Course Detail
Course Description
Course | Code | Semester | T+P (Hour) | Credit | ECTS |
---|---|---|---|---|---|
DATA STRUCTURES | - | Spring Semester | 3+2 | 4 | 8 |
Course Program |
Prerequisites Courses | |
Recommended Elective Courses |
Language of Course | English |
Course Level | First Cycle (Bachelor's Degree) |
Course Type | Elective |
Course Coordinator | Prof.Dr. Mehmet Kemal ÖZDEMİR |
Name of Lecturer(s) | |
Assistant(s) | Teaching assistant for the lab sessions. |
Aim | This course aims to teach how to organize data in a computer so that it can be used for designing efficient algorithms to solve various types of problems. Topics covered include arrays, lists, stacks, queues, trees, heaps, graphs and the use of these data structures for searching, sorting, selection and other related applications. C Programming language will be used for the implementation of data-structures. |
Course Content | This course contains; Introduction to data structures and algorithms; Introduction to Basics of C,Functions, Arrays, and Pointers,Strings, Structs, and Memory Allocation,Algorithm analysis and complexity notations,Fundamental data structures: Linked Lists,Abstract data types: Stack,Abstract data types: Queues,Trees and Binary Search Trees,Efficient Binary Trees and Multi-way Search Trees,Priority Queues and Heaps,Graphs,Searching and Sorting,Hashing and Collision,Files and Their Organization. |
Dersin Öğrenme Kazanımları | Teaching Methods | Assessment Methods |
Explain basic principles of algorithm analysis. | 12, 21, 6, 9 | A |
Apply basic data structures, such as arrays, lists, stacks and queues, to algorithmic design | 12, 17, 2, 21, 6, 9 | A, F |
Applys the tree, binary tree, heap, hash tables, and graph data structures in problem solutions | 12, 17, 6, 9 | A |
Choose the right data type for efficient solution of a problem. | 12, 17, 2, 6, 9 | F |
Analyze the accuracy, complexity and efficiency of an algorithmic solution. | 17, 2, 21, 6, 9 | A, F |
Teaching Methods: | 12: Problem Solving Method, 17: Experimental Technique, 2: Project Based Learning Model, 21: Simulation Technique, 6: Experiential Learning, 9: Lecture Method |
Assessment Methods: | A: Traditional Written Exam, F: Project Task |
Course Outline
Order | Subjects | Preliminary Work |
---|---|---|
1 | Introduction to data structures and algorithms; Introduction to Basics of C | Book Chapter 1, Lecture Slides 1 |
2 | Functions, Arrays, and Pointers | Book Chapter 1 and 3, Lecture Slides 2 |
3 | Strings, Structs, and Memory Allocation | Book Chapter 4 ve 5, Lecture Slides 3 |
4 | Algorithm analysis and complexity notations | Book Chapter 2, Lecture Slides 4 |
5 | Fundamental data structures: Linked Lists | Book Chapter 6, Lecture Slides 4 |
6 | Abstract data types: Stack | Book Chapter 7, Lecture Slides 6 |
7 | Abstract data types: Queues | Book Chapter 8, Lecture Slides 7 |
8 | Trees and Binary Search Trees | Book Chapter 9, Lecture Slides 8 |
9 | Efficient Binary Trees and Multi-way Search Trees | Book Chapter 10-11, Lecture Slides 9 |
10 | Priority Queues and Heaps | Book Chapter 12, Lecture Slides 10 |
11 | Graphs | Book Chapter 13, Lecture Slides 11 |
12 | Searching and Sorting | Book Chapter 14, Lecture Slides 12 |
13 | Hashing and Collision | Book Chapter 15, Lecture Slides 13 |
14 | Files and Their Organization | Book Chapter 16, Lecture Slides 14 |
Resources |
Course Textbook: Data Structures Using C 2nd Edition by Reema Thareja ISBN-10 : 0198099304 |
Supplementary Material: Data Structures and Algorithms in C++, 4th Edition, Mark A. Weiss, ISBN: 978-0132847377 Lecture presentations and notes |
Course Contribution to Program Qualifications
Course Contribution to Program Qualifications | |||||||
No | Program Qualification | Contribution Level | |||||
1 | 2 | 3 | 4 | 5 | |||
1 | Adequate knowledge in mathematics, science and engineering subjects pertaining to the relevant discipline; ability to use theoretical and applied knowledge in these areas in the solution of complex engineering problems. | X | |||||
2 | Ability to formulate, and solve complex engineering problems; ability to select and apply proper analysis and modeling methods for this purpose. | X | |||||
3 | Ability to design a complex system, process, device or product under realistic constraints and conditions, in such a way as to meet the desired result; ability to apply modern design methods for this purpose. | X | |||||
4 | Ability to select and use modern techniques and tools needed for analyzing and solving complex problems encountered in engineering practice; ability to employ information technologies effectively. | X | |||||
