Communication Complexity and Parallel Computing

Size: px
Start display at page:

Download "Communication Complexity and Parallel Computing"

Transcription

1 Juraj Hromkovic Communication Complexity and Parallel Computing With 40 Figures Springer

2 Table of Contents 1 Introduction Motivation and Aims Concept and Organization How to Read the Book 6 2 Communication Protocol Models Basic Notions Introduction Alphabets, Words, and Languages Boolean Functions and Boolean Matrices Representation of Computing Problems Exercises Communication Complexity According to a Fixed Partition Definitions Methods for Proving Lower Bounds Theoretical Properties of Communication Complexity According to a Fixed Partition Exercises Research Problems Communication Complexity Introduction Definitions Lower Bound Methods Theoretical Properties of Communication Complexity Communication Complexity and Chomsky Hierarchy Exercises Research Problems One-Way Communication Complexity Introduction Definitions Methods for Proving Lower Bounds Communication Complexity Versus One-way Communication Complexity Exercises Research Problems 96

3 viii Table of Contents 2.5 Nondeterministic Communication Complexity and Randomized Protocols Introduction Nondeterministic Protocols Lower Bounds on Nondeterministic Communication Complexity Deterministic Protocols Versus Nondeterministic Protocols Randomized Protocols Randomness Versus Nondeterminism and Determinism Exercises Research problems An Improved Model of Communication Protocols Introduction Definitions Lower Bound Methods Communication Complexity Versus s-communication Complexity Some Properties of s-communication Complexity Exercises Problems Bibliographical Remarks Boolean Circuits Introduction Definitions and Fundamental Properties Introduction Boolean Circuit Models Fundamental Observations Exercises Lower Bounds on the Area of Boolean Circuits Introduction Definitions Lower Bounds on the Area Complexity Measures A Comparison of two Area Complexity Measures Three-Dimensional Layout Exercises Problems Topology of Circuits and Lower Bounds Introduction Separators Lower Bounds on Boolean Circuits with a Sublinear Separator 192

4 Table of Contents ix Circuit Structures for Which Communication Complexity Does Not Help Planar Boolean Circuits Exercises Problems Lower Bounds on the Size of Unbounded Fan-in Circuits Introduction Method of Communication Complexity of Infinite Bases Unbounded Fan-in Circuits with Sublinear Vertex-Separators Exercises Problems Lower Bounds on the Depth of Boolean Circuits Introduction Monotone Boolean Circuits Communication Complexity of Relations Characterizations of Circuit Depth by the Communication Complexity of Relations Exercises Research Problems Bibliographical Remarks 237 VLSI Circuits and Interconnection Networks Introduction Definitions Introduction A VLSI circuit Model Complexity Measures Probabilistic Models Exercises Lower Bounds on VLSI Complexity Measures Introduction Lower Bounds on Area Complexity Lower Bounds on Tradeoffs of Area and Time VLSI circuits with Special Communication Structures Exercises Problems Interconnection Networks Introduction A Model of Interconnection Networks Separators and Lower Bounds Exercises Problems 270

5 x Table of Contents 4.5 Multilective VLSI circuits Introduction and Definitions Multilectivity Versus Semilectivity Lower Bounds on Multilective VLSI programs Exercises Problems Bibliographical Remarks Sequential Computations Introduction Finite Automata Introduction Definitions One-Way Communication Complexity and Lower Bounds on the Size of Finite Automata Uniform Protocols Exercises Research Problems Turing Machines Introduction Time Complexity of Classical Turing Machines Sequential Space and Time-Space Complexity Exercises Research Problems Decision Trees and Branching Programs Introduction Definitions Capacity of Branching Programs Lower Bounds on the Depth of Decision Trees Exercises Research Problems Bibliographical Remarks. 311 References 317 Index 331

Dynamic Logic David Harel, The Weizmann Institute Dexter Kozen, Cornell University Jerzy Tiuryn, University of Warsaw The MIT Press, Cambridge, Massac

Dynamic Logic David Harel, The Weizmann Institute Dexter Kozen, Cornell University Jerzy Tiuryn, University of Warsaw The MIT Press, Cambridge, Massac Dynamic Logic David Harel, The Weizmann Institute Dexter Kozen, Cornell University Jerzy Tiuryn, University of Warsaw The MIT Press, Cambridge, Massachusetts, 2000 Among the many approaches to formal reasoning

More information

W[1]-hardness. Dániel Marx. Recent Advances in Parameterized Complexity Tel Aviv, Israel, December 3, 2017

W[1]-hardness. Dániel Marx. Recent Advances in Parameterized Complexity Tel Aviv, Israel, December 3, 2017 1 W[1]-hardness Dániel Marx Recent Advances in Parameterized Complexity Tel Aviv, Israel, December 3, 2017 2 Lower bounds So far we have seen positive results: basic algorithmic techniques for fixed-parameter

More information

Fixed Parameter Algorithms

Fixed Parameter Algorithms Fixed Parameter Algorithms Dániel Marx Tel Aviv University, Israel Open lectures for PhD students in computer science January 9, 2010, Warsaw, Poland Fixed Parameter Algorithms p.1/41 Parameterized complexity

