Quick Sort. Implementation
|
|
|
- Helen Bond
- 10 years ago
- Views:
Transcription
1 Implementation Next, recall that our goal is to partition all remaining elements based on whether they are smaller than or greater than the pivot We will find two entries: One larger than the pivot (staring from the front) One smaller than the pivot (starting from the back) which are out of order and then correct the ordering I.e., swap them 1
2 Implementation Continue doing so until the appropriate entries you find are actually in order The index to the larger entry we found would be the first large entry in the list (as seen from the left) Therefore, we could move this entry into the last entry of the list We can fill this spot with the pivot 2
3 Example First, we examine the first, middle, and last entries of the full list The span below will indicate which list we are currently sorting 3
4 Example We select 57 to be our pivot We move 24 into the first location 4
5 Example Starting at the 2 nd and 2 nd -last locations: we search forward until we find 70 > 57 we search backward until we find 49 < 57 5
6 Example We swap 70 and 49, placing them in order with respect to eachother 6
7 Example We search forward until we find 97 > 57 We search backward until we find 16 < 57 7
8 Example We swap 16 and 97 which are now in order with respect to each other 8
9 Example We search forward until we find 63 > 57 We search backward until we find 55 < 57 9
10 Example We swap 63 and 55 10
11 Example We search forward until we find 85 > 57 We search backward until we find 36 < 57 11
12 Example We swap 85 and 36, placing them in order with respect to each other 12
13 Example We search forward until we find 68 > 57 We search backward until we find 9 < 57 13
14 Example We swap 68 and 9 14
15 Example We search forward until we find 76 > 57 We search backward until we find 9 < 57 The indices are out of order, so we stop 15
16 Example We move the larger indexed item to the vacancy at the end of the array We fill the empty location with the pivot, 57 The pivot is now in the correct location 16
17 Example We will now recursively call quick sort on the first half of the list When we are finished, all entries < 57 will be sorted 17
18 Example We examine the first, middle, and last elements of this sub list 18
19 Example We choose 24 to be our pivot We move 9 into the first location in this sub-list 19
20 Example We search forward until we find 49 > 24 We search backward until we find 21 < 24 20
21 Example We swap 49 and 21, placing them in order with respect to eachother 21
22 Example We search forward until we find 38 > 24 We search backward until we find 16 < 24 The indices are reversed, so we stop 22
23 Example We move 38 to the vacant location and move the pivot 24 into the location previously occupied by is now in the correct location 23
24 Example We will now recursively call quick sort on the left and right halves of those entries which are < 57 24
25 Example The first partition has three entries, so we sort it using insertion sort 25
26 Example The second partition also has only four entries, so again, we use insertion sort 26
27 Example First we examine the first, middle, and last entries of the sub-list 27
28 Example We choose 74 to be our pivot We move 76 to the vacancy left by 74 28
29 Example We search forward until we find 81 > 74 We search backward until we find 70 < 74 29
30 Example We swap 70 and 84 placing them in order 30
31 Example We search forward until we find 85 > 74 We search backward until we find 61 < 74 31
32 Example We swap 85 and 61 placing them in order 32
33 Example We search forward until we find 79 > 74 We search backward until we find 63 < 74 The indices are reversed, so we stop 33
34 Example We move 79 to the vacant location and move the pivot 74 into the location previously occupied by is now in the correct location 34
35 Example We sort the left sub-list first It has four elements, so we simply use insertion sort 35
36 Example Having sorted the four elements, we focus on the remaining sub-list of seven entries 36
37 Example To sort the next sub-list, we examine the first, middle, and last entries 37
