The Algorithm Design Manual

Size: px
Start display at page:

Download "The Algorithm Design Manual"

Transcription

1 Steven S. Skiena The Algorithm Design Manual With 72 Figures Includes CD-ROM THE ELECTRONIC LIBRARY OF SCIENCE

2 Contents Preface vii I TECHNIQUES Introduction to Algorithms Correctness and Efficiency Correctness Efficiency Expressing Algorithms Keeping Score The RAM Model of Computation Best, Worst, and Average-Case Complexity The Big Oh Notation Growth Rates Logarithms Modeling the Problem About the War Stories War Story: Psychic Modeling Exercises Data Structures and Sorting Fundamental Data Types Containers Dictionaries Binary Search Trees Priority Queues Specialized Data Structures Sorting Applications of Sorting

3 Approaches to Sorting Data Structures Incremental Insertion Divide and Conquer Randomization Bucketing Techniques War Story: Stripping Triangulations War Story: Mystery of the Pyramids War Story: String 'em Up Exercises Breaking Problems Down Dynamic Programming Fibonacci numbers The Partition Problem Approximate String Matching Longest Increasing Sequence Minimum Weight Triangulation Limitations of Dynamic Programming War Story: Evolution of the Lobster War Story: What's Past Is Prolog War Story: Text Compression for Bar Codes Divide and Conquer Fast Exponentiation Binary Search Square and Other Roots Exercises Graph Algorithms The Friendship Graph Data Structures for Graphs War Story: Getting the Graph Traversing a Graph Breadth-First Search Depth-First Search Applications of Graph Traversal Connected Components Tree and Cycle Detection Two-Coloring Graphs Topological Sorting Articulation Vertices

4 Contents xiii 4.6 Modeling Graph Problems Minimum Spanning Trees Prim's Algorithm Kruskal's Algorithm Shortest Paths Dijkstra's Algorithm All-Pairs Shortest Path War Story: Nothing but Nets War Story: Dialing for Documents Exercises Combinatorial Search and Heuristic Methods Backtracking Constructing All Subsets Constructing All Permutations Constructing All Paths in a Graph Search Pruning Bandwidth Minimization War Story: Covering Chessboards Heuristic Methods Simulated Annealing Neural Networks Genetic Algorithms War Story: Annealing Arrays Parallel Algorithms War Story: Going Nowhere Fast Exercises Intractable Problems and Approximations Problems and Reductions Simple Reductions Hamiltonian Cycle Independent Set and Vertex Cover Clique and Independent Set Satisfiability The Theory of NP-Completeness Satisfiability Difficult Reductions Integer Programming Vertex Cover 149

5 5 Other NP-Complete Problems The Art of Proving Hardness War Story: Hard Against the Clock Approximation Algorithms Approximating Vertex Cover The Euclidean Traveling Salesman Exercises How to Design Algorithms 163 II RESOURCES 8 A Catalog of Algorithmic Problems Data Structures Dictionaries Priority Queues Suffix Trees and Arrays Graph Data Structures Set Data Structures Kd-Trees Numerical Problems Solving Linear Equations Bandwidth Reduction Matrix Multiplication Determinants and Permanents Constrained and Unconstrained Optimization Linear Programming Random Number Generation Factoring and Primality Testing Arbitrary-Precision Arithmetic Knapsack Problem Discrete Fourier Transform Combinatorial Problems Sorting Searching Median and Selection Generating Permutations Generating Subsets Generating Partitions Generating Graphs Calendrical Calculations fob Scheduling Satisfiability 266

6 Contents xv 8.4 Graph Graph Problems: Polynomial-Time Connected Components Topological Sorting Minimum Spanning Tree Shortest Path Transitive Closure and Reduction Matching Eulerian Cycle / Chinese Postman Edge and Vertex Connectivity Network Flow Drawing Graphs Nicely Drawing Trees Planarity Detection and Embedding Problems: Hard Problems Clique Independent Set Vertex Cover Traveling Salesman Problem Hamiltonian Cycle Graph Partition Vertex Coloring Edge Coloring Graph Isomorphism Steiner Tree Feedback Edge/Vertex Set 8.6 Computational Geometry Robust Geometric Primitives Convex Hull Triangulation Voronoi Diagrams Nearest Neighbor Search Range Search Point Location Intersection Detection Bin Packing Medial-Axis Transformation Polygon Partitioning Simplifying Polygons Shape Similarity Motion Planning Maintaining Line Arrangements Minkowski Sum 8.7 Set and String Problems Set Cover Set Packing

7 8.7.3 String Matching Approximate String Matching Text Compression Cryptography Finite State Machine Minimization Longest Common Substring Shortest Common Superstring Algorithmic Resources Software Systems LEDA Netlib The Stanford GraphBase Combinatorica Algorithm Animations with XTango Programs from Books Data Sources Textbooks On-Line Resources Literature People Software Professional Consulting Services 437 Bibliography 439 Index 463

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

Computational Discrete Mathematics

Computational Discrete Mathematics Computational Discrete Mathematics Combinatorics and Graph Theory with Mathematica SRIRAM PEMMARAJU The University of Iowa STEVEN SKIENA SUNY at Stony Brook CAMBRIDGE UNIVERSITY PRESS Table of Contents

