Review for Test 2 i206 Fall 2010 John Chuang. 2 Topics  Operating System and Memory Hierarchy  Algorithm analysis and Big-O Notation  Data structures.

Slides:



Advertisements
Similar presentations
David Luebke 1 6/7/2014 CS 332: Algorithms Skip Lists Introduction to Hashing.
Advertisements

CMSC420: Skip Lists Kinga Dobolyi Based off notes by Dave Mount.
Comp 122, Spring 2004 Hash Tables – 1. hashtables - 2 Lin / Devi Comp 122, Fall 2003 Dictionary Dictionary: »Dynamic-set data structure for storing items.
Data Structures.
Intro. to Data Structures 1CSCI 3333 Data Structures - Roughly based on Chapter 6.
Computer Science 112 Fundamentals of Programming II Overview of Collections.
More on Randomized Data Structures. Motivation for Randomized Data Structures We’ve seen many data structures with good average case performance on random.
InOrder Traversal Algorithm // InOrder traversal algorithm inOrder(TreeNode n) { if (n != null) { inOrder(n.getLeft()); visit(n) inOrder(n.getRight());
Review. What to know You are responsible for all material covered in lecture, the readings, or the programming assignments There will also be some questions.
Exam Review 3 Chapters 10 – 13, 15 CSC212 Section FG CS Dept, CCNY.
CSCE 210 Data Structures and Algorithms
Data Structures: Trees i206 Fall 2010 John Chuang Some slides adapted from Marti Hearst, Brian Hayes, or Glenn Brookshear.
Midterm 2 Overview Fawzi Emad Chau-Wen Tseng Department of Computer Science University of Maryland, College Park.
Computer Organization Boolean Logic and the CPU i206 Fall 2010 John Chuang Some slides adapted from Marti Hearst, Brian Hayes, or Glenn Brookshear.
Software Design Analysis of Algorithms i206 Fall 2010 John Chuang Some slides adapted from Glenn Brookshear, Marti Hearst, or Goodrich & Tamassia.
Data Structures Heaps and Graphs i206 Fall 2010 John Chuang Some slides adapted from Marti Hearst, Brian Hayes, or Glenn Brookshear.
Overview CS113, Fall 2000 Gene Itkis. The Promise Heavy Fast-paced Challenging Rewarding.
1 Advanced Data Structures. 2 Topics Data structures (old) stack, list, array, BST (new) Trees, heaps, union-find, hash tables, spatial, string Algorithm.
Graphs & Exam Review 3 Chapter 10 – 13 CS211 CS Dept, MHC.
The Most Commonly-used Data Structures
Operating System & Memory Hierarchy i206 Fall 2010 John Chuang Some slides adapted from Glenn Brookshear, Brian Hayes, or Marti Hearst.
Course Review i206 Fall 2010 John Chuang. 2 Outline  Test 3 topics  Course review  Course evaluation.
Data Structures Hash Table (aka Dictionary) i206 Fall 2010 John Chuang Some slides adapted from Marti Hearst, Brian Hayes, Andreas Veneris, Glenn Brookshear,
Distributed Systems & Networks i206 Fall 2010 John Chuang Some slides adapted from Coulouris, Dollimore and Kindberg.
The Design and Analysis of Algorithms
Data Structures Lecture-1:Introduction
C o n f i d e n t i a l Developed By Nitendra NextHome Subject Name: Data Structure Using C Title: Overview of Data Structure.
Copyright © Wondershare Software Introduction to Data Structures Prepared by: Eng. Ahmed & Mohamed Taha.
Comp 249 Programming Methodology Chapter 15 Linked Data Structure - Part B Dr. Aiman Hanna Department of Computer Science & Software Engineering Concordia.
Chapter 3 List Stacks and Queues. Data Structures Data structure is a representation of data and the operations allowed on that data. Data structure is.
Java Collections An Introduction to Abstract Data Types, Data Structures, and Algorithms David A Watt and Deryck F Brown © 2001, D.A. Watt and D.F. Brown.
Min Chen School of Computer Science and Engineering Seoul National University Data Structure: Chapter 1.
Chapter 12 Recursion, Complexity, and Searching and Sorting
CS212: DATA STRUCTURES Lecture 1: Introduction. What is this course is about ?  Data structures : conceptual and concrete ways to organize data for efficient.
CSC 205 Java Programming II Algorithm Efficiency.
CS261 – Recitation 5 Fall Outline Assignment 3: Memory and Timing Tests Binary Search Algorithm Binary Search Tree Add/Remove examples 1.
10/20/20151 CS 3343: Analysis of Algorithms Review for final.
 DATA STRUCTURE DATA STRUCTURE  DATA STRUCTURE OPERATIONS DATA STRUCTURE OPERATIONS  BIG-O NOTATION BIG-O NOTATION  TYPES OF DATA STRUCTURE TYPES.