38 Example We select 79 as our pivot and move: 76 into the lowest position 85 into the highest position 38
39 Example We search forward until we find 85 > 79 We search backward until we find 77 < 79 39
40 Example We swap 85 and 77, placing them in order 40
41 Example We search forward until we find 97 > 79 We search backward until we find 77 < 79 The indices are reversed, so we stop 41
42 Example Finally, we move 97 to the vacant location and copy 79 into the appropriate location 79 is now in the correct location 42
43 Example This splits the sub-list into two sub-lists of size 2 and 4 We use insertion sort for the first sub-list 43
44 Example We are left with one sub-list with four entries, so again, we use insertion sort 44
45 Example Sorting the last sub-list, we arrive at an ordered list 45
CSC148 Lecture 8. Algorithm Analysis Binary Search Sorting
CSC148 Lecture 8 Algorithm Analysis Binary Search Sorting Algorithm Analysis Recall definition of Big Oh: We say a function f(n) is O(g(n)) if there exists positive constants c,b such that f(n)
APP INVENTOR. Test Review
APP INVENTOR Test Review Main Concepts App Inventor Lists Creating Random Numbers Variables Searching and Sorting Data Linear Search Binary Search Selection Sort Quick Sort Abstraction Modulus Division
South East of Process Main Building / 1F. North East of Process Main Building / 1F. At 14:05 April 16, 2011. Sample not collected
At 14:05 April 16, 2011 At 13:55 April 16, 2011 At 14:20 April 16, 2011 ND ND 3.6E-01 ND ND 3.6E-01 1.3E-01 9.1E-02 5.0E-01 ND 3.7E-02 4.5E-01 ND ND 2.2E-02 ND 3.3E-02 4.5E-01 At 11:37 April 17, 2011 At
Binary Heaps * * * * * * * / / \ / \ / \ / \ / \ * * * * * * * * * * * / / \ / \ / / \ / \ * * * * * * * * * *
Binary Heaps A binary heap is another data structure. It implements a priority queue. Priority Queue has the following operations: isempty add (with priority) remove (highest priority) peek (at highest
6. Standard Algorithms
6. Standard Algorithms The algorithms we will examine perform Searching and Sorting. 6.1 Searching Algorithms Two algorithms will be studied. These are: 6.1.1. inear Search The inear Search The Binary
Sorting revisited. Build the binary search tree: O(n^2) Traverse the binary tree: O(n) Total: O(n^2) + O(n) = O(n^2)
Sorting revisited How did we use a binary search tree to sort an array of elements? Tree Sort Algorithm Given: An array of elements to sort 1. Build a binary search tree out of the elements 2. Traverse
Analysis of Binary Search algorithm and Selection Sort algorithm
Analysis of Binary Search algorithm and Selection Sort algorithm In this section we shall take up two representative problems in computer science, work out the algorithms based on the best strategy to
Data Structures and Data Manipulation
Data Structures and Data Manipulation What the Specification Says: Explain how static data structures may be used to implement dynamic data structures; Describe algorithms for the insertion, retrieval
Binary Heap Algorithms
CS Data Structures and Algorithms Lecture Slides Wednesday, April 5, 2009 Glenn G. Chappell Department of Computer Science University of Alaska Fairbanks [email protected] 2005 2009 Glenn G. Chappell
Converting a Number from Decimal to Binary
Converting a Number from Decimal to Binary Convert nonnegative integer in decimal format (base 10) into equivalent binary number (base 2) Rightmost bit of x Remainder of x after division by two Recursive
Big Data and Scripting. Part 4: Memory Hierarchies
1, Big Data and Scripting Part 4: Memory Hierarchies 2, Model and Definitions memory size: M machine words total storage (on disk) of N elements (N is very large) disk size unlimited (for our considerations)
Chapter 7: Sequential Data Structures
Java by Definition Chapter 7: Sequential Data Structures Page 1 of 112 Chapter 7: Sequential Data Structures We have so far explored the basic features of the Java language, including an overview of objectoriented
Lecture 2 February 12, 2003
6.897: Advanced Data Structures Spring 003 Prof. Erik Demaine Lecture February, 003 Scribe: Jeff Lindy Overview In the last lecture we considered the successor problem for a bounded universe of size u.
