Data Structures Outline

7/28/2019 Data Structures Outline

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Detailed Course out line ofData Structures and Algorithms(Course Code) Page1of5

SUKKUR INSTITUTE OFBUSINESSADMINISTRATIONSUKKUR

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Programs & Clas :BE- Semeste :Spring 201Credit Hours: Class Work:

Lab Work: 1Total: 4

Instructo : Mr Muham ad Asif Ali+923337007123

Pr -requisite Courses:1. Introduction to Programming (CS-201)2. Object Oriented Programming

Pos-requisite Courses:

Evaluation

1. Sessional Assignmetns

Quizes

Class Participation

2

5. Mid-Term E amination 40. Final Examinatio 40

Recommended Books:

Data Structure AndAlgorithms In Java

Robert Lafor ndedition

Reference Books:

1 Data Structures andAlgorithms in C++

Michael T. Goodrich, RobertoTamassia and David Mount

ndEdtion

Introduction toAlgorithms

Thomas H. Cormen,Leiserson, Rivest, and Stein(CLRS).

rdEdition


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Detailed Course out line ofData Structure & Algorithms (CSC 222) Page2of5

Course Objectives:

This course is an extension of the knowledge of algorithm design and programming gained in programming courses

with continued emphasis on the logic underlying the transition from specification to program. Particular attention is

paid to issues arising in the implementation of larger programs: introduction of data structures and data abstraction;

Introduction of recursion as a design tool. Introduction of algorithmcomplexity analysis. Students will learn about

well-known data structures as listed below in course outline. This course will enable students to:

Understand the working of Abstract Data Types such as Lists, Queues etc.

Understand and program Stack operations (Push, Pop, isEmpty)

Understand and implement Queue Operations (Insert, Remove) using Linked Lists

Describe binary Trees

Understanding the working of slow sorting techniques such as Bubble sort, Insertion Sort, Selection Sort

Understanding the working of recursion and fast sorting techniques such as Merge Sort, Heap Sort.

Expected Outcomes:

1. Implementthese structures as classes in Java;

2. Determinewhich structures are appropriate in various situations;3. Confidentlylearn new structures beyond what are presented in this class.

4. To develop an ability to make critical analysis of any problem and suggest the feasible algorithm if available or

design algorithm from already studied in the course.

Lab Work

Every week lab exercises related to topic covered in that week would be given. Students would be required to

complete the lab work sheets and get that signed after due working and demonstration.

Students Conduct:

1. I expect students to arrive on-time for the class. Classroom participation constitutes 4% of the grade in this class.

You will be expected to have previously read the reading assignment before the class, and to be able to participate in

classroom discussions.

2. Mobile phones and other communication devices must be in switched off or inactive during class hours.

3. Other policies would be conveyed to you in class from time to time. Remember that rules, regulation and policies

of the institute will supersede in any case.


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Lecture Hours:

Dependant on Time Table

Lab Hours:

Dependant on Time Table

Office Hours:

2 hours right after the regular class sessions and by appointment on rest of other week days

Office:Academic Block-1, Research LabCubicle 08


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Sessionwise Details:

WeekNo

Topic Text Book Referenc

Introduction to Data Structures

Need of Data Structures

Arrays

List Data Structure with help of arrayso Insert()o Remove()o Find()

Data Structure And Algorithms InJava

Chapter 1,2

2 Array based Stacko Push()o Pop()o Peek()o Print_all()

Array based Queue.


Chapter 4

3 Functions of Queue

Priority Queueo Insert_Priority()

Introduction to Sorting


Chapter 4

Sorting Techniqueso Bubble Sorto Insertion Sorto Selection Sort


Chapter 3

5 Introduction to Algorithms

Micro and Macro issues

Asymptotic Notations

Running Time Analysiso Best Caseo Worst Caseo Average Case

7 Brute Force algorithm for finding 2D maxima

Plane Sweep algorithm for finding 2D maxima

Analysis of Plane Sweep algorithm

Analysis of slow sorting techniques- Linked Lists

o Insertion in listo Deletion in listo Find in list

Abstract Data Typeso Queues (with functions)o Stacks (with functions)


Chapter 5

1 Recursion

MergeSort

Analysis of MergeSorto Worst Case running time analysiso Best Case running time analysis


Chapter 6


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11 HeapSort

o Worst Case running time analysiso Best Case running time analysis


Chapter 12

12 Optimization problems

Introduction to Greedy Algorithms

13

Money counting problem Huffman Encoding


Chapter 8

1 Binary Search Treeso Insert()o Find()o inOrder()o preorder()o postOrder()

Binary Tree traversal


Chapter 8

15o

Revisio

Documents

Data Structures Outline