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

Analysis of Algorithms

Analysis of Algorithms Second Edition Design and Analysis of Algorithms Prabhakar Gupta Vineet Agarwal Manish Varshney Design and Analysis of ALGORITHMS SECOND EDITION PRABHAKAR GUPTA Professor, Computer Science and Engineering

More information

Introduction to Algorithms Third Edition

Introduction to Algorithms Third Edition Thomas H. Cormen Charles E. Leiserson Ronald L. Rivest Clifford Stein Introduction to Algorithms Third Edition The MIT Press Cambridge, Massachusetts London, England Preface xiü I Foundations Introduction

More information

4.1.2 Merge Sort Sorting Lower Bound Counting Sort Sorting in Practice Solving Problems by Sorting...

4.1.2 Merge Sort Sorting Lower Bound Counting Sort Sorting in Practice Solving Problems by Sorting... Contents 1 Introduction... 1 1.1 What is Competitive Programming?... 1 1.1.1 Programming Contests.... 2 1.1.2 Tips for Practicing.... 3 1.2 About This Book... 3 1.3 CSES Problem Set... 5 1.4 Other Resources...

More information

DESIGN AND ANALYSIS OF ALGORITHMS

DESIGN AND ANALYSIS OF ALGORITHMS DESIGN AND ANALYSIS OF ALGORITHMS QUESTION BANK Module 1 OBJECTIVE: Algorithms play the central role in both the science and the practice of computing. There are compelling reasons to study algorithms.

More information

CLASS: II YEAR / IV SEMESTER CSE CS 6402-DESIGN AND ANALYSIS OF ALGORITHM UNIT I INTRODUCTION

CLASS: II YEAR / IV SEMESTER CSE CS 6402-DESIGN AND ANALYSIS OF ALGORITHM UNIT I INTRODUCTION CLASS: II YEAR / IV SEMESTER CSE CS 6402-DESIGN AND ANALYSIS OF ALGORITHM UNIT I INTRODUCTION 1. What is performance measurement? 2. What is an algorithm? 3. How the algorithm is good? 4. What are the

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

Anany Levitin 3RD EDITION. Arup Kumar Bhattacharjee. mmmmm Analysis of Algorithms. Soumen Mukherjee. Introduction to TllG DCSISFI &

Anany Levitin 3RD EDITION. Arup Kumar Bhattacharjee. mmmmm Analysis of Algorithms. Soumen Mukherjee. Introduction to TllG DCSISFI & Introduction to TllG DCSISFI & mmmmm Analysis of Algorithms 3RD EDITION Anany Levitin Villa nova University International Edition contributions by Soumen Mukherjee RCC Institute of Information Technology

More information

CS-6402 DESIGN AND ANALYSIS OF ALGORITHMS

CS-6402 DESIGN AND ANALYSIS OF ALGORITHMS CS-6402 DESIGN AND ANALYSIS OF ALGORITHMS 2 marks UNIT-I 1. Define Algorithm. An algorithm is a sequence of unambiguous instructions for solving a problem in a finite amount of time. 2.Write a short note

More information

DEPARTMENT OF COMPUTER SCIENCE & ENGINEERING Question Bank Subject Name: CS6402- Design & Analysis of Algorithm Year/Sem : II/IV UNIT-I INTRODUCTION

DEPARTMENT OF COMPUTER SCIENCE & ENGINEERING Question Bank Subject Name: CS6402- Design & Analysis of Algorithm Year/Sem : II/IV UNIT-I INTRODUCTION Chendu College of Engineering & Technology (Approved by AICTE, New Delhi and Affiliated to Anna University) Zamin Endathur, Madurantakam, Kancheepuram District 603311 +91-44-27540091/92 www.ccet.org.in

More information

Algorithms and Data Structures

Algorithms and Data Structures Algorithm Analysis Page 1 - Algorithm Analysis Dr. Fall 2008 Algorithm Analysis Page 2 Outline Textbook Overview Analysis of Algorithm Pseudo-Code and Primitive Operations Growth Rate and Big-Oh Notation

More information

Chapter 9 Graph Algorithms

Chapter 9 Graph Algorithms Chapter 9 Graph Algorithms 2 Introduction graph theory useful in practice represent many real-life problems can be if not careful with data structures 3 Definitions an undirected graph G = (V, E) is a

More information

Chapter 9 Graph Algorithms

Chapter 9 Graph Algorithms Introduction graph theory useful in practice represent many real-life problems can be if not careful with data structures Chapter 9 Graph s 2 Definitions Definitions an undirected graph is a finite set

More information

Lecture 1. Introduction

Lecture 1. Introduction Lecture 1 Introduction 1 Lecture Contents 1. What is an algorithm? 2. Fundamentals of Algorithmic Problem Solving 3. Important Problem Types 4. Fundamental Data Structures 2 1. What is an Algorithm? Algorithm

More information

Chapter 9 Graph Algorithms

Chapter 9 Graph Algorithms Chapter 9 Graph Algorithms 2 Introduction graph theory useful in practice represent many real-life problems can be slow if not careful with data structures 3 Definitions an undirected graph G = (V, E)

