computer Science's best expositors is highly recommended reading. (See the review of this book in Plus magazine.)


Aims of the Course

At the end of the course, the students will be able to:


Textbooks

The main textbook for this part of the course is Introduction to the Theory of Computation by Michael Sipser. The author maintains a list of errata for the current edition of this book. This book is quite expensive, but it is very well written and readable.

As supplementary reading on the science of computing as a whole, I also strongly recommend the books:

  • Algorithmics: The Spirit of Computing by David Harel. Of special relevance to this course are chapters 6-9 ibidem.

  • Computers Ltd.: What They Really Can't Do (Oxford University Press) by David Harel.


    Prerequisites

    The course assumes knowledge of basic discrete mathematics, such as the one that you have been using in the course Matematik 2B and in Algorithms and Data Structures. Those of you who would like to refresh their memory, or who are not confident about their understanding of the basic mathematics used in this course, are strongly encouraged to read, e.g., Chapter 0 of Sipser's book and/or Chapter 1 of the book Elements of the Theory of Computation (2nd edition) by Lewis and Papadimitriou. As practice makes perfect, I also recommend that you work out some of the exercises to be found in those references. Try, for example, exercises 0.2-0.5, 0.7, 0.10-0.11 in Sipser's book and/or exercises 1.1.1-1.1.4, 1.5.1-1.5.2 in the book by Lewis and Papadimitriou.

    Note: The above exercises are not really part of this course. How many you attempt to solve depends only upon your level of confidence with the mathematics that will be used as the course progresses.


    Course Material and Lecture Plan

    The course will consist of a series of 5 lectures, which will take place at 10:15 (new time) on Wednesdays in the period 8 September-8 October 2004. The location of the lectures will be room A4-108. Look at the semester calendar (inactive at the moment) for updated information on the schedule for this (and all other) courses.

    Our working language for the course will be English.

    Lecture Plan


    Exercise Classes and Advice on Modus Operandi

    As usual, each lecture will have an associated exercise class. The exercises mentioned on the web page for a lecture should be solved during the exercise class that precedes the following lecture. For example, the exercises listed on the web page for lecture 1 should be solved before lecture 2. There will be no exercise class preceding the first lecture. The exercise classes will take place in room E3-109 from about 8:15 till 10:00.

    In general, I shall give you more exercises than you might conceivably be able to solve during one exercise class. The exercises marked with a star are those that I consider more important for your understanding. All the exercises will be "doable", and working them out will greatly increase your understanding of the topics covered in the course. The best advice I can give you is to work them all out by yourselves, and to make sure you understand the solutions if the other members of your group (or me) gave you the solutions on a golden plate. Above all, don't give up if you cannot find the key to the solutions right away. Problem solving is often a matter of mental stamina as much as creativity.

    Above all, try to be critical of your solutions to the exercises. You may not need (some of) the material covered in this course in your future careers, but having an analytical and critical attitude will always help you.

    For further advice on how to learn this material (and, in fact, the material in any course) I strongly recommend that you look at the slides for the talk Psychologists' tips on how and how not to learn by Wilfrid Hodges. In particular, try to reflect upon the hints he gives, and ask yourselves how much you practice what he preaches. You might also wish to read How to Read Mathematics by Shai Simonson and Fernando Gouveau --- a collection of useful, down-to-earth tips on how to read, and learn from, mathematical texts


    Exam

    The exam will be individual and oral. Each student will be examined for at most 20 minutes on one of the topics listed in the exam prospectus that will be distributed during the last lecture. The topic will be selected randomly by each student. The student will be informed of his/her mark (on the standard 13-scale) after the oral exam. The student can choose to hold the exam in either Danish or English.

    The list of exam questions for this part of the course is as follows:

    1. Decidable and recognizable languages: Definitions and closure properties. (Read pages 127-142 in Sipser's book, and recall your solution to exercises 3.14 and 3.15. In your presentation focus on the notions of decidable and recognizable languages, their relationships and on your solutions to the exercises.)
    2. The acceptance problem for Turing machines and other undecidable problems. (Read pages 160, 165-168 and 171-175.)
    3. The complexity class P: Definition, closure properties and examples. (Read pages 225-241 in Sipser's book, and recall your solution to exercise 7.6.)
    4. The complexity class NP and the concept of NP-completeness. (Read pages 241-254 in Sipser's book.)


    This page will be actively modified over the autumn term 2004, and is currently undergoing heavy restructuring. You are invited to check it regularly during the autumn term. The page is dormant in the spring term.


    Luca Aceto, Department of Computer Science, Aalborg University.
    Last modified: .