ECTS - Data Structures
Data Structures (CMPE226) Course Detail
| Course Name | Course Code | Season | Lecture Hours | Application Hours | Lab Hours | Credit | ECTS |
|---|---|---|---|---|---|---|---|
| Data Structures | CMPE226 | 4. Semester | 3 | 0 | 0 | 3 | 8 |
| Pre-requisite Course(s) |
|---|
| CMPE225 |
| Course Language | English |
|---|---|
| Course Type | Compulsory Departmental Courses |
| Course Level | Natural & Applied Sciences Master's Degree |
| Mode of Delivery | Face To Face |
| Learning and Teaching Strategies | Lecture, Discussion, Question and Answer, Drill and Practice, Brain Storming. |
| Course Lecturer(s) |
|
| 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;
|
| 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 |
Sources
| 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 | An ability to apply advanced knowledge of computing and/or informatics to solve software engineering problems. | |||||
| 2 | Develop solutions using different technologies, software architectures and life-cycle approaches. | |||||
| 3 | An ability to design, implement and evaluate a software system, component, process or program by using modern techniques and engineering tools required for software engineering practices. | |||||
| 4 | An ability to gather/acquire, analyze, interpret data and make decisions to understand software requirements. | |||||
| 5 | Skills of effective oral and written communication and critical thinking about a wide range of issues arising in the context of working constructively on software projects. | |||||
| 6 | An ability to access information in order to follow recent developments in science and technology and to perform scientific research or implement a project in the software engineering domain. | |||||
| 7 | An understanding of professional, legal, ethical and social issues and responsibilities related to Software Engineering. | |||||
| 8 | Skills in project and risk management, awareness about importance of entrepreneurship, innovation and long-term development, and recognition of international standards of excellence for software engineering practices standards and methodologies. | |||||
| 9 | An understanding about the impact of Software Engineering solutions in a global, environmental, societal and legal context while making decisions. | |||||
| 10 | Promote the development, adoption and sustained use of standards of excellence for software engineering practices. | |||||
ECTS/Workload Table
| Activities | Number | Duration (Hours) | Total Workload |
|---|---|---|---|
| Course Hours (Including Exam Week: 16 x Total Hours) | 16 | 3 | 48 |
| Laboratory | |||
| Application | |||
| Special Course Internship | |||
| Field Work | |||
| Study Hours Out of Class | 16 | 6 | 96 |
| Presentation/Seminar Prepration | |||
| Project | |||
| Report | |||
| Homework Assignments | |||
| Quizzes/Studio Critics | |||
| Prepration of Midterm Exams/Midterm Jury | 2 | 20 | 40 |
| Prepration of Final Exams/Final Jury | 1 | 20 | 20 |
| Total Workload | 204 | ||