More information

11/22/2016. Chapter 9 Graph Algorithms. Introduction. Definitions. Definitions. Definitions. Definitions

11/22/2016. Chapter 9 Graph Algorithms. Introduction. Definitions. Definitions. Definitions. Definitions Introduction Chapter 9 Graph Algorithms graph theory useful in practice represent many real-life problems can be slow if not careful with data structures 2 Definitions an undirected graph G = (V, E) is

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

Data Structures and Algorithms

Data Structures and Algorithms Berner Fachhochschule - Technik und Informatik Data Structures and Algorithms Topic 1: Algorithm Analysis Philipp Locher FS 2018 Outline Course and Textbook Overview Analysis of Algorithm Pseudo-Code and

More information

r=1 The Binomial Theorem. 4 MA095/98G Revision

r=1 The Binomial Theorem. 4 MA095/98G Revision Revision Read through the whole course once Make summary sheets of important definitions and results, you can use the following pages as a start and fill in more yourself Do all assignments again Do the

More information

Department of Computer Applications. MCA 312: Design and Analysis of Algorithms. [Part I : Medium Answer Type Questions] UNIT I

Department of Computer Applications. MCA 312: Design and Analysis of Algorithms. [Part I : Medium Answer Type Questions] UNIT I MCA 312: Design and Analysis of Algorithms [Part I : Medium Answer Type Questions] UNIT I 1) What is an Algorithm? What is the need to study Algorithms? 2) Define: a) Time Efficiency b) Space Efficiency

More information

Lecture 13. Reading: Weiss, Ch. 9, Ch 8 CSE 100, UCSD: LEC 13. Page 1 of 29

Lecture 13. Reading: Weiss, Ch. 9, Ch 8 CSE 100, UCSD: LEC 13. Page 1 of 29 Lecture 13 Connectedness in graphs Spanning trees in graphs Finding a minimal spanning tree Time costs of graph problems and NP-completeness Finding a minimal spanning tree: Prim s and Kruskal s algorithms

More information

Lecture 24: More Reductions (1997) Steven Skiena. skiena

Lecture 24: More Reductions (1997) Steven Skiena.   skiena Lecture 24: More Reductions (1997) Steven Skiena Department of Computer Science State University of New York Stony Brook, NY 11794 4400 http://www.cs.sunysb.edu/ skiena Prove that subgraph isomorphism

More information

Review for Midterm Exam

Review for Midterm Exam Review for Midterm Exam 1 Policies and Overview midterm exam policies overview of problems, algorithms, data structures overview of discrete mathematics 2 Sample Questions on the cost functions of algorithms

More information

Theorem 2.9: nearest addition algorithm

Theorem 2.9: nearest addition algorithm There are severe limits on our ability to compute near-optimal tours It is NP-complete to decide whether a given undirected =(,)has a Hamiltonian cycle An approximation algorithm for the TSP can be used

More information

Applied Combinatorics

Applied Combinatorics Applied Combinatorics SECOND EDITION FRED S. ROBERTS BARRY TESMAN LßP) CRC Press VV^ J Taylor & Francis Group Boca Raton London New York CRC Press is an imprint of the Taylor & Francis Group an informa

More information

Subject Index. Journal of Discrete Algorithms 5 (2007)

Subject Index. Journal of Discrete Algorithms 5 (2007) Journal of Discrete Algorithms 5 (2007) 751 755 www.elsevier.com/locate/jda Subject Index Ad hoc and wireless networks Ad hoc networks Admission control Algorithm ; ; A simple fast hybrid pattern-matching

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

Notation Index. Probability notation. (there exists) (such that) Fn-4 B n (Bell numbers) CL-27 s t (equivalence relation) GT-5.

Notation Index. Probability notation. (there exists) (such that) Fn-4 B n (Bell numbers) CL-27 s t (equivalence relation) GT-5. Notation Index (there exists) (for all) Fn-4 Fn-4 (such that) Fn-4 B n (Bell numbers) CL-27 s t (equivalence relation) GT-5 ( n ) k (binomial coefficient) CL-15 ( n m 1,m 2,...) (multinomial coefficient)

More information

Introductory Combinatorics

Introductory Combinatorics Introductory Combinatorics Third Edition KENNETH P. BOGART Dartmouth College,. " A Harcourt Science and Technology Company San Diego San Francisco New York Boston London Toronto Sydney Tokyo xm CONTENTS

More information

Notation Index 9 (there exists) Fn-4 8 (for all) Fn-4 3 (such that) Fn-4 B n (Bell numbers) CL-25 s ο t (equivalence relation) GT-4 n k (binomial coef

Notation Index 9 (there exists) Fn-4 8 (for all) Fn-4 3 (such that) Fn-4 B n (Bell numbers) CL-25 s ο t (equivalence relation) GT-4 n k (binomial coef Notation 9 (there exists) Fn-4 8 (for all) Fn-4 3 (such that) Fn-4 B n (Bell numbers) CL-25 s ο t (equivalence relation) GT-4 n k (binomial coefficient) CL-14 (multinomial coefficient) CL-18 n m 1 ;m 2

More information

Contents. 1 Introduction. 2 Searching and Traversal Techniques. Preface... (vii) Acknowledgements... (ix)