Binary search algorithm
Binary search algorithm Definition Search a sorted array by repeatedly dividing the search interval in half. Begin with an interval covering the whole array. If the value of the search key is less than
Sense of Number. Basic Edition for. October 2014. Graphic Design by Dave Godfrey Compiled by the Sense of Number Maths Team
Sense of Number Basic Edition for October 2014 Graphic Design by Dave Godfrey Compiled by the Sense of Number Maths Team For sole use within. A picture is worth 1000 words! www.senseofnumber.co.uk The
+ Addition + Tips for mental / oral session 1 Early addition. Combining groups of objects to find the total. Then adding on to a set, one by one
+ Addition + We encourage children to use mental methods whenever possible Children may not need to be taught every step STEP Tips for mental / oral session Counting Concept & images Comments Early addition
Heaps & Priority Queues in the C++ STL 2-3 Trees
Heaps & Priority Queues in the C++ STL 2-3 Trees CS 3 Data Structures and Algorithms Lecture Slides Friday, April 7, 2009 Glenn G. Chappell Department of Computer Science University of Alaska Fairbanks
Sorting Algorithms. Nelson Padua-Perez Bill Pugh. Department of Computer Science University of Maryland, College Park
Sorting Algorithms Nelson Padua-Perez Bill Pugh Department of Computer Science University of Maryland, College Park Overview Comparison sort Bubble sort Selection sort Tree sort Heap sort Quick sort Merge
MATHEMATICS Unit Decision 1
General Certificate of Education January 2008 Advanced Subsidiary Examination MATHEMATICS Unit Decision 1 MD01 Tuesday 15 January 2008 9.00 am to 10.30 am For this paper you must have: an 8-page answer
Load Balancing Techniques
Load Balancing Techniques 1 Lecture Outline Following Topics will be discussed Static Load Balancing Dynamic Load Balancing Mapping for load balancing Minimizing Interaction 2 1 Load Balancing Techniques
Algorithm Design and Recursion
Chapter 13 Algorithm Design and Recursion Objectives To understand basic techniques for analyzing the efficiency of algorithms. To know what searching is and understand the algorithms for linear and binary
AIP Factoring Practice/Help
The following pages include many problems to practice factoring skills. There are also several activities with examples to help you with factoring if you feel like you are not proficient with it. There
Algorithms and Data Structures
Algorithms and Data Structures Part 2: Data Structures PD Dr. rer. nat. habil. Ralf-Peter Mundani Computation in Engineering (CiE) Summer Term 2016 Overview general linked lists stacks queues trees 2 2
Outline BST Operations Worst case Average case Balancing AVL Red-black B-trees. Binary Search Trees. Lecturer: Georgy Gimel farb
Binary Search Trees Lecturer: Georgy Gimel farb COMPSCI 220 Algorithms and Data Structures 1 / 27 1 Properties of Binary Search Trees 2 Basic BST operations The worst-case time complexity of BST operations
RALLY SIGNS AND DESCRIPTIONS. The principal parts of the exercises are boldface and underlined.
RALLY SIGNS AND DESCRIPTIONS Designated wording and symbols for rally signs Judges may use duplicates of stations marked with an asterisk in designing their courses. The principal parts of the exercises
CA-6050 Solar Power Unit. User Guide. Designed to work with the Norsonic range of sound level meters to provide a DC supply in remote locations.
CA-6050 Solar Power Unit User Guide Designed to work with the Norsonic range of sound level meters to provide a DC supply in remote locations. 1 Contents Introduction... 2 Components... 3 Solar Array Case...