More information

W[1]-hardness. Dániel Marx 1. Hungarian Academy of Sciences (MTA SZTAKI) Budapest, Hungary

W[1]-hardness. Dániel Marx 1. Hungarian Academy of Sciences (MTA SZTAKI) Budapest, Hungary W[1]-hardness Dániel Marx 1 1 Institute for Computer Science and Control, Hungarian Academy of Sciences (MTA SZTAKI) Budapest, Hungary School on Parameterized Algorithms and Complexity Będlewo, Poland

More information

Equivalence of NTMs and TMs

Equivalence of NTMs and TMs Equivalence of NTMs and TMs What is a Turing Machine? Similar to a finite automaton, but with unlimited and unrestricted memory. It uses an infinitely long tape as its memory which can be read from and

More information

Electronic Colloquium on Computational Complexity, Report No. 18 (1998)

Electronic Colloquium on Computational Complexity, Report No. 18 (1998) Electronic Colloquium on Computational Complexity, Report No. 18 (1998 Randomness and Nondeterminism are Incomparable for Read-Once Branching Programs Martin Sauerhoff FB Informatik, LS II, Univ. Dortmund,

More information

Nondeterministic Query Algorithms

Nondeterministic Query Algorithms Journal of Universal Computer Science, vol. 17, no. 6 (2011), 859-873 submitted: 30/7/10, accepted: 17/2/11, appeared: 28/3/11 J.UCS Nondeterministic Query Algorithms Alina Vasilieva (Faculty of Computing,

More information

Theory of Computations Spring 2016 Practice Final Exam Solutions

Theory of Computations Spring 2016 Practice Final Exam Solutions 1 of 8 Theory of Computations Spring 2016 Practice Final Exam Solutions Name: Directions: Answer the questions as well as you can. Partial credit will be given, so show your work where appropriate. Try

More information

Decidable Problems. We examine the problems for which there is an algorithm.

Decidable Problems. We examine the problems for which there is an algorithm. Decidable Problems We examine the problems for which there is an algorithm. Decidable Problems A problem asks a yes/no question about some input. The problem is decidable if there is a program that always

More information

Theory of Programming Languages COMP360

Theory of Programming Languages COMP360 Theory of Programming Languages COMP360 Sometimes it is the people no one imagines anything of, who do the things that no one can imagine Alan Turing What can be computed? Before people even built computers,

More information

Topological Structure and Analysis of Interconnection Networks

Topological Structure and Analysis of Interconnection Networks Topological Structure and Analysis of Interconnection Networks Network Theory and Applications Volume 7 Managing Editors: Ding-Zhu Du, University of Minnesota, U.S.A. and Cauligi Raghavendra, University

More information

COMP 382: Reasoning about algorithms

COMP 382: Reasoning about algorithms Spring 2015 Unit 2: Models of computation What is an algorithm? So far... An inductively defined function Limitation Doesn t capture mutation of data Imperative models of computation Computation = sequence

More information

Parameterized Complexity - an Overview

Parameterized Complexity - an Overview Parameterized Complexity - an Overview 1 / 30 Parameterized Complexity - an Overview Ue Flarup 1 flarup@imada.sdu.dk 1 Department of Mathematics and Computer Science University of Southern Denmark, Odense,

More information

Theory of Computations Spring 2016 Practice Final

Theory of Computations Spring 2016 Practice Final 1 of 6 Theory of Computations Spring 2016 Practice Final 1. True/False questions: For each part, circle either True or False. (23 points: 1 points each) a. A TM can compute anything a desktop PC can, although

More information

ECS 120 Lesson 16 Turing Machines, Pt. 2

ECS 120 Lesson 16 Turing Machines, Pt. 2 ECS 120 Lesson 16 Turing Machines, Pt. 2 Oliver Kreylos Friday, May 4th, 2001 In the last lesson, we looked at Turing Machines, their differences to finite state machines and pushdown automata, and their

More information

THE DESIGN AND ANALYSIS OF COMPUTER ALGORITHMS

THE DESIGN AND ANALYSIS OF COMPUTER ALGORITHMS 2008 AGI-Information Management Consultants May be used for personal purporses only or by libraries associated to dandelon.com network. THE DESIGN AND ANALYSIS OF COMPUTER ALGORITHMS Alfred V. Aho Bell

More information

DISCRETE MATHEMATICS

DISCRETE MATHEMATICS DISCRETE MATHEMATICS WITH APPLICATIONS THIRD EDITION SUSANNA S. EPP DePaul University THOIVISON * BROOKS/COLE Australia Canada Mexico Singapore Spain United Kingdom United States CONTENTS Chapter 1 The

More information

Theory of Languages and Automata

Theory of Languages and Automata Theory of Languages and Automata Chapter 3- The Church-Turing Thesis Sharif University of Technology Turing Machine O Several models of computing devices Finite automata Pushdown automata O Tasks that

More information

Applied Interval Analysis

Applied Interval Analysis Luc Jaulin, Michel Kieffer, Olivier Didrit and Eric Walter Applied Interval Analysis With Examples in Parameter and State Estimation, Robust Control and Robotics With 125 Figures Contents Preface Notation