Contents. 1 Introduction. 2 Searching and Traversal Techniques. Preface... (vii) Acknowledgements... (ix) Contents Preface... (vii) Acknowledgements... (ix) 1 Introduction 1.1 Algorithm 1 1.2 Life Cycle of Design and Analysis of Algorithm 2 1.3 Pseudo-Code for Expressing Algorithms 5 1.4 Recursive Algorithms

More information

F. THOMSON LEIGHTON INTRODUCTION TO PARALLEL ALGORITHMS AND ARCHITECTURES: ARRAYS TREES HYPERCUBES

F. THOMSON LEIGHTON INTRODUCTION TO PARALLEL ALGORITHMS AND ARCHITECTURES: ARRAYS TREES HYPERCUBES F. THOMSON LEIGHTON INTRODUCTION TO PARALLEL ALGORITHMS AND ARCHITECTURES: ARRAYS TREES HYPERCUBES MORGAN KAUFMANN PUBLISHERS SAN MATEO, CALIFORNIA Contents Preface Organization of the Material Teaching

More information

LOGIC AND DISCRETE MATHEMATICS

LOGIC AND DISCRETE MATHEMATICS LOGIC AND DISCRETE MATHEMATICS A Computer Science Perspective WINFRIED KARL GRASSMANN Department of Computer Science University of Saskatchewan JEAN-PAUL TREMBLAY Department of Computer Science University

More information

Introduction to Combinatorial Algorithms

Introduction to Combinatorial Algorithms Fall 2009 Intro Introduction to the course What are : Combinatorial Structures? Combinatorial Algorithms? Combinatorial Problems? Combinatorial Structures Combinatorial Structures Combinatorial structures

More information

5105 BHARATHIDASAN ENGINEERING COLLEGE

5105 BHARATHIDASAN ENGINEERING COLLEGE CS 6402 DESIGN AND ANALYSIS OF ALGORITHMS II CSE/IT /IV SEMESTER UNIT I PART A 1. Design an algorithm to compute the area and circumference of a circle?(dec 2016) 2. Define recurrence relation? (Dec 2016)

More information

Lecture 3. Brute Force

Lecture 3. Brute Force Lecture 3 Brute Force 1 Lecture Contents 1. Selection Sort and Bubble Sort 2. Sequential Search and Brute-Force String Matching 3. Closest-Pair and Convex-Hull Problems by Brute Force 4. Exhaustive Search

More information

Data Structures and Algorithm Analysis in C++

Data Structures and Algorithm Analysis in C++ INTERNATIONAL EDITION Data Structures and Algorithm Analysis in C++ FOURTH EDITION Mark A. Weiss Data Structures and Algorithm Analysis in C++, International Edition Table of Contents Cover Title Contents

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

Design and Analysis of Algorithms. Comp 271. Mordecai Golin. Department of Computer Science, HKUST

Design and Analysis of Algorithms. Comp 271. Mordecai Golin. Department of Computer Science, HKUST Design and Analysis of Algorithms Revised 05/02/03 Comp 271 Mordecai Golin Department of Computer Science, HKUST Information about the Lecturer Dr. Mordecai Golin Office: 3559 Email: golin@cs.ust.hk http://www.cs.ust.hk/

More information

Problem Score Maximum MC 34 (25/17) = 50 Total 100

Problem Score Maximum MC 34 (25/17) = 50 Total 100 Stony Brook University Midterm 2 CSE 373 Analysis of Algorithms November 22, 2016 Midterm Exam Name: ID #: Signature: Circle one: GRAD / UNDERGRAD INSTRUCTIONS: This is a closed book, closed mouth exam.

More information

DESIGN AND ANALYSIS OF ALGORITHMS

DESIGN AND ANALYSIS OF ALGORITHMS QUESTION BANK DESIGN AND ANALYSIS OF ALGORITHMS UNIT1: INTRODUCTION OBJECTIVE: Algorithms play the central role in both the science and the practice of computing. There are compelling reasons to study

More information

Topic Analysis PART-A

Topic Analysis PART-A Govt. of Karnataka, Department of Technical Education Diploma in Information Science & Engineering Third Semester Subject: ANALYSIS AND DESIGN OF ALGORITHM Contact Hrs / week: Total hrs: 64 Topic Analysis

More information

INDEX. Cambridge University Press How to Think About Algorithms Jeff Edmonds Index More information

INDEX. Cambridge University Press How to Think About Algorithms Jeff Edmonds Index More information INDEX 439 abstract data type (ADT), 1, 43 exercise solutions, 414 functions vs., 43 merging with queue, 56 specifications/implementations, 44 dictionary, 47 graphs, 47 link list implementation, 51 list,

More information

15CS43: DESIGN AND ANALYSIS OF ALGORITHMS

15CS43: DESIGN AND ANALYSIS OF ALGORITHMS 15CS43: DESIGN AND ANALYSIS OF ALGORITHMS QUESTION BANK MODULE1 1. What is an algorithm? Write step by step procedure to write an algorithm. 2. What are the properties of an algorithm? Explain with an

More information

The Design of Approximation Algorithms

The Design of Approximation Algorithms The Design of Approximation Algorithms David P. Williamson Cornell University David B. Shmoys Cornell University m Щ0 CAMBRIDGE UNIVERSITY PRESS Contents Preface page ix I An Introduction to the Techniques