Class : MAC 286. Data Structure. Research Paper on Sorting Algorithms
Name : Jariya Phongsai Class : MAC 286. Data Structure Research Paper on Sorting Algorithms Prof. Lawrence Muller Date : October 26, 2009 Introduction In computer science, a ing algorithm is an efficient
root node level: internal node edge leaf node CS@VT Data Structures & Algorithms 2000-2009 McQuain
inary Trees 1 A binary tree is either empty, or it consists of a node called the root together with two binary trees called the left subtree and the right subtree of the root, which are disjoint from each
5/4/2011. Overview. Claim Drafting. Patent Claims: Example. Patent Claims. Patent Claims 1. Patent Claims 2
Overview Claim Drafting Claim types in computing arts context System/device claims Method claims Computer-readable media claims Claiming to hit the target Joint infringement issues End-user claims and
SiS 180 S-ATA User s Manual. Quick User s Guide. Version 0.1
SiS 180 S-ATA User s Manual Quick User s Guide Version 0.1 Edition April 2003 Copyright Trademarks SiS is a registered trademark of Silicon Integrated Systems Corp. All brand or product names mentioned
Home Page. Data Structures. Title Page. Page 1 of 24. Go Back. Full Screen. Close. Quit
Data Structures Page 1 of 24 A.1. Arrays (Vectors) n-element vector start address + ielementsize 0 +1 +2 +3 +4... +n-1 start address continuous memory block static, if size is known at compile time dynamic,
Zabin Visram Room CS115 CS126 Searching. Binary Search
Zabin Visram Room CS115 CS126 Searching Binary Search Binary Search Sequential search is not efficient for large lists as it searches half the list, on average Another search algorithm Binary search Very
Dalhousie University CSCI 2132 Software Development Winter 2015 Lab 7, March 11
Dalhousie University CSCI 2132 Software Development Winter 2015 Lab 7, March 11 In this lab, you will first learn how to use pointers to print memory addresses of variables. After that, you will learn
1) The postfix expression for the infix expression A+B*(C+D)/F+D*E is ABCD+*F/DE*++
Answer the following 1) The postfix expression for the infix expression A+B*(C+D)/F+D*E is ABCD+*F/DE*++ 2) Which data structure is needed to convert infix notations to postfix notations? Stack 3) The
Summary Of Mental Maths Targets EYFS Yr 6. Year 3. Count from 0 in multiples of 4 & 8, 50 & 100. Count back in 100s, 10s, 1s eg.
Autumn 1 Say the number names in order to 10. Read and write from 1 to 20 in numerals and words. Count in steps of 2, 3, and 5 from 0, and in tens from any number, forward and backward. Count from 0 in
Data Structures Using C++ 2E. Chapter 5 Linked Lists
Data Structures Using C++ 2E Chapter 5 Linked Lists Doubly Linked Lists Traversed in either direction Typical operations Initialize the list Destroy the list Determine if list empty Search list for a given
Tasks to Move Students On
Maths for Learning Inclusion Tasks to Move Students On Part 1 Maths for Learning Inclusion (M4LI) Tasks to Move Students On Numbers 1 10 Structuring Number Maths for Learning Inclusion (M4LI) Tasks to
Read and React Offense Drills
Read and React Offense Drills Table of Contents. Foundation: PASS & CUT. Foundation: POST-PASS & CUT (North-South) 6. Foundation: DRIBBLE-AT 7 4. Circle Movement: Dribble Penetration 8 5. Basic Post Slides
Junior Assessment of Mathematics (JAM)
Junior Assessment of Mathematics (JAM) Student Response record sheet Child s Name: Room: Date of birth: Module One: Number (Additive Strategies) 0-1 - Pre Level 1 2-3 - Early Level 1 4 - At Level 1 Early
Multiplication. Year 1 multiply with concrete objects, arrays and pictorial representations
Year 1 multiply with concrete objects, arrays and pictorial representations Children will experience equal groups of objects and will count in 2s and 10s and begin to count in 5s. They will work on practical
SharePoint. Site Owner s Manual. Please send feedback or suggestions for updates to the following email address [email protected].
