1. ET 2006 : Data Structures & Algorithms
Lecture 1: Introduction
Malaka J Walpola

2. Outline - I Class Details Discussion & Survey
Learning Outcomes & Course Outline
Assessments
Class Rules & Expectations
Discussion & Survey
Introduction to Algorithms
What is an algorithm?
Flowcharts
Pseudocode

3. Outline - II Basic Data Structures
Introduction to Data Structures and Abstract Data Types
Basic Data Structures & Operations on Them
Arrays
Records
Lists
Stack
Queue
Dictionary

4. Class Details

5. ET 2006: Data Structures & Algorithms
Credits: 4 (GPA)
Pre-requisites : ET 1001-Introduction to ICT
Course Objective:
To provide knowledge of basic data structures and algorithmic design paradigms used to manipulate data structures for common functions in software programming

6. CS 2022 : Data Structures & Algorithms
Lecturers: Malaka J. Walpola
Contact information
Phone:

7. CS 2022 : Data Structures & Algorithms
Hours:
Lectures – (45 Hrs: 4.5 to 5 Hrs/week)
Monday 1.00 – 5.30/6.00
Labs/Assignments (30 Hrs)
Reading the Books, Self Study & Homework (will depend on individuals)

8. Learning Outcomes
On the completion of this module, the student will be able to:
LO1: Select and implement common data structures for a given situation [12 Hrs]
LO2: Implement appropriate algorithms to manipulate data structures [12 Hrs]
LO3: Analyze the performance and complexity of basic algorithms [9 Hrs]
LO4: Use data structures and synthesize efficient algorithms to solve real life problems [12 Hrs]

9. Course Outline - I
Select and implement common data structures for a given situation [12]
Basic data structures and their properties:
linear (arrays, linked-lists, stacks, queues)
Non-linear (trees and graphs)
Operations on data structures: insertion, deletion, sorting, searching, traversing
Heap abstract data type and heap operations;
Dictionaries and hash tables

10. Course Outline - II
Implement appropriate algorithms to manipulate data structures [12]
Characteristics of an algorithm.
Algorithm creation techniques and matrices of algorithms:
Recursion: tail and non-tail, direct and indirect;
Algorithms for stacks and queues: first in first out (FIFO) and last in first out(LIFO)
Sorting algorithms:
Internal and external sorting
Simple Sorting Algorithms (Bubble, selection, insertion)
Advanced Sorting Algorithms (Merge, Quick, Bucket, Shell, Heap)
Searching Algorithms: - linear (sequential) search and binary search (BST)

11. Course Outline - III
Analyze the performance and complexity of basic algorithms [9]
Factors considered in analyzing algorithms, and growth of functions
Asymptotic notations
Time complexity and asymptotic complexity analysis
Efficiency of different searching and sorting algorithms

12. Course Outline - IV
Use data structures and synthesize efficient algorithms to solve real life problems [12]
Solving real-life recursion problems: factorials, Fibonacci numbers, Towers of Hanoi.
Divide and conquer techniques; Tree and graph traversal techniques (Death-first and Breadth first), Handling cycles and vertices, Tree traversal pre-order, in-order and post-order
Graph traversal algorithms: - Bellman-Ford shortest-path and Dijkstra's shortest-path algorithms

13. Method of Assessment Exam – 70% Assignments – 30% 3 hour Closed book
Answer all
Will have short answer/multiple choice questions
Assignments – 30%
Assignment 1: On LO1 & LO2 - 10%
Assignment 2: On LO3 - 10%
Assignment 3: On LO4 - 10%

14. Recommended Text Books
Adam Drozdek, Data Structures and algorithms in Java, , 3rd Ed., Cengage Learning Asia, 2008
Michael Goodrich and Roberto Tamassia, Data Structures and Algorithms in Java; 5th Ed., Wiley,
Thomas H. Cormen, Charles E. Leiserson, Ronald L. Rivest and Clifford Stein, Introduction to Algorithms, 3rd Ed. Cambridge, MA, MIT Press, 2009

15. Class Rules Be Respectful and Responsible
No talking among yourselves
No cell phones/communication devices
Be Organized and Follow Directions
Be Prepared
If you miss a lecture, it is your responsibility to makeup
Assignment Must Be Your Own Work
It will help you understand the material
Cite all references
We may be using plagiarism detection tools

16. Expectations
All the students are required to read the assigned sections of the book
Please keep up with the reading
In-class activities and homework will assume that you have done this.
All the students are expected to actively participate in the in-class activities
If you have difficulties in homework, bring them to class and ask during the breaks

17. Questions or Concerns?

18. Discussion & Survey

19. Introduction to Algorithms

20. Learning Outcomes
After successfully studying contents covered in this lecture, students should be able to,
explain the idea of a computational task
explain what an algorithm is and express an algorithm using pseudo code or flowcharts
explain the concept of an abstract data type
write pseudo codes for operations of linked list, stack, queue, and dictionary data structures
implement linked list, stack, queue, and dictionary data structures and use them

21. Introduction Why Do We Study Data Structures and Algorithms?
To make understanding and solving problems simple
To solve problems in the BEST way

22. Sample Problems Searching the Web for the IESL College of Engineering
Calculating the Fourier Transform of a Signal
Designing a PCB Layout for a Circuit
Sorting a List of Names
Calculating Best Path from Colombo to Anuradhapura

23. Sample Problems Searching the Web for the IESL College of Engineering
Calculating Best Path from Colombo to Anuradhapura
Calculating the Fourier Transform of a Signal
Designing a PCB Layout for a Circuit
Sorting a List of Names

24. Computational Task
A computational task is not just a “single” task such as
“Is prime ?”
“What is 37487*2371 ?”
A computational task is a whole family of “similar” tasks with varying INPUT, such as
“Given a whole number A, is A prime?”
“Given 2 numbers x and y, what is x times y?”

