Topic outline

  • Welcome to Data Structures

    Join Online Class



    Instructor : Amatul Bushra Akhi, Assistant Professor, Department of CSE
    Office : Room-317, AB-4, Daffodil Smart City Campus
    Telephone : 01733481053
    Email              : akhi.cse@diu.edu.bd

    Welcome Information on Data Structures Course

    • Welcome Audio
    • Listen to Course Objectives
    • Listen to Expected Outcomes
    • Listen to Course Delivery Plan
    • Some Successful Projects


    Student Interests Survey

    Online C Compiler for Data Structures Lab

    Course Rationale

    This course investigates abstract data types (ADTs), recursion, algorithms for searching and sorting, and basic algorithm analysis. ADTs to be covered include lists, stacks, queues, priority queues, trees, sets, and graphs. The emphasis is on the trade-offs associated with implementing alternative data structures for these ADTs.

    Course Objectives

    • To introduce the fundamental concept of data structures including link-list
    • To emphasize the importance of data structures in implementing the algorithms
    • To develop effective skills in the implementation of data structure


    Course Outcomes (CO’s)

    • CO1 Able to explain implementation and operations of basic data structures: Linked list, stack, queue, tree and graph
    • CO2 Able to apply programming techniques using pointers, dynamic memory allocation and structures to implement data structures: stack, queue, tree and graph
    • CO3 Able to design and implement new abstract data using linked list, stack, queue, tree and graph with the help of programming implementations
    • CO4 Able to apply the knowledge of data structure in problem solving


    Grading Scheme
    Theory Class
    Attendance: 7%
    Class Tests/Quizes:  15% 
    Assignment: 5%
    Presentation (using video/ppt): 8%
    Midterm Exam: 25%
    Final Exam: 40%
    [All assessment will be based on onsite/online situation]

    Textbook

    a. Data Structures and Algorithm Analysis in C by Mark Allen Weiss
    b. Principles of Data Structures     by Pande

    Reference Books/Materials

  • Week 1: Preparing Background


    • Topics of discussion

    1. Introduction and importance of Data Structure in computing; Applications
    2. Review discussion on recursion, pointer, structure, self-referential structure; dynamic memory allocation

    • Expected Learning Outcome

    1. Appreciate the needs of data structure
    2. Visualize the applications
    3. Perform exercise on basic self-referential structure

    • Self-Test and Additional Problem Solving

  • Week 2: Exercise and Course Project


    • Topics for discussion:

    1. Computational Complexity and exercises
    2. Self-referential structure application for link list
    3. Exercise on visualization of data node
    4. Course Project Team and discussion on presentation and deliverable

    • Expected Learning Outcome:

    1. Computational Complexity and exercises
    2. Self-referential structure application for link list
    3. Exercise on visualization of data node
    4. Course Project Team and discussion on presentation and deliverable

  • Week 3: Discussion on Link-List


    Topics of discussion:

    1. Link-List and operations on link list
    2. Project Discussion and execution plan
    3. Class Test#1

    Expected Learning Outcome:

    1. Visualization of the link list
    2. Write code for the designed link list
    3. Selection of project topic by team

  • Week 4: Adaptive Lesson on Link-List


    Topics of discussion:

    1. Practice lesson on Link-List

    Expected Learning Outcome:

    1. Review of Link-List Knowledge
    2. Self-confidence building on applying the link-list concept

    • Week 5: Review discussion on Link-List


      • Topics of discussion:

      1. Review operations on Link list and applications
      2. Discussion on Stack data structure
      3. Exercise using Stack data structure

      • Expected Learning Outcome:

      1. Implement link list operations using C programming
      2. Analyzing stack data structure

      • Self-Test Questions

      • Week 6: Discussion on Stack Applications


        • Topics of discussion:

        1. Application of stack in processing expressions
        2. Discussion on Queue data structure
        3. Class Test# 2

        • Expected Learning Outcome:

        1. Implement processing of expression using stack   
        2. Analyze queue data structure

        • Presentation on Course Project

      • Week 7: Midterm Exam


        • Topics for Mid Exam:
        1. Link-list and operations
        2. Stack and application of stack

        • Week 8: Discussion on Tree Data Structure


          • Topics of discussion:

          1. Discussion on Tree data structure and Tree Terminologies
          2. Tree traversals and applications

          • Expected Learning Outcome:

          1. Implementation of tree data structure
          2. Problem solving for tree traversal
          Online Class Recording:




          Click to get Lecture Materials


          • Week 9: Discussion on Binary Search Tree (BST)


            • Topics of discussion:

            1. BST and operations on BST
            2. Applications of BST

            • Expected Learning Outcome:

            1. Implementation of BST and related operations
            2. Problem solving using BST

            • Week 10: Discussion on Heap


              • Topics of discussion:

              1. HEAP data structure and applications of Heap
              2. Exercise on BST and Heap

              • Expected Learning Outcome:

              1. Implementation of Heap and operations
              2. Problem solving using BST

              • Week 11: AVL tree and Graph


                • Topics of discussion:

                1. AVL tree discussion
                2. AVL tree Rotations
                3. AVL Tree construction, insertion
                4. AVL Tree VS BST

              • Week 12: Review Discussion


                • Topics of discussion:

                1. Review exercises on Tree, BST, Heap and Graph

                • Expected Learning Outcome:

                1. Problem solving using Tree, BST, Heap, and Graph

                • Self-test

                • Week 13-14: Final Exam


                  • Topics of the final:
                  1. Tree, BST and applications
                  2. Heap and application of Heap
                  3. Basics of Graph data structure

                  • Topic 14

                    • Topic 15

                      • Topic 16

                        • Topic 17

                          • Topic 18

                            • Topic 19

                              • Topic 20