SharePoint Site Owner s Manual Please send feedback or suggestions for updates to the following email address [email protected] London School of Economics & Political Science lse.ac.uk/imt/training
CHAPTER 6: ANALYZE MICROSOFT DYNAMICS NAV 5.0 DATA IN MICROSOFT EXCEL
Chapter 6: Analyze Microsoft Dynamics NAV 5.0 Data in Microsoft Excel CHAPTER 6: ANALYZE MICROSOFT DYNAMICS NAV 5.0 DATA IN MICROSOFT EXCEL Objectives The objectives are: Explain the process of exporting
& Data Processing 2. Exercise 3: Memory Management. Dipl.-Ing. Bogdan Marin. Universität Duisburg-Essen
Folie a: Name & Data Processing 2 3: Memory Management Dipl.-Ing. Bogdan Marin Fakultät für Ingenieurwissenschaften Abteilung Elektro-und Informationstechnik -Technische Informatik- Objectives Memory Management
Email UAE Bulk Email System. User Guide
Email UAE Bulk Email System User Guide 1 Table of content Features -----------------------------------------------------------------------------------------------------03 Login ---------------------------------------------------------------------------------------------------------08
SiS964 RAID. User s Manual. Edition. Trademarks V1.0 P/N: 91-187-U49-M2-0E
SiS964 RAID User s Manual Edition V1.0 P/N: 91-187-U49-M2-0E Trademarks All brand or product names mentioned are trademarks or registered trademarks of their respective holders. CONTENTS Introduction...
Top 20 ways to reduce your empty property business rates liability
Top 20 ways to reduce your empty property business rates liability Top 20 ways to reduce your empty property business rates liability With many property owners currently struggling to rent out vacant properties,
HOW TO COLLECT AND USE DATA IN EXCEL. Brendon Riggs Texas Juvenile Probation Commission Data Coordinators Conference 2008
HOW TO COLLECT AND USE DATA IN EXCEL Brendon Riggs Texas Juvenile Probation Commission Data Coordinators Conference 2008 Goals To be able to gather and organize information in Excel To be able to perform
FACTORS, PRIME NUMBERS, H.C.F. AND L.C.M.
Mathematics Revision Guides Factors, Prime Numbers, H.C.F. and L.C.M. Page 1 of 16 M.K. HOME TUITION Mathematics Revision Guides Level: GCSE Higher Tier FACTORS, PRIME NUMBERS, H.C.F. AND L.C.M. Version:
SMALL INDEX LARGE INDEX (SILT)
Wayne State University ECE 7650: Scalable and Secure Internet Services and Architecture SMALL INDEX LARGE INDEX (SILT) A Memory Efficient High Performance Key Value Store QA REPORT Instructor: Dr. Song
Closest Pair Problem
Closest Pair Problem Given n points in d-dimensions, find two whose mutual distance is smallest. Fundamental problem in many applications as well as a key step in many algorithms. p q A naive algorithm
Departmental Reporting in Microsoft Excel for Sage 50 Accounts
al Reporting in Microsoft Excel for Sage 50 Accounts 1 Introduction Whilst Sage 50 Accounts does already offer integrated Excel reporting functionality, we found that it was often missing the flexibility
OVERVIEW: ANNUAL AND SCAVENGER PROPERTY TAX SALES. Office of Cook County Treasurer Maria Pappas
OVERVIEW: ANNUAL AND SCAVENGER PROPERTY TAX SALES Office of Cook County Treasurer Maria Pappas October 3, 2012 SUMMARY Property Tax Cycle Overview Annual Tax Sale Scavenger Tax Sale 2 PROPERTY TAX CYCLE
Introduction to the data.table package in R
Introduction to the data.table package in R Revised: September 18, 2015 (A later revision may be available on the homepage) Introduction This vignette is aimed at those who are already familiar with creating
BSc (Hons) Business Information Systems, BSc (Hons) Computer Science with Network Security. & BSc. (Hons.) Software Engineering
BSc (Hons) Business Information Systems, BSc (Hons) Computer Science with Network Security & BSc. (Hons.) Software Engineering Cohort: BIS/05/FT BCNS/05/FT BSE/05/FT Examinations for 2005-2006 / Semester
How To Sell An Industrial Building In Batavia, Illinois For $879,000
Industrial Building Batavia, IL For Sale $879,000 Offering Highlights 16,000 SF Office / Warehouse Flex Building 66.9% Leased to 2 Tenants 2,000-5,300 SF Available for Owner / User Neil Johnson Managing
Introduction to Algorithms March 10, 2004 Massachusetts Institute of Technology Professors Erik Demaine and Shafi Goldwasser Quiz 1.
