ITEC 2620M Introduction to Data Structures

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ITEC 2620MIntroduction to Data Structures

• Instructor Prof. Z. Yang
• Course Website http//people.math.yorku.ca/zyang
  /itec2620m.htm
• Office Tel 3049

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Course Objective

• Course is about concepts
• what you can program, not how
• Traditionally, second course in computer science
• still separates top third of programmers
• not taught in any known college diploma program
• Learn and use efficient programming patterns
• an efficient programmer can often produce
  programs that run five times faster than an
  inefficient programmer

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Textbooks

• A Practical Introduction to Data Structures and
  Algorithm Analysis Java Edition by Clifford A.
  Shaffer
• Lecture notes and announcements will be made
  available at
• http//people.math.yorku.ca/zyang/itec2620m.htm

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Marking Scheme

• Assignment 1 10
• Midterm 30
• about 1/3 code, 2/3 concepts
• Final 60
• about 1/3 code, 2/3 concepts
• Late Policy
• The assignment is optional. Late assignments will
  NOT be accepted. If you miss it, the weight will
  be added to the weight of the TWO PROGRAMMING
  QUESTIONS in the final exam. No medical note is
  required. A make-up midterm will NOT be provided.
  If you miss the midterm, the weight will be
  added to the weight of the final exam.

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Schedule

• Lecture Topic
• 1a Introduction
• 1b Searching
• 2a Sorting non-recursive algorithms
• 2b Estimation and Complexity analysis
  non-recursive algorithms
• 3a More complexity analysis, Complexity
  estimation non-recursive algorithms
• 3b Linked lists
• 4a Doubly linked lists and Binary trees
• 4b Recursion and Binary tree operations

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Schedule (Contd)

• Lecture Topic
• 5a Sorting recursive algorithms
• 5b Link list and BST operations
• 6a Complexity estimation recursive
  algorithms
• 6b Midterm review
• 7a MIDTERM
• 7b Estimation of recursive algorithm, abstract
  data types and Stacks
• 8a Stack based recursion, Queues, Priority
  Queues
• 8b Midterm solution discussion

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Schedule (Contd)

• Lecture Topic
• 9a Heaps and Heapsort
• 9b Graphs and Graph algorithm
• 10a Hashing
• 10b 2-3 trees
• 11a B-trees
• 11b Btrees
• 12a Review
• 12b Review

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Course Organization

• Key concepts first
• searching, sorting, complexity analysis, linked
  structures
• Concrete to concept
• searching ? sorting ? complexity analysis
• binary tree ? recursion

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Chapter 1

• Introduction

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Need for Data Structure

• Computer
• Store and retrieve information
• Perform calculation
• Costs and benefits
• A data structure requires a certain amount of
  space for each data item it stores, a certain
  amount of time to perform a single basic
  operation, and a certain amount of programming
  effort.

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Problem, Algorithms and Programs

• Problem a task to be performed
• Algorithm a method or a process followed to
  solve a problem
• Program an instance, or concrete representation,
  of an algorithm in some programming language.

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Algorithm Efficiency

• Design goals
• Design an algorithm that is easy to understand,
  code, and debug.
• Design an algorithm that makes efficient use of
  the computers resources.
• Algorithm analysis

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Three keys to programming

• Algorithm Design
• Sequence, branching, looping flowcharts and
  pseudocode
• Efficiency and time-space tradeoffs (linkages
  between algorithms and data structures)
• Data Organization
• objects and classes
• data structures
• Modularization
• methods (modularization of algorithms)
• classes and inheritance (modularization of
  data/objects)