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

Chapter 1 Introduction

Chapter 1 Introduction Preface xv Chapter 1 Introduction 1.1 What's the Book About? 1 1.2 Mathematics Review 2 1.2.1 Exponents 3 1.2.2 Logarithms 3 1.2.3 Series 4 1.2.4 Modular Arithmetic 5 1.2.5 The P Word 6 1.3 A Brief Introduction

More information

INSTITUTE OF AERONAUTICAL ENGINEERING

INSTITUTE OF AERONAUTICAL ENGINEERING INSTITUTE OF AERONAUTICAL ENGINEERING (Autonomous) Dundigal, Hyderabad -500 043 INFORMATION TECHNOLOGY TUTORIAL QUESTION BANK Course Name : DESIGN AND ANALYSIS OF ALGORITHMS Course Code : AIT001 Class

More information

CSE 100: B+ TREE, 2-3 TREE, NP- COMPLETNESS

CSE 100: B+ TREE, 2-3 TREE, NP- COMPLETNESS CSE 100: B+ TREE, 2-3 TREE, NP- COMPLETNESS Analyzing find in B-trees Since the B-tree is perfectly height-balanced, the worst case time cost for find is O(logN) Best case: If every internal node is completely

More information

COURSE: DATA STRUCTURES USING C & C++ CODE: 05BMCAR17161 CREDITS: 05

COURSE: DATA STRUCTURES USING C & C++ CODE: 05BMCAR17161 CREDITS: 05 COURSE: DATA STRUCTURES USING C & C++ CODE: 05BMCAR17161 CREDITS: 05 Unit 1 : LINEAR DATA STRUCTURES Introduction - Abstract Data Types (ADT), Arrays and its representation Structures, Stack, Queue, Circular

More information

L.J. Institute of Engineering & Technology Semester: VIII (2016)

L.J. Institute of Engineering & Technology Semester: VIII (2016) Subject Name: Design & Analysis of Algorithm Subject Code:1810 Faculties: Mitesh Thakkar Sr. UNIT-1 Basics of Algorithms and Mathematics No 1 What is an algorithm? What do you mean by correct algorithm?

More information

( ) n 5. Test 1 - Closed Book

( ) n 5. Test 1 - Closed Book Name Test 1 - Closed Book Student ID # Multiple Choice. Write your answer to the LEFT of each problem. points each 1. During which operation on a leftist heap may subtree swaps be needed? A. DECREASE-KEY

More information

Index. stack-based, 400 A* algorithm, 325

Index. stack-based, 400 A* algorithm, 325 Index Abstract transitive closure, 174-175, 217-221 Active vertex, 411 Acyclic graph. See Digraph; Directed acyclic graph (DAG) Acyclic network, 313-321, 334-335 maxflow, 427-429 Adjacency-lists representation,

More information

CS/ENGRD 2110 Object-Oriented Programming and Data Structures Spring 2012 Thorsten Joachims. Lecture 25: Review and Open Problems

CS/ENGRD 2110 Object-Oriented Programming and Data Structures Spring 2012 Thorsten Joachims. Lecture 25: Review and Open Problems CS/ENGRD 2110 Object-Oriented Programming and Data Structures Spring 2012 Thorsten Joachims Lecture 25: Review and Open Problems Course Overview Programming Concepts Object-Oriented Programming Interfaces

More information

Ph.D. Comprehensive Examination Design and Analysis of Algorithms

Ph.D. Comprehensive Examination Design and Analysis of Algorithms Ph.D. Comprehensive Examination Design and Analysis of Algorithms Main Books 1. Cormen, Leiserton, Rivest, Introduction to Algorithms, MIT Press, 2001. Additional Books 1. Kenneth H. Rosen, Discrete mathematics

More information

Discrete Mathematics SECOND EDITION OXFORD UNIVERSITY PRESS. Norman L. Biggs. Professor of Mathematics London School of Economics University of London

Discrete Mathematics SECOND EDITION OXFORD UNIVERSITY PRESS. Norman L. Biggs. Professor of Mathematics London School of Economics University of London Discrete Mathematics SECOND EDITION Norman L. Biggs Professor of Mathematics London School of Economics University of London OXFORD UNIVERSITY PRESS Contents PART I FOUNDATIONS Statements and proofs. 1

More information

Sankalchand Patel College of Engineering - Visnagar Department of Computer Engineering and Information Technology. Assignment

Sankalchand Patel College of Engineering - Visnagar Department of Computer Engineering and Information Technology. Assignment Class: V - CE Sankalchand Patel College of Engineering - Visnagar Department of Computer Engineering and Information Technology Sub: Design and Analysis of Algorithms Analysis of Algorithm: Assignment

More information

Graph and Digraph Glossary

Graph and Digraph Glossary 1 of 15 31.1.2004 14:45 Graph and Digraph Glossary A B C D E F G H I-J K L M N O P-Q R S T U V W-Z Acyclic Graph A graph is acyclic if it contains no cycles. Adjacency Matrix A 0-1 square matrix whose

More information

Computational Geometry Overview from Cormen, et al.

