COMPUTER ENGINEERING | |||||
Bachelor | TR-NQF-HE: Level 6 | QF-EHEA: First Cycle | EQF-LLL: Level 6 |
Course Code | Course Name | Semester | Theoretical | Practical | Credit | ECTS |
SEN2212 | Data Structures and Algorithms II | Spring |
2 | 2 | 3 | 7 |
This catalog is for information purposes. Course status is determined by the relevant department at the beginning of semester. |
Language of instruction: | English |
Type of course: | Non-Departmental Elective |
Course Level: | Bachelor’s Degree (First Cycle) |
Mode of Delivery: | Face to face |
Course Coordinator : | Dr. Öğr. Üyesi BETÜL ERDOĞDU ŞAKAR |
Course Lecturer(s): |
Dr. Öğr. Üyesi BETÜL ERDOĞDU ŞAKAR Dr. Öğr. Üyesi YÜCEL BATU SALMAN RA SEVGİ CANPOLAT RA MERVE ARITÜRK |
Recommended Optional Program Components: | None |
Course Objectives: | The objective of this course is to analyze data structures and algorithms used in software engineering in detail. After completing the course, the student will have knowledge of applying, implementing and analysis of data structures, including, trees, binary search trees, balanced search trees, heaps and graphs. Certain fundamental techniques, such as sorting, hashing and greedy algorithms are also taught. |
The students who have succeeded in this course; The students who have succeeded in this course; 1) Describe and apply basic object oriented programming principles. 2) Implement basic data structures such as trees, binary search trees, balanced search trees, heaps and graphs. 3) Describe and implement sorting algorithms on common data structures. 4) Describe and implement searching algorithms on common data structures. 5) Implement and use hashing algorithms. 6) Implement and use greedy algorithms. 7) Choose and design data structures for writing efficient programs. |
The course content is composed of basic data structures like trees, binary search trees, balanced search trees, heaps, graphs and sorting, hashing and greedy algorithms. |
Week | Subject | Related Preparation |
1) | Introduction and Sorting Algorithms. | Sorting algorithms. |
2) | Introduction to different tree structures. | Trees. |
3) | Introduction to binary search trees. | Binary search trees. |
4) | Implementing binary search tree using Java. | Binary search trees. |
5) | Introduction to balanced trees and implementing AVL balanced tree structure using Java. | AVL trees. |
6) | Using other balanced tree structure using Java. | Other balanced trees. |
7) | Using heap structure and implementing them using Java. | Heap. |
8) | Using heaps as priority queues. Midterm. | Heap. |
9) | Analyzing and implementing hashing algorithms. | Hashing algorithms. |
10) | Analyzing and implementing graph structure using Java. | Graph. |
11) | Analyzing and implementing graph algorithms. | Graph algorithms. |
12) | Analyzing and implementing greedy algorithms. | Greedy algorithms. |
13) | Analyzing and implementing greedy algorithms. Quiz. | Greedy algorithms. |
14) | Review. |
Course Notes / Textbooks: | Data Structures & Problem Solving Using Java (Mark Allen Weiss) Data Structures and Algorithm Analysis in Java (Mark Allen Weiss) Data Structures and Abstractions with Java (Frank Carrano) |
References: | Yok. |
Semester Requirements | Number of Activities | Level of Contribution |
Application | 4 | % 10 |
Quizzes | 1 | % 10 |
Project | 1 | % 15 |
Midterms | 1 | % 25 |
Final | 1 | % 40 |
Total | % 100 | |
PERCENTAGE OF SEMESTER WORK | % 45 | |
PERCENTAGE OF FINAL WORK | % 55 | |
Total | % 100 |
Activities | Number of Activities | Duration (Hours) | Workload |
Course Hours | 14 | 2 | 28 |
Laboratory | 14 | 2 | 28 |
Study Hours Out of Class | 12 | 2 | 24 |
Project | 10 | 2 | 20 |
Homework Assignments | 2 | 5 | 10 |
Quizzes | 5 | 2 | 10 |
Midterms | 5 | 3 | 15 |
Final | 10 | 3 | 30 |
Total Workload | 165 |
No Effect | 1 Lowest | 2 Low | 3 Average | 4 High | 5 Highest |
Program Outcomes | Level of Contribution | |
1) | Adequate knowledge in mathematics, science and computer engineering; the ability to use theoretical and practical knowledge in these areas in complex engineering problems. | |
2) | Ability to identify, formulate, and solve complex engineering problems; ability to select and apply appropriate analysis and modeling methods for this purpose. | 2 |
3) | Ability to design a complex system, process, device or product to meet specific requirements under realistic constraints and conditions; ability to apply modern design methods for this purpose. | 3 |
4) | Ability to develop, select and use modern techniques and tools necessary for the analysis and solution of complex problems encountered in computer engineering applications; ability to use information technologies effectively. | |
5) | Ability to design, conduct experiments, collect data, analyze and interpret results for the study of complex engineering problems or computer engineering research topics. | 3 |
6) | Ability to work effectively within and multi-disciplinary teams; individual study skills. | 2 |
7) | Ability to communicate effectively in verbal and written Turkish; knowledge of at least one foreign language; ability to write active reports and understand written reports, to prepare design and production reports, to make effective presentations, to give and receive clear and understandable instructions. | |
8) | Awareness of the necessity of lifelong learning; ability to access information, to follow developments in science and technology and to renew continuously. | |
9) | To act in accordance with ethical principles, professional and ethical responsibility; information on the standards used in engineering applications. | |
10) | Information on business practices such as project management, risk management and change management; awareness of entrepreneurship and innovation; information about sustainable development. | |
11) | Knowledge of the effects of engineering practices on health, environment and safety in the universal and social scale and the problems of the era reflected in engineering; awareness of the legal consequences of engineering solutions. |