Introduction to Algorithms March 10, 2004 Massachusetts Institute of Technology 6.046J/18.410J Professors Erik Demaine and Shafi Goldwasser Quiz 1 Quiz 1 Do not open this quiz booklet until you are directed
Getting Started with Excel 2008. Table of Contents
Table of Contents Elements of An Excel Document... 2 Resizing and Hiding Columns and Rows... 3 Using Panes to Create Spreadsheet Headers... 3 Using the AutoFill Command... 4 Using AutoFill for Sequences...
Factoring - Grouping
6.2 Factoring - Grouping Objective: Factor polynomials with four terms using grouping. The first thing we will always do when factoring is try to factor out a GCF. This GCF is often a monomial like in
Quiz 4 Solutions EECS 211: FUNDAMENTALS OF COMPUTER PROGRAMMING II. 1 Q u i z 4 S o l u t i o n s
Quiz 4 Solutions Q1: What value does function mystery return when called with a value of 4? int mystery ( int number ) { if ( number
Lecture 12 Doubly Linked Lists (with Recursion)
Lecture 12 Doubly Linked Lists (with Recursion) In this lecture Introduction to Doubly linked lists What is recursion? Designing a node of a DLL Recursion and Linked Lists o Finding a node in a LL (recursively)
Name Intro to Algebra 2. Unit 1: Polynomials and Factoring
Name Intro to Algebra 2 Unit 1: Polynomials and Factoring Date Page Topic Homework 9/3 2 Polynomial Vocabulary No Homework 9/4 x In Class assignment None 9/5 3 Adding and Subtracting Polynomials Pg. 332
ITS Spam Filtering Service Quick Guide 2: Using the Quarantine
ITS Spam Filtering Service Quick Guide 2: Using the Quarantine The quarantine is where suspected spam messages are held on the ITS Spam Filtering server. In the graphic below, the quarantine window displays
USB 2.0 Flash Drive User Manual
USB 2.0 Flash Drive User Manual 1 INDEX Table of Contents Page 1. IMPORTANT NOTICES...3 2. PRODUCT INTRODUCTION...4 3. PRODUCT FEATURES...5 4. DRIVER INSTALLATION GUIDE...6 4.1 WINDOWS 98 / 98 SE... 6
Cuckoo Filter: Practically Better Than Bloom
Cuckoo Filter: Practically Better Than Bloom Bin Fan, David G. Andersen, Michael Kaminsky, Michael D. Mitzenmacher Carnegie Mellon University, Intel Labs, Harvard University {binfan,dga}@cs.cmu.edu, [email protected],
7. LU factorization. factor-solve method. LU factorization. solving Ax = b with A nonsingular. the inverse of a nonsingular matrix
7. LU factorization EE103 (Fall 2011-12) factor-solve method LU factorization solving Ax = b with A nonsingular the inverse of a nonsingular matrix LU factorization algorithm effect of rounding error sparse
Maths Targets for pupils in Year 2
Maths Targets for pupils in Year 2 A booklet for parents Help your child with mathematics For additional information on the agreed calculation methods, please see the school website. ABOUT THE TARGETS
from Recursion to Iteration
from Recursion to Iteration 1 Quicksort Revisited using arrays partitioning arrays via scan and swap recursive quicksort on arrays 2 converting recursion into iteration an iterative version with a stack
Data Structures Using C++ 2E. Chapter 5 Linked Lists
Data Structures Using C++ 2E Chapter 5 Linked Lists Test #1 Next Thursday During Class Cover through (near?) end of Chapter 5 Objectives Learn about linked lists Become aware of the basic properties of
SiS S-ATA User s Manual. Quick User s Guide. Version 0.1
SiS S-ATA User s Manual Quick User s Guide Version 0.1 Edition April 2003 Copyright Trademarks SiS is a registered trademark of Silicon Integrated Systems Corp. All brand or product names mentioned are
Monte Carlo Simulation. SMG ITS Advanced Excel Workshop