Computational Geometry Overview from Cormen, et al. UMass Lowell Computer Science 91.503 Graduate Algorithms Prof. Karen Daniels Spring, 2014 Computational Geometry Overview from Cormen, et al. Chapter 33 (with additional material from other sources) 1

More information

END-TERM EXAMINATION

END-TERM EXAMINATION (Please Write your Exam Roll No. immediately) Exam. Roll No... END-TERM EXAMINATION Paper Code : MCA-205 DECEMBER 2006 Subject: Design and analysis of algorithm Time: 3 Hours Maximum Marks: 60 Note: Attempt

More information

Reference Sheet for CO142.2 Discrete Mathematics II

Reference Sheet for CO142.2 Discrete Mathematics II Reference Sheet for CO14. Discrete Mathematics II Spring 017 1 Graphs Defintions 1. Graph: set of N nodes and A arcs such that each a A is associated with an unordered pair of nodes.. Simple graph: no

More information

ECE250: Algorithms and Data Structures Final Review Course

ECE250: Algorithms and Data Structures Final Review Course ECE250: Algorithms and Data Structures Final Review Course Ladan Tahvildari, PEng, SMIEEE Professor Software Technologies Applied Research (STAR) Group Dept. of Elect. & Comp. Eng. University of Waterloo

More information

The Square Root Phenomenon in Planar Graphs

The Square Root Phenomenon in Planar Graphs 1 The Square Root Phenomenon in Planar Graphs Survey and New Results Dániel Marx Institute for Computer Science and Control, Hungarian Academy of Sciences (MTA SZTAKI) Budapest, Hungary Satisfiability

More information

9. Which situation is true regarding a cascading cut that produces c trees for a Fibonacci heap?

9. Which situation is true regarding a cascading cut that produces c trees for a Fibonacci heap? 1 1 Name Test 1 - Closed Book Student ID # Multiple Choice. Write your answer to the LEFT of each problem. points each 1. During which operation on a leftist heap may subtree swaps be needed? A. DECREASE-KEY

More information

1 Format. 2 Topics Covered. 2.1 Minimal Spanning Trees. 2.2 Union Find. 2.3 Greedy. CS 124 Quiz 2 Review 3/25/18

1 Format. 2 Topics Covered. 2.1 Minimal Spanning Trees. 2.2 Union Find. 2.3 Greedy. CS 124 Quiz 2 Review 3/25/18 CS 124 Quiz 2 Review 3/25/18 1 Format You will have 83 minutes to complete the exam. The exam may have true/false questions, multiple choice, example/counterexample problems, run-this-algorithm problems,

More information

Lecture 1 (Part 1) Introduction/Overview

Lecture 1 (Part 1) Introduction/Overview UMass Lowell Computer Science 91.503 Analysis of Algorithms Prof. Karen Daniels Fall, 2013 Lecture 1 (Part 1) Introduction/Overview Monday, 9/9/13 Web Page Web Page http://www.cs.uml.edu/~kdaniels/courses/alg_503_f13.html

More information

Virtual University of Pakistan

Virtual University of Pakistan Virtual University of Pakistan Department of Computer Science Course Outline Course Instructor Dr. Sohail Aslam E mail Course Code Course Title Credit Hours 3 Prerequisites Objectives Learning Outcomes

More information

Reductions. Linear Time Reductions. Desiderata. Reduction. Desiderata. Classify problems according to their computational requirements.

Reductions. Linear Time Reductions. Desiderata. Reduction. Desiderata. Classify problems according to their computational requirements. Desiderata Reductions Desiderata. Classify problems according to their computational requirements. Frustrating news. Huge number of fundamental problems have defied classification for decades. Desiderata'.

More information

Topic 10 Part 2 [474 marks]

Topic 10 Part 2 [474 marks] Topic Part 2 [474 marks] The complete graph H has the following cost adjacency matrix Consider the travelling salesman problem for H a By first finding a minimum spanning tree on the subgraph of H formed

More information

CAD Algorithms. Categorizing Algorithms

CAD Algorithms. Categorizing Algorithms CAD Algorithms Categorizing Algorithms Mohammad Tehranipoor ECE Department 2 September 2008 1 Categorizing Algorithms Greedy Algorithms Prim s Algorithm (Minimum Spanning Tree) A subgraph that is a tree

More information

1. [1 pt] What is the solution to the recurrence T(n) = 2T(n-1) + 1, T(1) = 1

1. [1 pt] What is the solution to the recurrence T(n) = 2T(n-1) + 1, T(1) = 1 Asymptotics, Recurrence and Basic Algorithms 1. [1 pt] What is the solution to the recurrence T(n) = 2T(n-1) + 1, T(1) = 1 1. O(logn) 2. O(n) 3. O(nlogn) 4. O(n 2 ) 5. O(2 n ) 2. [1 pt] What is the solution

More information

Dynamic Programming Homework Problems

Dynamic Programming Homework Problems CS 1510 Dynamic Programming Homework Problems 1. (2 points) Consider the recurrence relation T (0) = T (1) = 2 and for n > 1 n 1 T (n) = T (i)t (i 1) i=1 We consider the problem of computing T (n) from