More information

Course Introduction / Review of Fundamentals of Graph Theory

Course Introduction / Review of Fundamentals of Graph Theory Course Introduction / Review of Fundamentals of Graph Theory Hiroki Sayama sayama@binghamton.edu Rise of Network Science (From Barabasi 2010) 2 Network models Many discrete parts involved Classic mean-field

More information

Contents. Preface xvii Acknowledgments. CHAPTER 1 Introduction to Parallel Computing 1. CHAPTER 2 Parallel Programming Platforms 11

Contents. Preface xvii Acknowledgments. CHAPTER 1 Introduction to Parallel Computing 1. CHAPTER 2 Parallel Programming Platforms 11 Preface xvii Acknowledgments xix CHAPTER 1 Introduction to Parallel Computing 1 1.1 Motivating Parallelism 2 1.1.1 The Computational Power Argument from Transistors to FLOPS 2 1.1.2 The Memory/Disk Speed

More information

LOGIC SYNTHESIS AND VERIFICATION ALGORITHMS. Gary D. Hachtel University of Colorado. Fabio Somenzi University of Colorado.

LOGIC SYNTHESIS AND VERIFICATION ALGORITHMS. Gary D. Hachtel University of Colorado. Fabio Somenzi University of Colorado. LOGIC SYNTHESIS AND VERIFICATION ALGORITHMS by Gary D. Hachtel University of Colorado Fabio Somenzi University of Colorado Springer Contents I Introduction 1 1 Introduction 5 1.1 VLSI: Opportunity and

More information

Prove, where is known to be NP-complete. The following problems are NP-Complete:

Prove, where is known to be NP-complete. The following problems are NP-Complete: CMPSCI 601: Recall From Last Time Lecture 21 To prove is NP-complete: Prove NP. Prove, where is known to be NP-complete. The following problems are NP-Complete: SAT (Cook-Levin Theorem) 3-SAT 3-COLOR CLIQUE

More information

MATHEMATICAL STRUCTURES FOR COMPUTER SCIENCE

MATHEMATICAL STRUCTURES FOR COMPUTER SCIENCE MATHEMATICAL STRUCTURES FOR COMPUTER SCIENCE A Modern Approach to Discrete Mathematics SIXTH EDITION Judith L. Gersting University of Hawaii at Hilo W. H. Freeman and Company New York Preface Note to the

More information

Limited Automata and Unary Languages

Limited Automata and Unary Languages Limited Automata and Unary Languages Giovanni Pighizzini and Luca Prigioniero Dipartimento di Informatica, Università degli Studi di Milano, Italy {pighizzini,prigioniero}@di.unimi.it Abstract. Limited

More information

ONE-STACK AUTOMATA AS ACCEPTORS OF CONTEXT-FREE LANGUAGES *

ONE-STACK AUTOMATA AS ACCEPTORS OF CONTEXT-FREE LANGUAGES * ONE-STACK AUTOMATA AS ACCEPTORS OF CONTEXT-FREE LANGUAGES * Pradip Peter Dey, Mohammad Amin, Bhaskar Raj Sinha and Alireza Farahani National University 3678 Aero Court San Diego, CA 92123 {pdey, mamin,

More information

Learning with the Aid of an Oracle

Learning with the Aid of an Oracle ' Learning with the Aid of an Oracle (1996; Bshouty, Cleve, Gavaldà, Kannan, Tamon) CHRISTINO TAMON, Computer Science, Clarkson University, http://www.clarkson.edu/ tino Exact Learning, Boolean Circuits,

More information

Discrete Wiskunde II. Lecture 6: Planar Graphs

Discrete Wiskunde II. Lecture 6: Planar Graphs , 2009 Lecture 6: Planar Graphs University of Twente m.uetz@utwente.nl wwwhome.math.utwente.nl/~uetzm/dw/ Planar Graphs Given an undirected graph (or multigraph) G = (V, E). A planar embedding of G is

More information

TAFL 1 (ECS-403) Unit- V. 5.1 Turing Machine. 5.2 TM as computer of Integer Function

TAFL 1 (ECS-403) Unit- V. 5.1 Turing Machine. 5.2 TM as computer of Integer Function TAFL 1 (ECS-403) Unit- V 5.1 Turing Machine 5.2 TM as computer of Integer Function 5.2.1 Simulating Turing Machine by Computer 5.2.2 Simulating Computer by Turing Machine 5.3 Universal Turing Machine 5.4

More information

Finite Automata. Dr. Nadeem Akhtar. Assistant Professor Department of Computer Science & IT The Islamia University of Bahawalpur

Finite Automata. Dr. Nadeem Akhtar. Assistant Professor Department of Computer Science & IT The Islamia University of Bahawalpur Finite Automata Dr. Nadeem Akhtar Assistant Professor Department of Computer Science & IT The Islamia University of Bahawalpur PhD Laboratory IRISA-UBS University of South Brittany European University

More information

Michel Raynal. Distributed Algorithms for Message-Passing Systems

Michel Raynal. Distributed Algorithms for Message-Passing Systems Michel Raynal Distributed Algorithms for Message-Passing Systems Contents Part I Distributed Graph Algorithms 1 Basic Definitions and Network Traversal Algorithms... 3 1.1 DistributedAlgorithms... 3 1.1.1

More information

Formal languages and computation models

Formal languages and computation models Formal languages and computation models Guy Perrier Bibliography John E. Hopcroft, Rajeev Motwani, Jeffrey D. Ullman - Introduction to Automata Theory, Languages, and Computation - Addison Wesley, 2006.