Review for Final Andy Wang Data Structures, Algorithms, and Generic Programming.
Nirmalya Roy School of Electrical Engineering and Computer Science Washington State University Cpt S 223 – Advanced Data Structures Course Introduction.
IT 152 Data Structures and Algorithms Tonga Institute of Higher Education.
CS Data Structures II Review & Final Exam. 2 Topics Review Final Exam.
HASHING PROJECT 1. SEARCHING DATA STRUCTURES Consider a set of data with N data items stored in some data structure We must be able to insert, delete.
Data Structures Types of Data Structure Data Structure Operations Examples Choosing Data Structures Data Structures in Alice.
Nirmalya Roy School of Electrical Engineering and Computer Science Washington State University Cpt S 223 – Advanced Data Structures Course Introduction.
Elementary Data Organization. Outline  Data, Entity and Information  Primitive data types  Non primitive data Types  Data structure  Definition 
Final Exam Tuesday, December 22nd 2:00 - 3:50pm room 102 Warren Weaver Hall.
Review for Final Exam – cs411/511 Definitions (5 questions, 2 points each) Algorithm Analysis (3 questions, 3 points each) General Questions (3 questions,
Data Structure II So Pak Yeung Outline Review  Array  Sorted Array  Linked List Binary Search Tree Heap Hash Table.
1 5. Abstract Data Structures & Algorithms 5.6 Algorithm Evaluation.
Data Structures for Midterm 2. C++ Data Structure Runtimes.
CISC220 Fall 2009 James Atlas Dec 07: Final Exam Review.
Hash Tables ADT Data Dictionary, with two operations – Insert an item, – Search for (and retrieve) an item How should we implement a data dictionary? –
CS321 Spring 2016 Lecture 3 Jan Admin A1 Due this Friday – 11:00PM Thursday = Recurrence Equations – Important. Everyone Should be added to class.
Course Introductions.  Introduction to java  Basics of Java  Classes & Objects  Java Collections and APIs  Algorithms and their analysis  Recursion.
 Saturday, April 20, 8:30-11:00am in B9201  Similar in style to written midterm exam  May include (a little) coding on paper  About 1.5 times as long.
Computer Science: A Structured Programming Approach Using C1 Objectives ❏ To introduce the basic concepts of linked lists ❏ To introduce the basic concepts.
Data Structures By Dr. Mehedi Masud ِAssociate Professor, Computer Science Dept. College of Computers and Information Systems Taif University 1.
BITS Pilani Pilani Campus Data Structure and Algorithms Design Dr. Maheswari Karthikeyan Lecture1.
COMP 103 Course Review. 2 Menu  A final word on hash collisions in Open Addressing / Probing  Course Summary  What we have covered  What you should.
FALL 2005CENG 213 Data Structures1 Review. FALL 2005CENG 213 Data Structures2 Collection of items Problems that must manage data by value. Some important.
COMP 53 – Week Eleven Hashtables.
Algorithmic Efficency
Midterm Review.
Chapter 15 Lists Objectives
CS302 Data Structures Fall 2012.
Chapter 15 Lists Objectives
CSS 342 Data Structures, Algorithms, and Discrete Mathematics I
COP3530- Data Structures Introduction
Presentation transcript:

Review for Test 2 i206 Fall 2010 John Chuang

2 Topics  Operating System and Memory Hierarchy  Algorithm analysis and Big-O Notation  Data structures -Array, linked list, list, stack, queue, dictionary, tree, graph

John Chuang3 OS and Memory Hierarchy  Data Storage: -Bit storage using transistors -Memory hierarchy -Locality of reference and caching  Operating System: -Process management -Context switch -Threads vs. processes -Synchronization and locks

John Chuang4 Algorithm Analysis  Big-O notation  Worst, best, and average case  Linear search  Binary search  Search in an array  Search in a linked list  Search in a hash table  Insertion sort  Heap sort

John Chuang5 Data Structures  What are the different types of data structures?  Which data structures are appropriate for what applications? What are the tradeoffs?  What are the key methods for each data structure? What are the effects of each method?  How are the data structures and methods implemented? What are the tradeoffs between different implementations?  What are the run-times of each method?  How are data structures used to perform sorting or searching tasks efficiently?