More information

Search Algorithms. IE 496 Lecture 17

Search Algorithms. IE 496 Lecture 17 Search Algorithms IE 496 Lecture 17 Reading for This Lecture Primary Horowitz and Sahni, Chapter 8 Basic Search Algorithms Search Algorithms Search algorithms are fundamental techniques applied to solve

More information

Brute Force: Selection Sort

Brute Force: Selection Sort Brute Force: Intro Brute force means straightforward approach Usually based directly on problem s specs Force refers to computational power Usually not as efficient as elegant solutions Advantages: Applicable

More information

TOTAL CREDIT UNITS L T P/ S SW/F W. Course Title: Analysis & Design of Algorithm. Course Level: UG Course Code: CSE303 Credit Units: 5

TOTAL CREDIT UNITS L T P/ S SW/F W. Course Title: Analysis & Design of Algorithm. Course Level: UG Course Code: CSE303 Credit Units: 5 Course Title: Analysis & Design of Algorithm Course Level: UG Course Code: CSE303 Credit Units: 5 L T P/ S SW/F W TOTAL CREDIT UNITS 3 1 2-5 Course Objectives: The designing of algorithm is an important

More information

COS 226 Final Exam, Spring 2009

COS 226 Final Exam, Spring 2009 NAME: login ID: precept #: COS 226 Final Exam, Spring 2009 This test is 16 questions, weighted as indicated. The exam is closed book, except that you are allowed to use a one page cheatsheet. No calculators

More information

Elementary maths for GMT. Algorithm analysis Part II

Elementary maths for GMT. Algorithm analysis Part II Elementary maths for GMT Algorithm analysis Part II Algorithms, Big-Oh and Big-Omega An algorithm has a O( ) and Ω( ) running time By default, we mean the worst case running time A worst case O running

More information

APPROXIMATION ALGORITHMS FOR GEOMETRIC PROBLEMS

APPROXIMATION ALGORITHMS FOR GEOMETRIC PROBLEMS APPROXIMATION ALGORITHMS FOR GEOMETRIC PROBLEMS Subhas C. Nandy (nandysc@isical.ac.in) Advanced Computing and Microelectronics Unit Indian Statistical Institute Kolkata 70010, India. Organization Introduction

More information

Course Review for Finals. Cpt S 223 Fall 2008

Course Review for Finals. Cpt S 223 Fall 2008 Course Review for Finals Cpt S 223 Fall 2008 1 Course Overview Introduction to advanced data structures Algorithmic asymptotic analysis Programming data structures Program design based on performance i.e.,

More information

Algorithm Design Techniques. Hwansoo Han

Algorithm Design Techniques. Hwansoo Han Algorithm Design Techniques Hwansoo Han Algorithm Design General techniques to yield effective algorithms Divide-and-Conquer Dynamic programming Greedy techniques Backtracking Local search 2 Divide-and-Conquer

More information

Heuristic Search. Theory and Applications. Stefan Edelkamp. Stefan Schrodl ELSEVIER. Morgan Kaufmann is an imprint of Elsevier HEIDELBERG LONDON

Heuristic Search. Theory and Applications. Stefan Edelkamp. Stefan Schrodl ELSEVIER. Morgan Kaufmann is an imprint of Elsevier HEIDELBERG LONDON Heuristic Search Theory and Applications Stefan Edelkamp Stefan Schrodl AMSTERDAM BOSTON HEIDELBERG LONDON ELSEVIER NEW YORK OXFORD PARIS SAN DIEGO SAN FRANCISCO SINGAPORE SYDNEY» TOKYO Morgan Kaufmann

More information

R13. II B. Tech I Semester Supplementary Examinations, May/June DATA STRUCTURES (Com. to ECE, CSE, EIE, IT, ECC)

R13. II B. Tech I Semester Supplementary Examinations, May/June DATA STRUCTURES (Com. to ECE, CSE, EIE, IT, ECC) SET - 1 II B. Tech I Semester Supplementary Examinations, May/June - 2016 PART A 1. a) Write a procedure for the Tower of Hanoi problem? b) What you mean by enqueue and dequeue operations in a queue? c)

More information

CS521 \ Notes for the Final Exam

CS521 \ Notes for the Final Exam CS521 \ Notes for final exam 1 Ariel Stolerman Asymptotic Notations: CS521 \ Notes for the Final Exam Notation Definition Limit Big-O ( ) Small-o ( ) Big- ( ) Small- ( ) Big- ( ) Notes: ( ) ( ) ( ) ( )

More information

2. (a) Explain when the Quick sort is preferred to merge sort and vice-versa.