More information

1. [5 points each] True or False. If the question is currently open, write O or Open.

1. [5 points each] True or False. If the question is currently open, write O or Open. University of Nevada, Las Vegas Computer Science 456/656 Spring 2018 Practice for the Final on May 9, 2018 The entire examination is 775 points. The real final will be much shorter. Name: No books, notes,

More information

Total No. of Questions : 18] [Total No. of Pages : 02. M.Sc. DEGREE EXAMINATION, DEC First Year COMPUTER SCIENCE.

Total No. of Questions : 18] [Total No. of Pages : 02. M.Sc. DEGREE EXAMINATION, DEC First Year COMPUTER SCIENCE. (DMCS01) Total No. of Questions : 18] [Total No. of Pages : 02 M.Sc. DEGREE EXAMINATION, DEC. 2016 First Year COMPUTER SCIENCE Data Structures Time : 3 Hours Maximum Marks : 70 Section - A (3 x 15 = 45)

More information

Parameterized Reductions

Parameterized Reductions 1 Fine-Grained Complexity and Algorithm Design Boot Camp Parameterized Reductions Dániel Marx Institute for Computer Science and Control, Hungarian Academy of Sciences (MTA SZTAKI) Budapest, Hungary Simons

More information

Syllabi of the Comprehensive Examination in Computer Science

Syllabi of the Comprehensive Examination in Computer Science Syllabi of the Comprehensive Examination in Computer Science The material of the comprehensive examination is drawn mostly from the undergraduate curriculum at Kuwait University and is updated to reflect

More information

Graph algorithms based on infinite automata: logical descriptions and usable constructions

Graph algorithms based on infinite automata: logical descriptions and usable constructions Graph algorithms based on infinite automata: logical descriptions and usable constructions Bruno Courcelle (joint work with Irène Durand) Bordeaux-1 University, LaBRI (CNRS laboratory) 1 Overview Algorithmic

More information

class. Moreover, so far, the problem of evaluating a Boolean formula [6] and the problem of multiplying permutations on ve points [3] (and some of the

class. Moreover, so far, the problem of evaluating a Boolean formula [6] and the problem of multiplying permutations on ve points [3] (and some of the A Note on the Hardness of Tree Isomorphism Birgit Jenner Tubingen and Ulm Pierre McKenzie Montreal and Tubingen December 5, 1997 Jacobo Toran Ulm Abstract In this note we prove that the tree isomorphism

More information

Distributed Algorithms 6.046J, Spring, Nancy Lynch

Distributed Algorithms 6.046J, Spring, Nancy Lynch Distributed Algorithms 6.046J, Spring, 205 Nancy Lynch What are Distributed Algorithms? Algorithms that run on networked processors, or on multiprocessors that share memory. They solve many kinds of problems:

More information

About the Author. Dependency Chart. Chapter 1: Logic and Sets 1. Chapter 2: Relations and Functions, Boolean Algebra, and Circuit Design

About the Author. Dependency Chart. Chapter 1: Logic and Sets 1. Chapter 2: Relations and Functions, Boolean Algebra, and Circuit Design Preface About the Author Dependency Chart xiii xix xxi Chapter 1: Logic and Sets 1 1.1: Logical Operators: Statements and Truth Values, Negations, Conjunctions, and Disjunctions, Truth Tables, Conditional

More information

Thomas H. Cormen Charles E. Leiserson Ronald L. Rivest. Introduction to Algorithms

Thomas H. Cormen Charles E. Leiserson Ronald L. Rivest. Introduction to Algorithms Thomas H. Cormen Charles E. Leiserson Ronald L. Rivest Introduction to Algorithms Preface xiii 1 Introduction 1 1.1 Algorithms 1 1.2 Analyzing algorithms 6 1.3 Designing algorithms 1 1 1.4 Summary 1 6

More information

Formal Languages and Grammars. Chapter 2: Sections 2.1 and 2.2

Formal Languages and Grammars. Chapter 2: Sections 2.1 and 2.2 Formal Languages and Grammars Chapter 2: Sections 2.1 and 2.2 Formal Languages Basis for the design and implementation of programming languages Alphabet: finite set Σ of symbols String: finite sequence

More information

Decision Properties for Context-free Languages

Decision Properties for Context-free Languages Previously: Decision Properties for Context-free Languages CMPU 240 Language Theory and Computation Fall 2018 Context-free languages Pumping Lemma for CFLs Closure properties for CFLs Today: Assignment

More information

CSE 105 THEORY OF COMPUTATION

CSE 105 THEORY OF COMPUTATION CSE 105 THEORY OF COMPUTATION Fall 2016 http://cseweb.ucsd.edu/classes/fa16/cse105-abc/ Today's learning goals Sipser sec 3.2 Describe several variants of Turing machines and informally explain why they