Advanced Excel Workshop Monte Carlo Simulation Page 1 Contents Monte Carlo Simulation Tutorial... 2 Example 1: New Marketing Campaign... 2 VLOOKUP... 5 Example 2: Revenue Forecast... 6 Pivot Table... 8
SPV Reporting Tool VBA Code User Guide. Last Updated: December, 2009
SPV Reporting Tool VBA Code User Guide Last Updated: December, 2009 SPV Reporting Tool Excel VBA Functionalities Golden Copy Golden Copy - Introduction This portion of the User Guide will go through troubleshooting
Factorising quadratics
Factorising quadratics An essential skill in many applications is the ability to factorise quadratic expressions. In this unit you will see that this can be thought of as reversing the process used to
Microsoft Excel 2007 Consolidate Data & Analyze with Pivot Table Windows XP
Microsoft Excel 2007 Consolidate Data & Analyze with Pivot Table Windows XP Consolidate Data in Multiple Worksheets Example data is saved under Consolidation.xlsx workbook under ProductA through ProductD
HOW TO GUIDE MONEY MANAGEMENT
MONEY MANAGEMENT CONTENTS Introduction... 2 Launch Money Management... 3 Add Accounts... 4 Delete Accounts... 6 Transaction History... 7 Sorting Transaction History... 7 Deleting Transactions (Manual Only)...
Office Outlook web access Reference Guide
U TO R E XC H A N G E : C a l e n d a r i n g a n d e m a i l u p g r a d e w i t h M i c r o s o f t E xc h a n g e Office Outlook web access Reference Guide To log in, go to owa.utoronto.ca. You will
Tutorial (03) IP addresses & Sub netting
Tutorial (03) IP addresses & Sub netting Dr. Ahmed M. ElShafee ١ Agenda IP Addressing Conventions Original IPv4 Address Classes Subnetting CIDR (Classless InterDomain Routing) ٢ IP Addressing Conventions
Linked List Problems
Linked List Problems By Nick Parlante Copyright 1998-99, Nick Parlante Abstract This document presents 18 linked list problems covering a wide range of difficulty. Most obviously, these problems are useful
Improvements of Printer Driver GUI for GA-1060
Improvements of Printer Driver GUI for GA-1060 Revision 1.1 This printer driver is not compatible because of the operativeness improvement of GUI with printer driver of version 2.xx. Please use this manual
How To Set Up A Raid On A Hard Disk Drive On A Sasa S964 (Sasa) (Sasa) (Ios) (Tos) And Sas964 S9 64 (Sata) (
SiS964/SiS180 SATA w/ RAID User s Manual Quick User s Guide Version 0.3 Edition December 2003 Copyright 2003 Silicon Integrated Systems Corp. Trademarks SiS is a registered trademark of Silicon Integrated
SiS964/SiS180 SATA w/ RAID User s Manual. Quick User s Guide. Version 0.3
SiS964/SiS180 SATA w/ RAID User s Manual Quick User s Guide Version 0.3 Edition December 2003 Copyright 2003 Silicon Integrated Systems Corp. Trademarks SiS is a registered trademark of Silicon Integrated
Aras Corporation. 2005 Aras Corporation. All rights reserved. Notice of Rights. Notice of Liability
Aras Corporation 2005 Aras Corporation. All rights reserved Notice of Rights All rights reserved. Aras Corporation (Aras) owns this document. No part of this document may be reproduced or transmitted in
Human Capital Management (HCM) Case Study
Human Capital Management (HCM) Case Study This case study explains a human capital management process using organizational management and personnel administration. Product SAP ERP G.B.I. Release 6.0 EhP4
159.735. Final Report. Cluster Scheduling. Submitted by: Priti Lohani 04244354
159.735 Final Report Cluster Scheduling Submitted by: Priti Lohani 04244354 1 Table of contents: 159.735... 1 Final Report... 1 Cluster Scheduling... 1 Table of contents:... 2 1. Introduction:... 3 1.1
