ECTS - Introduction to Data Structures

Introduction to Data Structures (CMPE321) Course Detail

Course Name Course Code Season Lecture Hours Application Hours Lab Hours Credit ECTS
Introduction to Data Structures CMPE321 6. Semester 2 2 0 3 5
Pre-requisite Course(s)
CMPE221
Course Language English
Course Type Compulsory Departmental Courses
Course Level Bachelor’s Degree (First Cycle)
Mode of Delivery Face To Face
Learning and Teaching Strategies Lecture, Question and Answer, Drill and Practice, Team/Group.
Course Coordinator
Course Lecturer(s)
Course Assistants
Course Objectives This course aims to introduce the students a number of popular data structures and algorithms, along with the basic techniques in algorithm analysis.
Course Learning Outcomes The students who succeeded in this course;
  • Understand common data structures and algorithms, and implement them.
  • Analyze the complexities of data structures and algorithms.
  • Choose appropriate data structures and algorithms for problem solving.
Course Content Static and dynamic memory allocation, recursion, algorithms, stacks, queues, linked lists, circular linked lists, trees, binary trees, Hash tables, searching and sorting algorithms.

Weekly Subjects and Releated Preparation Studies

Week Subjects Preparation
1 Introduction, Standard Template Library (STL) Ch 2, 4 (Other Source 5)
2 Pointer Syntax in C++ pp. 15-26
3 Structures pp.26-30
4 Templates: Generic Functions pp. 97-103
5 Templates: Generic Classes pp. 103-112
6 Recursion pp. 265-275
7 Recursion (continued) pp. 275-284
8 Stacks and Queues pp. 537-544
9 Stacks and Queues (continued) pp. 545-551
10 Stacks and Queues (continued) pp. 552-559
11 Linked Lists pp. 565-582
12 Linked Lists (continued) pp. 565-582
13 Trees and Binary Trees pp. 605-622
14 Trees and Binary Trees (continued) pp. 622-633

Sources

Course Book 1. Mark Allen Weiss, “Data Structures and Problem Solving Using C++, 2nd Edition”, Addison Wesley, 2003. ISBN # 0321205006
Other Sources 2. Yedidyah Langsam, Moshe J. Augenstein, and Aaron M. Tenenbaum, “Data Structures Using C and C++”, Prentice-Hall, 1996. ISBN # 0-13-036997-7
3. Absolute C++, W. Savitch, Addison-Wesley
4. Problem Solving with C++: The Object of Programming, W. Savitch, Addison-Wesley
5. C++ Primer, Stanley B. Lippman, Addison-Wesley.
6. Data Structures Using C++, D.S. Malik, Thomson Course Technology, 1st Edition

Evaluation System

Requirements Number Percentage of Grade
Attendance/Participation - -
Laboratory - -
Application - -
Field Work - -
Special Course Internship - -
Quizzes/Studio Critics - -
Homework Assignments 5 10
Presentation - -
Project - -
Report - -
Seminar - -
Midterms Exams/Midterms Jury 2 50
Final Exam/Final Jury 1 40
Toplam 8 100
Percentage of Semester Work 60
Percentage of Final Work 40
Total 100

Course Category

Core Courses X
Major Area Courses
Supportive Courses
Media and Managment Skills Courses
Transferable Skill Courses

The Relation Between Course Learning Competencies and Program Qualifications

# Program Qualifications / Competencies Level of Contribution
1 2 3 4 5
1 Has the ability to apply scientific knowledge gained in the undergraduate education and to expand and extend knowledge in the same or in a different area
2 Can apply gained knowledge and problem solving abilities in inter-disciplinary research
3 Has the ability to work independently within research area, to state the problem, to develop solution techniques, to solve the problem, to evaluate the obtained results and to apply them when necessary
4 Takes responsibility individually and as a team member to improve systematic approaches to produce solutions in unexpected complicated situations related to the area of study
5 Can develop strategies, implement plans and principles on the area of study and can evaluate obtained results within the framework X
6 Can develop and extend the knowledge in the area and to use them with scientific, social and ethical responsibility
7 Has the ability to follow recent developments within the area of research, to support research with scientific arguments and data, to communicate the information on the area of expertise in a systematically by means of written report and oral/visual presentation
8 To have an oral and written communication ability in at least one of the common foreign languages ("European Language Portfolio Global Scale", Level B2)
9 Has software and hardware knowledge in the area of expertise, and has proficient information and communication technology knowledge
10 Follows scientific, cultural, and ethical criteria in collecting, interpreting and announcing data in the research area and has the ability to teach.
11 Has professional ethical consciousness and responsibility which takes into account the universal and social dimensions in the process of data collection, interpretation, implementation and declaration of results in mathematics and its applications.

ECTS/Workload Table

Activities Number Duration (Hours) Total Workload
Course Hours (Including Exam Week: 16 x Total Hours) 16 2 32
Laboratory
Application
Special Course Internship
Field Work
Study Hours Out of Class 14 2 28
Presentation/Seminar Prepration
Project
Report
Homework Assignments 5 6 30
Quizzes/Studio Critics
Prepration of Midterm Exams/Midterm Jury 2 12 24
Prepration of Final Exams/Final Jury 1 12 12
Total Workload 126