More information

Variants of Turing Machines

Variants of Turing Machines November 4, 2013 Robustness Robustness Robustness of a mathematical object (such as proof, definition, algorithm, method, etc.) is measured by its invariance to certain changes Robustness Robustness of

More information

More on Polynomial Time and Space

More on Polynomial Time and Space CpSc 8390 Goddard Fall15 More on Polynomial Time and Space 20.1 The Original NP-Completeness Proof A configuration/snapshot of a machine is a representation of its current state (what info would be needed

More information

Theory of Computation

Theory of Computation Theory of Computation For Computer Science & Information Technology By www.thegateacademy.com Syllabus Syllabus for Theory of Computation Regular Expressions and Finite Automata, Context-Free Grammar s

More information

Iteration Bound. Lan-Da Van ( 倫 ), Ph. D. Department of Computer Science National Chiao Tung University Taiwan, R.O.C.

Iteration Bound. Lan-Da Van ( 倫 ), Ph. D. Department of Computer Science National Chiao Tung University Taiwan, R.O.C. Iteration Bound Lan-Da Van ( 倫 ) Ph. D. Department of Computer Science National Chiao Tung University Taiwan R.O.C. Spring 27 ldvan@cs.nctu.edu.tw http://www.cs.nctu.tw/~ldvan/ Outline Introduction Data

More information

Midterm Exam II CIS 341: Foundations of Computer Science II Spring 2006, day section Prof. Marvin K. Nakayama

Midterm Exam II CIS 341: Foundations of Computer Science II Spring 2006, day section Prof. Marvin K. Nakayama Midterm Exam II CIS 341: Foundations of Computer Science II Spring 2006, day section Prof. Marvin K. Nakayama Print family (or last) name: Print given (or first) name: I have read and understand all of

More information

Fundamentals of Discrete Mathematical Structures

Fundamentals of Discrete Mathematical Structures Fundamentals of Discrete Mathematical Structures THIRD EDITION K.R. Chowdhary Campus Director JIET School of Engineering and Technology for Girls Jodhpur Delhi-110092 2015 FUNDAMENTALS OF DISCRETE MATHEMATICAL

More information

MODELING LANGUAGES AND ABSTRACT MODELS. Giovanni De Micheli Stanford University. Chapter 3 in book, please read it.

MODELING LANGUAGES AND ABSTRACT MODELS. Giovanni De Micheli Stanford University. Chapter 3 in book, please read it. MODELING LANGUAGES AND ABSTRACT MODELS Giovanni De Micheli Stanford University Chapter 3 in book, please read it. Outline Hardware modeling issues: Representations and models. Issues in hardware languages.

More information

NONDETERMINISTIC MOORE

NONDETERMINISTIC MOORE NONDETERMINISTIC MOORE AUTOMATA AND BRZOZOWSKI'S ALGORITHM G. Castiglione, A. Restivo, M. Sciortino University of Palermo Workshop PRIN Varese, 5-7 Settembre 2011 SUMMARY A class of nondeterministic Moore

More information

The Dominating Set Problem in Intersection Graphs

The Dominating Set Problem in Intersection Graphs The Dominating Set Problem in Intersection Graphs Mark de Berg Sándor Kisfaludi-Bak Gerhard Woeginger IPEC, 6 September 2017 1 / 17 Dominating Set in intersection graphs Problem (Dominating Set) Given

More information

CS2 Language Processing note 3

CS2 Language Processing note 3 CS2 Language Processing note 3 CS2Ah 5..4 CS2 Language Processing note 3 Nondeterministic finite automata In this lecture we look at nondeterministic finite automata and prove the Conversion Theorem, which

More information

1. Draw the state graphs for the finite automata which accept sets of strings composed of zeros and ones which:

1. Draw the state graphs for the finite automata which accept sets of strings composed of zeros and ones which: P R O B L E M S Finite Autom ata. Draw the state graphs for the finite automata which accept sets of strings composed of zeros and ones which: a) Are a multiple of three in length. b) End with the string

More information

SIR C R REDDY COLLEGE OF ENGINEERING

SIR C R REDDY COLLEGE OF ENGINEERING SIR C R REDDY COLLEGE OF ENGINEERING DEPARTMENT OF INFORMATION TECHNOLOGY Course Outcomes II YEAR 1 st SEMESTER Subject: Data Structures (CSE 2.1.1) 1. Describe how arrays, records, linked structures,

More information

Clustering: Overview and K-means algorithm

Clustering: Overview and K-means algorithm Clustering: Overview and K-means algorithm Informal goal Given set of objects and measure of similarity between them, group similar objects together K-Means illustrations thanks to 2006 student Martin

More information

Sublinear Algorithms Lectures 1 and 2. Sofya Raskhodnikova Penn State University

Sublinear Algorithms Lectures 1 and 2. Sofya Raskhodnikova Penn State University Sublinear Algorithms Lectures 1 and 2 Sofya Raskhodnikova Penn State University 1 Tentative Topics Introduction, examples and general techniques. Sublinear-time algorithms for graphs strings basic properties

