Data Structures (CMPE226) Course Detail

Course Name Course Code Season Lecture Hours Application Hours Lab Hours Credit ECTS
Data Structures CMPE226 3 0 0 3 8
Pre-requisite Course(s)
Course Language English
Course Type N/A
Course Level Bachelor’s Degree (First Cycle)
Mode of Delivery Face To Face
Learning and Teaching Strategies Lecture, Discussion, Question and Answer, Drill and Practice, Brain Storming.
Course Coordinator
Course Lecturer(s)
Course Assistants
Course Objectives This course introduces the abstract concepts that are useful in problem solving, and shows how these concepts are implemented in a programming language. The students learn how to choose a suitable data structure for a specific problem, how to create more complex data structures using the already existing data types, and also how to implement and analyze the algorithms developed for these data structures. The students get a chance to apply their knowledge by completing assignments written in the C++ language.
Course Learning Outcomes The students who succeeded in this course;
  • Employ the data structure(s) necessary for a given problem
  • Use linked lists, stacks, queues, and binary trees
  • Apply recursion
  • Apply searching, sorting, and hashing algorithms/techniques
  • Identify the most appropriate data structure for the problem at hand
  • Construct complex data structures using existing data types
Course Content Stacks, recursion, queues; creation and destruction of dynamic variables, serial linked lists, circular lists, doubly linked lists, circular doubly linked lists; sorting and searching algorithms, space and time considerations, binary trees, binary search trees, tree traversal algorithms, binary tree sorting algorithms, hashing.

Weekly Subjects and Releated Preparation Studies

Week Subjects Preparation
1 Introduction, Standard Template Library (STL) Chapter 2,4 (main text)
2 Linked Lists Chapter 5
3 Linked Lists Chapter 5
4 Linked Lists Chapter 5
5 Recursion Chapter 6
6 Stack Chapter 7
7 Stack Chapter 7
8 Queues Chapter 8
9 Queues Chapter 8
10 Searching, Sorting Chapter 9,10
11 Hashing Chapter 5
12 Binary Trees Chapter 11
13 Binary Trees Chapter 11
14 Heap Sort Chapter 11
15 Review
16 Review


Course Book 1. Data Structures Using C++, D.S. Malik, Thomson Course Technology, 1st Edition.
Other Sources 2. Data Structures Using C and C++, Y.Langsam, Prentice-Hall International Inc., 2nd Edition.
3. Data Structures and Algorithm Analysis in C++, M. Weiss, Addison Wesley, 3rd Edition
4. Practical Data Structures in C++, B. Flamig, John Wiley & Sons, Pap/Dis Edition.
5. Fundamentals of Data Structures in C++, E. Horowitz, S. Sahni, D. Mehta, Silicon Press, 2nd Edition.
6. Data Structures and Algorithms in C++, M.T. Goodrich, R.Tamassia, D. M. Mount, Wiley, 2nd Edition.

Evaluation System

Requirements Number Percentage of Grade
Attendance/Participation - -
Laboratory - -
Application - -
Field Work - -
Special Course Internship - -
Quizzes/Studio Critics - -
Homework Assignments - -
Presentation - -
Project - -
Report - -
Seminar - -
Midterms Exams/Midterms Jury 2 60
Final Exam/Final Jury 1 40
Toplam 3 100
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 Adequate knowledge in mathematics, science and subjects specific to the computer engineering discipline; the ability to apply theoretical and practical knowledge of these areas to complex engineering problems. X
2 The ability to identify, define, formulate and solve complex engineering problems; selecting and applying proper analysis and modeling techniques for this purpose. X
3 The ability to design a complex system, process, device or product under realistic constraints and conditions to meet specific requirements; the ability to apply modern design methods for this purpose. X
4 The ability to develop, select and utilize modern techniques and tools essential for the analysis and determination of complex problems in computer engineering applications; the ability to utilize information technologies effectively. X
5 The ability to design experiments, conduct experiments, gather data, analyze and interpret results for the investigation of complex engineering problems or research topics specific to the computer engineering discipline. X
6 The ability to work effectively in inter/inner disciplinary teams; ability to work individually
7 Effective oral and writen communication skills in Turkish; the ability to write effective reports and comprehend written reports, to prepare design and production reports, to make effective presentations, to give and to receive clear and understandable instructions.
8 The knowledge of at least one foreign language; the ability to write effective reports and comprehend written reports, to prepare design and production reports, to make effective presentations, to give and to receive clear and understandable instructions.
9 Recognition of the need for lifelong learning; the ability to access information, to follow recent developments in science and technology.
10 The ability to behave according to ethical principles, awareness of professional and ethical responsibility;
11 Knowledge of the standards utilized in software engineering applications
12 Knowledge on business practices such as project management, risk management and change management;
13 Awareness about entrepreneurship, innovation
14 Knowledge on sustainable development
15 Knowledge on the effects of computer engineering applications on the universal and social dimensions of health, environment and safety;
16 Awareness of the legal consequences of engineering solutions
17 An ability to describe, analyze and design digital computing and representation systems. X
18 An ability to use appropriate computer engineering concepts and programming languages in solving computing problems. X

ECTS/Workload Table

Activities Number Duration (Hours) Total Workload
Course Hours (Including Exam Week: 16 x Total Hours) 16 3 48
Special Course Internship
Field Work
Study Hours Out of Class 16 4 64
Presentation/Seminar Prepration
Homework Assignments 3 12 36
Quizzes/Studio Critics
Prepration of Midterm Exams/Midterm Jury 2 15 30
Prepration of Final Exams/Final Jury 1 20 20
Total Workload 198