2. (a) Explain when the Quick sort is preferred to merge sort and vice-versa. Code No: RR210504 Set No. 1 1. (a) Order the following functions according to their order of growth (from the lowest to the highest). (n-2)!, 5 log (n+100) 10,2 2n, 0.001n 4 +3n 3 +1, ln 2 n, n 1/3, 3

More information

Steven Skiena. skiena

Steven Skiena.   skiena Lecture 12: Examples of Dynamic Programming (1997) Steven Skiena Department of Computer Science State University of New York Stony Brook, NY 11794 4400 http://www.cs.sunysb.edu/ skiena Give an O(n 2 )

More information

Coping with the Limitations of Algorithm Power Exact Solution Strategies Backtracking Backtracking : A Scenario

Coping with the Limitations of Algorithm Power Exact Solution Strategies Backtracking Backtracking : A Scenario Coping with the Limitations of Algorithm Power Tackling Difficult Combinatorial Problems There are two principal approaches to tackling difficult combinatorial problems (NP-hard problems): Use a strategy

More information

Algorithms and Data Structures CS-CO-412

Algorithms and Data Structures CS-CO-412 Algorithms and Data Structures CS-CO-412 David Vernon Professor of Informatics University of Skövde Sweden david@vernon.eu www.vernon.eu Algorithms and Data Structures 1 Copyright D. Vernon 2014 Course

More information

Department of Computer Science & Engineering University of Kalyani. Syllabus for Ph.D. Coursework

Department of Computer Science & Engineering University of Kalyani. Syllabus for Ph.D. Coursework Department of Computer Science & Engineering University of Kalyani Syllabus for Ph.D. Coursework Paper 1: A) Literature Review: (Marks - 25) B) Research Methodology: (Marks - 25) Paper 2: Computer Applications:

More information

Jörgen Bang-Jensen and Gregory Gutin. Digraphs. Theory, Algorithms and Applications. Springer

Jörgen Bang-Jensen and Gregory Gutin. Digraphs. Theory, Algorithms and Applications. Springer Jörgen Bang-Jensen and Gregory Gutin Digraphs Theory, Algorithms and Applications Springer Contents 1. Basic Terminology, Notation and Results 1 1.1 Sets, Subsets, Matrices and Vectors 1 1.2 Digraphs,

More information

Model Answer. Section A Q.1 - (20 1=10) B.Tech. (Fifth Semester) Examination Analysis and Design of Algorithm (IT3105N) (Information Technology)

Model Answer. Section A Q.1 - (20 1=10) B.Tech. (Fifth Semester) Examination Analysis and Design of Algorithm (IT3105N) (Information Technology) B.Tech. (Fifth Semester) Examination 2013 Analysis and Design of Algorithm (IT3105N) (Information Technology) Model Answer. Section A Q.1 - (20 1=10) 1. Merge Sort uses approach to algorithm design. Ans:

More information

Geometric data structures:

Geometric data structures: Geometric data structures: Machine Learning for Big Data CSE547/STAT548, University of Washington Sham Kakade Sham Kakade 2017 1 Announcements: HW3 posted Today: Review: LSH for Euclidean distance Other

More information

CS6702 GRAPH THEORY AND APPLICATIONS QUESTION BANK

CS6702 GRAPH THEORY AND APPLICATIONS QUESTION BANK CS6702 GRAPH THEORY AND APPLICATIONS 2 MARKS QUESTIONS AND ANSWERS 1 UNIT I INTRODUCTION CS6702 GRAPH THEORY AND APPLICATIONS QUESTION BANK 1. Define Graph. 2. Define Simple graph. 3. Write few problems

More information

B553 Lecture 12: Global Optimization

B553 Lecture 12: Global Optimization B553 Lecture 12: Global Optimization Kris Hauser February 20, 2012 Most of the techniques we have examined in prior lectures only deal with local optimization, so that we can only guarantee convergence

More information

Contents. CS 124 Final Exam Practice Problem 5/6/17. 1 Format and Logistics 2

Contents. CS 124 Final Exam Practice Problem 5/6/17. 1 Format and Logistics 2 CS 124 Final Exam Practice Problem 5/6/17 Contents 1 Format and Logistics 2 2 Topics Covered 2 2.1 Math Fundamentals.................................... 2 2.2 Graph Search........................................

More information

PATH FINDING AND GRAPH TRAVERSAL

PATH FINDING AND GRAPH TRAVERSAL GRAPH TRAVERSAL PATH FINDING AND GRAPH TRAVERSAL Path finding refers to determining the shortest path between two vertices in a graph. We discussed the Floyd Warshall algorithm previously, but you may

More information

Table of Contents. Chapter 1: Introduction to Data Structures... 1

Table of Contents. Chapter 1: Introduction to Data Structures... 1 Table of Contents Chapter 1: Introduction to Data Structures... 1 1.1 Data Types in C++... 2 Integer Types... 2 Character Types... 3 Floating-point Types... 3 Variables Names... 4 1.2 Arrays... 4 Extraction

More information

D.K.M.COLLEGE FOR WOMEN (AUTONOMOUS), VELLORE-1.

D.K.M.COLLEGE FOR WOMEN (AUTONOMOUS), VELLORE-1. D.K.M.COLLEGE FOR WOMEN (AUTONOMOUS), VELLORE-1. DESIGN AND ANALYSIS OF ALGORITHM UNIT- I SECTION-A 2 MARKS 1. Define an algorithm? 2. Specify the criteria of algorithm? 3. What is Computational Procedure?

More information

CLASSIC DATA STRUCTURES IN JAVA

CLASSIC DATA STRUCTURES IN JAVA CLASSIC DATA STRUCTURES IN JAVA Timothy Budd Oregon State University Boston San Francisco New York London Toronto Sydney Tokyo Singapore Madrid Mexico City Munich Paris Cape Town Hong Kong Montreal CONTENTS

More information