More information

Lecture 6. Abstract Interpretation

Lecture 6. Abstract Interpretation Lecture 6. Abstract Interpretation Wei Le 2014.10 Outline Motivation History What it is: an intuitive understanding An example Steps of abstract interpretation Galois connection Narrowing and Widening

More information

Theory of Computation, Homework 3 Sample Solution

Theory of Computation, Homework 3 Sample Solution Theory of Computation, Homework 3 Sample Solution 3.8 b.) The following machine M will do: M = "On input string : 1. Scan the tape and mark the first 1 which has not been marked. If no unmarked 1 is found,

More information

ICS 252 Introduction to Computer Design

ICS 252 Introduction to Computer Design ICS 252 Introduction to Computer Design Lecture 3 Fall 2006 Eli Bozorgzadeh Computer Science Department-UCI System Model According to Abstraction level Architectural, logic and geometrical View Behavioral,

More information

List of Figures. About the Authors. Acknowledgments

List of Figures. About the Authors. Acknowledgments List of Figures Preface About the Authors Acknowledgments xiii xvii xxiii xxv 1 Compilation 1 1.1 Compilers..................................... 1 1.1.1 Programming Languages......................... 1

More information

Planar Graphs. 1 Graphs and maps. 1.1 Planarity and duality

Planar Graphs. 1 Graphs and maps. 1.1 Planarity and duality Planar Graphs In the first half of this book, we consider mostly planar graphs and their geometric representations, mostly in the plane. We start with a survey of basic results on planar graphs. This chapter

More information

Combinatorial Methods in Density Estimation

Combinatorial Methods in Density Estimation Luc Devroye Gabor Lugosi Combinatorial Methods in Density Estimation Springer Contents Preface vii 1. Introduction 1 a 1.1. References 3 2. Concentration Inequalities 4 2.1. Hoeffding's Inequality 4 2.2.

More information

Some results on Interval probe graphs

Some results on Interval probe graphs Some results on Interval probe graphs In-Jen Lin and C H Wu Department of Computer science Science National Taiwan Ocean University, Keelung, Taiwan ijlin@mail.ntou.edu.tw Abstract Interval Probe Graphs

More information

Midterm Project: L-systems in Practice and Theory

Midterm Project: L-systems in Practice and Theory Midterm Project: L-systems in Practice and Theory Joey Gonzales-Dones March 28, 2016 1 Introduction Lindenmayer systems, or L-systems, are systems for algorithmically rewriting a string of characters.

More information

Automating Construction of Lexers

Automating Construction of Lexers Automating Construction of Lexers Regular Expression to Programs Not all regular expressions are simple. How can we write a lexer for (a*b aaa)? Tokenizing aaaab Vs aaaaaa Regular Expression Finite state

More information

ECE 3060 VLSI and Advanced Digital Design

ECE 3060 VLSI and Advanced Digital Design ECE 3060 VLSI and Advanced Digital Design Lecture 16 Technology Mapping/Library Binding Outline Modeling and problem analysis Rule-based systems for library binding Algorithms for library binding structural

More information

Torben./Egidius Mogensen. Introduction. to Compiler Design. ^ Springer

Torben./Egidius Mogensen. Introduction. to Compiler Design. ^ Springer Torben./Egidius Mogensen Introduction to Compiler Design ^ Springer Contents 1 Lexical Analysis 1 1.1 Regular Expressions 2 1.1.1 Shorthands 4 1.1.2 Examples 5 1.2 Nondeterministic Finite Automata 6 1.3

More information

Part I: Preliminaries 24

Part I: Preliminaries 24 Contents Preface......................................... 15 Acknowledgements................................... 22 Part I: Preliminaries 24 1. Basics of Software Testing 25 1.1. Humans, errors, and testing.............................

More information

A Characterization of the Chomsky Hierarchy by String Turing Machines

A Characterization of the Chomsky Hierarchy by String Turing Machines A Characterization of the Chomsky Hierarchy by String Turing Machines Hans W. Lang University of Applied Sciences, Flensburg, Germany Abstract A string Turing machine is a variant of a Turing machine designed

More information

Artificial Intelligence

Artificial Intelligence Artificial Intelligence Graph theory G. Guérard Department of Nouvelles Energies Ecole Supérieur d Ingénieurs Léonard de Vinci Lecture 1 GG A.I. 1/37 Outline 1 Graph theory Undirected and directed graphs

More information

Safra's Büchi determinization algorithm

Safra's Büchi determinization algorithm Safra's Büchi determinization algorithm Aditya Oak Seminar on Automata Theory 28 Jan 2016 Introduction Proposed by S. Safra in 1988 For determinization of non-deterministic Büchi automaton Gives equivalent

More information

Semantics with Applications 3. More on Operational Semantics

Semantics with Applications 3. More on Operational Semantics Semantics with Applications 3. More on Operational Semantics Hanne Riis Nielson, Flemming Nielson (thanks to Henrik Pilegaard) [SwA] Hanne Riis Nielson, Flemming Nielson Semantics with Applications: An

