INTERNATIONAL BURCH UNIVERSITY
Faculty of Engineering and Natural Sciences
Department of Information Technologies
2016-2017

SYLLABUS
Code Name Level Year Semester
CEN 254 Data Structures Undergraduate 2 Spring
Status Number of ECTS Credits Class Hours Per Week Total Hours Per Semester Language
Compulsory 5 3 + 2 102

Instructor Assistant Coordinator
Amar Sarić, Assist. Prof. Dr. Amar Sarić, Assist. Prof. Dr.
[email protected] no email

This course is an introduction to abstract data structures and related algorithms, including the sorting algorithms. Their implementation and applications are discussed along with the basic analysis of their complexity. The topics include: * Study of the basic data structures and their implementations: lists, stacks, queues, hash tables and trees. * Programming techniques using recursion. * Various searching and sorting methods such as insertion sort, merge sort, and quick sort.

COURSE OBJECTIVE
After completing this course, students should be able to:

* Understand the basic data structures and their use in programming
* Understand and apply sorting algorithms
* Implement various data structures and algorithms
* Analyze computational complexity of basic algorithms

COURSE CONTENT
Week
Topic
  1. Introduction / Java Review
  2. Algorithm Analysis, Computational Complexity, Big-O Notation, Binary Search
  3. Containers, Array Based Lists, Linked Lists
  4. Stacks and Queues
  5. Hashing – Chaining
  6. Hashing – Open Addressing
  7. Stacks
  8. MIDTERM EXAM
  9. Naive Sorting Algorithms (O(n^2))
  10. Quicksort and Quickselect
  11. Merge sort
  12. Heaps and Heapsort
  13. Binary Trees, Binary Search Trees
  14. Balanced Trees, AVL-Trees, Overview of Other Balanced Trees
  15. B-Trees, Final Exam Review

LABORATORY/PRACTICE PLAN
Week
Topic

    TEACHING/ASSESSMENT
    Description
    • Interactive Lectures
    • Practical Sessions
    • Excersises
    • Presentation
    • Problem solving
    • Assignments
    Description (%)
    Method Quantity Percentage (%)
    Homework330
    Midterm Exam(s)125
    Final Exam135
    +Participation110
    Total: 100
    Learning outcomes
      TEXTBOOK(S)
      • Sedgewick and Wayne, Algorithms, 4th Edition, Addison-Wesley, 2011

      ECTS (Allocated based on student) WORKLOAD
      Activities Quantity Duration (Hour) Total Work Load
      Lecture (14 weeks x Lecture hours per week)14342
      Laboratory / Practice (14 weeks x Laboratory/Practice hours per week)14228
      Midterm Examination (1 week)122
      Final Examination(1 week)122
      Preparation for Midterm Examination133
      Preparation for Final Examination155
      Assignment / Homework/ Project4520
      Seminar / Presentation 0
      Total Workload: 102
      ECTS Credit (Total workload/25): 4