25. Algorithm What is an Algorithm?
Well defined procedure
Takes some inputs
Produce some outputs
An algorithm is a step-by-step method of solving a computational task
Recipe

26. Specifying Algorithms
Listing the Steps
Flowcharts
Pseudocode
Program Listing
Class Activity: Specify an algorithm to add all the numbers in a list by listing the steps

27. Flowcharts
A diagram that show the “flow of control” of an algorithm/a program
Flowchart symbols

28. Flowchart Symbols Terminals Input/output Data
Represents the stat or end of the process
Represented by rounded rectangles
Input/output Data
Represented by parallelograms
Indicate an input or output operation
Start
End
Read input x
Output Max Value

29. Flowchart Symbols Stored Data Processing Represented by rectangles
Indicates a process such as a mathematical computation or variable assignment
Processing
Stored data value
x = x + 1
y = y + 5
Increment x
add 5 to y

30. Flowchart Symbols Decision Represented by diamond shape
Indicates different paths of execution/choices the program can take
Is end of the array?
Yes No
More employees ?
Yes No

31. Flowcharts Example Class Activity
Draw the flowchart of an algorithm to add all the numbers in a list of numbers
Class Activity
Draw the flowchart of an algorithm to find and print the largest number in a list of numbers

32. Pseudocode Human readable version of program code
An intermediate level between program code and listing of steps
Each step should be simple and precise
Can use predefined procedures
Example: Express an algorithm to add all the numbers in a list of numbers using pseudocode
Class Activity: Express an algorithm to find and print the largest number in a list of numbers using pseudocode

33. Basic Data Structures

34. Introduction What is a data structure? Examples
A way to store and organize data
Operations performed on them
Facilitates creation, access and modification
Examples
Records, arrays, link lists, stacks, queues, trees, graphs
Discuss sample applications (priority queue, etc.) and provide an overview of how we can modify the basic data structures to suite our requirements

35. Introduction What is a ADT? Importance of ADT
Data structure specification
A set of operations on the structure
Implementation independent
Importance of ADT
Data abstraction
Allows us to focus on important aspects of data
Encapsulation or information hiding

36. Introduction ADT specification The set of operations on the structure
Name
Input/Pre condition
Process
Output/Post condition
Types of operations
Constructors
Access procedures
Manipulation procedures

37. Arrays A finite set of homogeneous elements
Stored in continuous memory locations
Calculating address of elements
2D arrays
Row major vs column major ordering

38. Arrays Types Strings as character arrays
Multidimensional arrays
Arrays that can grow
Dynamic arrays
Strings as character arrays
In c: null terminated character arrays
In java: string has a length
Which type of array to use will depend on
Requirements
Programming language construct
Arrays, ArrayList, and Vector

39. Records A simple data structure Example Stores heterogeneous data
Also called tuple or struct
Example
A record to store student name, index no, and currentGPA
Index no: integer
name: string
CurrentGPA: floating point

40. ADT - Linked List A set of linked elements Consists of
Nodes (Elements)
An attribute called head which specifies the first node of the linked list
Node composition
Data fields
Pointers

41. Linked List - Specification
LIST-SEARCH(L,k)
Finds the first node with the key k in the list L
Returns NIL if no element is found
LIST-INSERT(L,x)
Inserts the node x into the front of the list L
LIST-DELETE(L,x)
Deletes the node x from the list L if exists

42. Linked List - Types Linked list Doubly linked list
Circular linked list

43. Linked List - Specification
Extensions
LIST-INSERT(L,x,i)
Inserts the node x into the ith location of the list L
Modifications for double linked lists
LIST-INSERT-BEFORE (L,x,i)
Inserts the node x before the ith element of the list L
LIST-INSERT-AFTER(L,x,i)
Inserts the node x after the ith element of the list L

44. Linked List - ImplementationC
Using pointers
Allocate & free memory dynamically
C++/Java/Python
Classes
Create objects and link them
Comparison between lists in Python and the linked lists

45. ADT - Queue A first in first out (FIFO) data structure
Similar to the queue you see in day to day life
Insert -> enqueue
Insert element to the end of the queue
Delete -> dequeue
Remove the first element from the queue
Priority queues

46. ADT - Stack A last in first out (LIFO) data structure
Insert -> push
Insert element to the top of the stack
Delete -> pop
Remove the element from top of the stack

47. ADT - Dictionary Represents a set Operations Search (S,k)
Insert (S,x) – add element to the dictionary
Delete (S,x)
Minimum (S)
Maximum (S)
Successor (S,x)
Predecessor (S,x)

48. Self Studying

49. Homework
Write pseudo codes for the operations of a (single) linked list
Write pseudo codes for the operations of a double linked list
How can you implement a stack and a queue using a linked list?
Write the pseudo codes for the operations
Will there be any advantages if you use a double linked list?

50. Homework How can you implement a dictionary using a linked list?
What type of a linked list (single linked list, double linked list or a circular linked list) would be the best option? Why?
What will be the answer to the above question if we remove the “Predecessor ” operation?
Write the pseudo codes for the operations

51. References
[1] T.H. Cormen, C.E. Leiserson, R.L. Rivest and C. Stein, Introduction to Algorithms, 3rd Ed. Cambridge, MA, MIT Press, [2] S. Baase and Allen Van Gelder, Computer Algorithms: Introduction to Design and Analysis, 3rd Ed. Delhi, India, Pearson Education, 2000.