Sample Questions Csci 1112 A. Bellaachia
Sample Questions Csci 1112 A. Bellaachia Important Series : o S( N) 1 2 N N i N(1 N) / 2 i 1 o Sum of squares: N 2 N( N 1)(2N 1) N i for large N i 1 6 o Sum of exponents: N k 1 k N i for large N and k
Unit 4.3 - Storage Structures 1. Storage Structures. Unit 4.3
Storage Structures Unit 4.3 Unit 4.3 - Storage Structures 1 The Physical Store Storage Capacity Medium Transfer Rate Seek Time Main Memory 800 MB/s 500 MB Instant Hard Drive 10 MB/s 120 GB 10 ms CD-ROM
CHAPTER 4 ESSENTIAL DATA STRUCTRURES
CHAPTER 4 ESSENTIAL DATA STRUCTURES 72 CHAPTER 4 ESSENTIAL DATA STRUCTRURES In every algorithm, there is a need to store data. Ranging from storing a single value in a single variable, to more complex
Sample Questions with Explanations for LSAT India
Five Sample Analytical Reasoning Questions and Explanations Directions: Each group of questions in this section is based on a set of conditions. In answering some of the questions, it may be useful to
CSE 326, Data Structures. Sample Final Exam. Problem Max Points Score 1 14 (2x7) 2 18 (3x6) 3 4 4 7 5 9 6 16 7 8 8 4 9 8 10 4 Total 92.
Name: Email ID: CSE 326, Data Structures Section: Sample Final Exam Instructions: The exam is closed book, closed notes. Unless otherwise stated, N denotes the number of elements in the data structure
Data Structures. Level 6 C30151. www.fetac.ie. Module Descriptor
The Further Education and Training Awards Council (FETAC) was set up as a statutory body on 11 June 2001 by the Minister for Education and Science. Under the Qualifications (Education & Training) Act,
Unordered Linked Lists
Unordered Linked Lists Derive class unorderedlinkedlist from the abstract class linkedlisttype Implement the operations search, insertfirst, insertlast, deletenode See code on page 292 Defines an unordered
Web Intelligence User Guide
Web Intelligence User Guide Office of Financial Management - Enterprise Reporting Services 4/11/2011 Table of Contents Chapter 1 - Overview... 1 Purpose... 1 Chapter 2 Logon Procedure... 3 Web Intelligence
2Creating Reports: Basic Techniques. Chapter
2Chapter 2Creating Reports: Chapter Basic Techniques Just as you must first determine the appropriate connection type before accessing your data, you will also want to determine the report type best suited
Cast On: Placing a foundation row of stitches upon the needle in order to begin knitting.
l Cast On l Increase l Decrease l Bind Off l Wrap and Turn l Wrap and Wrapped Stitch Together l Crossed Puff Stitch l Stockinette stitch: Knit RS rows and purl WS rows. If working in round, knit all rounds.
Scan-Line Fill. Scan-Line Algorithm. Sort by scan line Fill each span vertex order generated by vertex list
Scan-Line Fill Can also fill by maintaining a data structure of all intersections of polygons with scan lines Sort by scan line Fill each span vertex order generated by vertex list desired order Scan-Line
CS104: Data Structures and Object-Oriented Design (Fall 2013) October 24, 2013: Priority Queues Scribes: CS 104 Teaching Team
CS104: Data Structures and Object-Oriented Design (Fall 2013) October 24, 2013: Priority Queues Scribes: CS 104 Teaching Team Lecture Summary In this lecture, we learned about the ADT Priority Queue. A
CSA Helpdesk User Guide
CSA Helpdesk User Guide CSA Helpdesk User Guide 1 Creating Tickets 1.1 1.2 Creating a New Ticket via Email 4 Creating a New Ticket via the Website 7 2 Account Management 2.1 2.2 2.3 Logging in to your