More information

Department of Computer Science San Marcos, TX Report Number TXSTATE-CS-TR Ngozi I. Ihemelandu Carl J. Mueller

Department of Computer Science San Marcos, TX Report Number TXSTATE-CS-TR Ngozi I. Ihemelandu Carl J. Mueller Department of Computer Science San Marcos, TX 78666 Report Number TXSTATE-CS-TR-2011-26 THE INTRACTABILITY OF FINITE STATE MACHINE TEST SEQUENCES Ngozi I. Ihemelandu Carl J. Mueller 2011-01-03 T A B L

More information

Introduction to. Graph Theory. Second Edition. Douglas B. West. University of Illinois Urbana. ftentice iiilil PRENTICE HALL

Introduction to. Graph Theory. Second Edition. Douglas B. West. University of Illinois Urbana. ftentice iiilil PRENTICE HALL Introduction to Graph Theory Second Edition Douglas B. West University of Illinois Urbana ftentice iiilil PRENTICE HALL Upper Saddle River, NJ 07458 Contents Preface xi Chapter 1 Fundamental Concepts 1

More information

COMPUTATIONAL DYNAMICS

COMPUTATIONAL DYNAMICS COMPUTATIONAL DYNAMICS THIRD EDITION AHMED A. SHABANA Richard and Loan Hill Professor of Engineering University of Illinois at Chicago A John Wiley and Sons, Ltd., Publication COMPUTATIONAL DYNAMICS COMPUTATIONAL

More information

On the computational complexity of reachability in 2D binary images and some basic problems of 2D digital topology

On the computational complexity of reachability in 2D binary images and some basic problems of 2D digital topology Theoretical Computer Science 283 (2002) 67 108 www.elsevier.com/locate/tcs On the computational complexity of reachability in 2D binary images and some basic problems of 2D digital topology Remy Malgouyres

More information

Solid Modeling Lecture Series. Prof. Gary Wang Department of Mechanical and Manufacturing Engineering The University of Manitoba

Solid Modeling Lecture Series. Prof. Gary Wang Department of Mechanical and Manufacturing Engineering The University of Manitoba Solid Modeling 25.353 Lecture Series Prof. Gary Wang Department of Mechanical and Manufacturing Engineering The University of Manitoba Information complete, unambiguous, accurate solid model Solid Modeling

More information

ALGORITHMS EXAMINATION Department of Computer Science New York University December 17, 2007

ALGORITHMS EXAMINATION Department of Computer Science New York University December 17, 2007 ALGORITHMS EXAMINATION Department of Computer Science New York University December 17, 2007 This examination is a three hour exam. All questions carry the same weight. Answer all of the following six questions.

More information

DETERMINISTIC OPERATIONS RESEARCH

DETERMINISTIC OPERATIONS RESEARCH DETERMINISTIC OPERATIONS RESEARCH Models and Methods in Optimization Linear DAVID J. RADER, JR. Rose-Hulman Institute of Technology Department of Mathematics Terre Haute, IN WILEY A JOHN WILEY & SONS,

More information

Finite Math Linear Programming 1 May / 7

Finite Math Linear Programming 1 May / 7 Linear Programming Finite Math 1 May 2017 Finite Math Linear Programming 1 May 2017 1 / 7 General Description of Linear Programming Finite Math Linear Programming 1 May 2017 2 / 7 General Description of

More information

Some Complexity Results for Stateful Network Verification

Some Complexity Results for Stateful Network Verification Some Complexity Results for Stateful Network Verification Yaron Velner 1, Kalev Alpernas 1, Aurojit Panda 2, Alexander Rabinovich 1, Mooly Sagiv 1, Scott Shenker 2, and Sharon Shoham 3 1 Tel Aviv University,

More information

( A(x) B(x) C(x)) (A(x) A(y)) (C(x) C(y))

( A(x) B(x) C(x)) (A(x) A(y)) (C(x) C(y)) 1 Introduction Finite model theory studies the expressive power of logics on finite models. Classical model theory, on the other hand, concentrates on infinite structures: its origins are in mathematics,

More information

TECNIA INSTITUTE OF ADVANCED STUDIES

TECNIA INSTITUTE OF ADVANCED STUDIES Assignment1(UNIT1) Paper Code:MCA201 Paper: Theory of Computation (a) Positive closure. (b) Automata. Lexical analyzer. (d) Transition table. (e) Final state. Chomsky Classification. (ii) Regular Expressions.

