COP 3530: Data Structures, Algorithms,

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COP 3530 Data Structures, Algorithms,
Applications

• Instructor Kristian Linn Damkjer

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Course Overview

• Syllabus Review

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What The Course Is About

• Applications are developed to solve real-world
  problems.
• All programs manipulate data.
• Programs must represent data in some way.
• Data structures focuses on data representation
  and manipulation.
• Data manipulation requires algorithms.
• Algorithms are the fundamental elements in
  application development.

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Prerequisites

• Java
• CIS 3020 or CIS 3022 CIS 3023
• You should be proficient and self-sufficient
• You must be capable of writing programs without
  the aid of a compiler.

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Prerequisites

• Asymptotic Complexity
• COT 3100
• We will use primarily O notation.
• f(n) O(g(n)) Big Oh notation
• f(n) is bounded above by g(n)
• You should also be comfortable with T and O.
• f(n) T(g(n)) Big Theta notation
• f(n) is asymptotically equivalent to g(n)
• f(n) O(g(n)) Big Omega notation
• f(n) is bounded below by g(n)

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Prerequisites

• Strong Mathematical Reasoning
• Any of the various flavors of Calculus 2.
• At the very least you need to understand
• Sequences
• Series
• Summations
• Integration
• Differentiation
• Matrices
• Vectors

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Web Sites

• http//www.cise.ufl.edu/kdamkjer/courses/su05/cop
  3530/
• Announcements
• Syllabus
• Handouts
• Exercise Solutions
• Assignments
• TAs and Discussions
• http//www.cise.ufl.edu/sahni/cop3530/
• Text
• Source Codes
• Past Exams
• Past Exam Solutions

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Assignments

• Assignment guidelines
• Submission procedures
• Do Assignment 0 by Friday!

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Source Codes

• Read download and use instructions.
• Read download and use instructions.
• Must have Java 1.2 or higher
• Hopefully you have 1.4.2 or 1.5.0 (5.0)
• Review the source code documentation
• ProgramIndex.html
• AllNames.html
• Other HTML files produced by Javadoc

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Discussion Sections

• Go to either one
• TAs will answer your questions on lectures and
  assignments.
• TAs will cover exercises from the text.
• Web site lists topics and exercises for each
  discussion section.

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Textbook

• Its not rocket science (really)
• Its computer science
• There are three sections to the textbook
• Background (Chapters 1-4)
• Data Structures (Chapters 5-17)
• Algorithms (Chapters 18-22)
• What about Applications?
• Well cover applications throughout the entire
  semester along with general theory and other
  concepts.

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Grades

• Assignments 25
• Five Graded Projects
• No drops permitted
• Each worth 5
• Exams 75
• Three Exams
• No drops permitted
• Each worth 25

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Grades

• Historic Cutoffs
• A 83
• B 75
• B 70
• C 65
• C 60
• D 55
• D 50

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Classic Problem

• Sorting

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Classic Problem Sorting

• Given a list of comparable elements
• a0, a1, ,an-1
• Rearrange the list into a specific order
• Typically increasing or decreasing order.

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Classic Problem Sorting

• Given a list of comparable elements
• a0, a1, ,an-1
• Rearrange the list into a specific order
• Typically increasing or decreasing order.
• Objective
• a0 a1 an-1
• Examples
• 8, 6, 9, 4, 3 ? 3, 4, 6, 8, 9
• 8, 3, 6, 2, 8, 10, 2 ? 2, 2, 3, 6, 8, 8, 10

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Sorting Methods

• Insertion
• Bubble
• Selection
• Count
• Shaker
• Shell
• Heap
• Merge
• Quick

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Sorting Methods

• Insertion
• Bubble
• Selection
• Count
• Shaker
• Shell
• Heap
• Merge
• Quick

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Inserting an Element

• Given a sorted list (sequence), insert a new
  element
• Given 3, 6, 9, 14
• Insert 5
• Result 3, 5, 6, 9, 14

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Inserting an Element

• Insert 5 into the list 3, 6, 9, 14
• Compare new element (5) and last element in list
  (14)
• Shift 14 right to get 3, 6, 9, , 14
• Shift 9 right to get 3, 6, , 9, 14
• Shift 6 right to get 3, , 6, 9, 14
• Insert 5 to get 3, 5, 6, 9, 14

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Inserting an Element

• // insert t into a0i-1
• int j
• for (j i 1 j gt 0 t lt aj j--)
• aj 1 aj
• aj 1 t

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Next Time in COP 3530

• Read Chapters 14 for review of topics covered
  today
• Performance Analysis and Measurement
• We will start the Data Structures portion of this
  course
• Start thinking about different ways to represent
  data
• Read Chapter 5.15.2
• Data Structure Linear Lists