More information

Basic Idea. The routing problem is typically solved using a twostep

Basic Idea. The routing problem is typically solved using a twostep Global Routing Basic Idea The routing problem is typically solved using a twostep approach: Global Routing Define the routing regions. Generate a tentative route for each net. Each net is assigned to a

More information

Handbook of Weighted Automata

Handbook of Weighted Automata Manfred Droste Werner Kuich Heiko Vogler Editors Handbook of Weighted Automata 4.1 Springer Contents Part I Foundations Chapter 1: Semirings and Formal Power Series Manfred Droste and Werner Kuich 3 1

More information

Pseudorandomness and Cryptographic Applications

Pseudorandomness and Cryptographic Applications Pseudorandomness and Cryptographic Applications Michael Luby PRINCETON UNIVERSITY PRESS PRINCETON, NEW JERSEY Overview and Usage Guide Mini-Courses Acknowledgments ix xiii xv Preliminaries 3 Introduction

More information

PART 1 GRAPHICAL STRUCTURE

PART 1 GRAPHICAL STRUCTURE PART 1 GRAPHICAL STRUCTURE in this web service in this web service 1 Treewidth and Hypertree Width Georg Gottlob, Gianluigi Greco, Francesco Scarcello This chapter covers methods for identifying islands

More information

CS402 - Theory of Automata Glossary By

CS402 - Theory of Automata Glossary By CS402 - Theory of Automata Glossary By Acyclic Graph : A directed graph is said to be acyclic if it contains no cycles. Algorithm : A detailed and unambiguous sequence of instructions that describes how

More information

Computer Sciences Department

Computer Sciences Department 1 Reference Book: INTRODUCTION TO THE THEORY OF COMPUTATION, SECOND EDITION, by: MICHAEL SIPSER 3 D E C I D A B I L I T Y 4 Objectives 5 Objectives investigate the power of algorithms to solve problems.

More information

Clustering: Overview and K-means algorithm

Clustering: Overview and K-means algorithm Clustering: Overview and K-means algorithm Informal goal Given set of objects and measure of similarity between them, group similar objects together K-Means illustrations thanks to 2006 student Martin

More information

4.12 Generalization. In back-propagation learning, as many training examples as possible are typically used.

4.12 Generalization. In back-propagation learning, as many training examples as possible are typically used. 1 4.12 Generalization In back-propagation learning, as many training examples as possible are typically used. It is hoped that the network so designed generalizes well. A network generalizes well when

More information

Algorithms and Parallel Computing

Algorithms and Parallel Computing Algorithms and Parallel Computing Algorithms and Parallel Computing Fayez Gebali University of Victoria, Victoria, BC A John Wiley & Sons, Inc., Publication Copyright 2011 by John Wiley & Sons, Inc. All

More information

CSCE 321/3201 Analysis and Design of Algorithms. Prof. Amr Goneid. Fall 2016

CSCE 321/3201 Analysis and Design of Algorithms. Prof. Amr Goneid. Fall 2016 CSCE 321/3201 Analysis and Design of Algorithms Prof. Amr Goneid Fall 2016 CSCE 321/3201 Analysis and Design of Algorithms Prof. Amr Goneid Course Resources Instructor: Prof. Amr Goneid E-mail: goneid@aucegypt.edu

More information

ALGORITHMIC DECIDABILITY OF COMPUTER PROGRAM-FUNCTIONS LANGUAGE PROPERTIES. Nikolay Kosovskiy

ALGORITHMIC DECIDABILITY OF COMPUTER PROGRAM-FUNCTIONS LANGUAGE PROPERTIES. Nikolay Kosovskiy International Journal Information Theories and Applications, Vol. 20, Number 2, 2013 131 ALGORITHMIC DECIDABILITY OF COMPUTER PROGRAM-FUNCTIONS LANGUAGE PROPERTIES Nikolay Kosovskiy Abstract: A mathematical

More information

(a) R=01[((10)*+111)*+0]*1 (b) ((01+10)*00)*. [8+8] 4. (a) Find the left most and right most derivations for the word abba in the grammar

(a) R=01[((10)*+111)*+0]*1 (b) ((01+10)*00)*. [8+8] 4. (a) Find the left most and right most derivations for the word abba in the grammar Code No: R05310501 Set No. 1 III B.Tech I Semester Regular Examinations, November 2008 FORMAL LANGUAGES AND AUTOMATA THEORY (Computer Science & Engineering) Time: 3 hours Max Marks: 80 Answer any FIVE

More information

Decision Problems. Observation: Many polynomial algorithms. Questions: Can we solve all problems in polynomial time? Answer: No, absolutely not.

Decision Problems. Observation: Many polynomial algorithms. Questions: Can we solve all problems in polynomial time? Answer: No, absolutely not. Decision Problems Observation: Many polynomial algorithms. Questions: Can we solve all problems in polynomial time? Answer: No, absolutely not. Definition: The class of problems that can be solved by polynomial-time

More information

COMPUTER SCIENCE/INFORMATION SYSTEMS DEGREE PLAN

COMPUTER SCIENCE/INFORMATION SYSTEMS DEGREE PLAN COMPUTER SCIENCE/INFORMATION SYSTEMS DEGREE PLAN YEAR 1, SEMESTER 1 YEAR 1, SEMESTER 2 Composition I 3 Composition II 3 Calculus I 5 Calculus II 5 Humanistic (Religion) 3 Physics I 5 Total Wellness 2 Statistics

More information

Xuandong Li. BACH: Path-oriented Reachability Checker of Linear Hybrid Automata

Xuandong Li. BACH: Path-oriented Reachability Checker of Linear Hybrid Automata BACH: Path-oriented Reachability Checker of Linear Hybrid Automata Xuandong Li Department of Computer Science and Technology, Nanjing University, P.R.China Outline Preliminary Knowledge Path-oriented Reachability

More information