5 | Ability to design and conduct experiments, gather data, analyze and interpret results for investigating complex engineering problems or discipline specific research questions. | ||||||
6 | Ability to work efficiently in intra-disciplinary and multi-disciplinary teams; ability to work individually. | ||||||
7 | Ability to communicate effectively, both orally and in writing; knowledge of a minimum of one foreign language; ability to write effective reports and comprehend written reports, prepare design and production reports, make effective presentations, and give and receive clear and intelligible instructions. | ||||||
8 | Awareness of the need for lifelong learning; ability to access information, to follow developments in science and technology, and to continue to educate him/herself. | ||||||
9 | Knowledge on behavior according ethical principles, professional and ethical responsibility and standards used in engineering practices. | ||||||
10 | Knowledge about business life practices such as project management, risk management, and change management; awareness in entrepreneurship, innovation; knowledge about sustainable development. | ||||||
11 | Knowledge about the global and social effects of engineering practices on health, environment, and safety, and contemporary issues of the century reflected into the field of engineering; awareness of the legal consequences of engineering solutions. |
Assessment Methods
Contribution Level | Absolute Evaluation | |
Rate of Midterm Exam to Success | 30 | |
Rate of Final Exam to Success | 70 | |
Total | 100 |
ECTS / Workload Table | ||||||
Activities | Number of | Duration(Hour) | Total Workload(Hour) | |||
Course Hours | 14 | 3 | 42 | |||
Guided Problem Solving | 14 | 2 | 28 | |||
Resolution of Homework Problems and Submission as a Report | 14 | 5 | 70 | |||
Term Project | 14 | 2 | 28 | |||
Presentation of Project / Seminar | 0 | 0 | 0 | |||
Quiz | 7 | 1 | 7 | |||
Midterm Exam | 1 | 30 | 30 | |||
General Exam | 1 | 40 | 40 | |||
Performance Task, Maintenance Plan | 0 | 0 | 0 | |||
Total Workload(Hour) | 245 | |||||
Dersin AKTS Kredisi = Toplam İş Yükü (Saat)/30*=(245/30) | 8 | |||||
ECTS of the course: 30 hours of work is counted as 1 ECTS credit. |
Detail Informations of the Course
Course Description
Course | Code | Semester | T+P (Hour) | Credit | ECTS |
---|---|---|---|---|---|
DATA STRUCTURES | - | Spring Semester | 3+2 | 4 | 8 |
Course Program |
Prerequisites Courses | |
Recommended Elective Courses |
Language of Course | English |
Course Level | First Cycle (Bachelor's Degree) |
Course Type | Elective |
Course Coordinator | Prof.Dr. Mehmet Kemal ÖZDEMİR |
Name of Lecturer(s) | |
Assistant(s) | Teaching assistant for the lab sessions. |
Aim | This course aims to teach how to organize data in a computer so that it can be used for designing efficient algorithms to solve various types of problems. Topics covered include arrays, lists, stacks, queues, trees, heaps, graphs and the use of these data structures for searching, sorting, selection and other related applications. C Programming language will be used for the implementation of data-structures. |
Course Content | This course contains; Introduction to data structures and algorithms; Introduction to Basics of C,Functions, Arrays, and Pointers,Strings, Structs, and Memory Allocation,Algorithm analysis and complexity notations,Fundamental data structures: Linked Lists,Abstract data types: Stack,Abstract data types: Queues,Trees and Binary Search Trees,Efficient Binary Trees and Multi-way Search Trees,Priority Queues and Heaps,Graphs,Searching and Sorting,Hashing and Collision,Files and Their Organization. |
Dersin Öğrenme Kazanımları | Teaching Methods | Assessment Methods |
Explain basic principles of algorithm analysis. | 12, 21, 6, 9 | A |
Apply basic data structures, such as arrays, lists, stacks and queues, to algorithmic design | 12, 17, 2, 21, 6, 9 | A, F |
Applys the tree, binary tree, heap, hash tables, and graph data structures in problem solutions | 12, 17, 6, 9 | A |
Choose the right data type for efficient solution of a problem. | 12, 17, 2, 6, 9 | F |
Analyze the accuracy, complexity and efficiency of an algorithmic solution. | 17, 2, 21, 6, 9 | A, F |
Teaching Methods: | 12: Problem Solving Method, 17: Experimental Technique, 2: Project Based Learning Model, 21: Simulation Technique, 6: Experiential Learning, 9: Lecture Method |
Assessment Methods: | A: Traditional Written Exam, F: Project Task |
Course Outline
Order | Subjects | Preliminary Work |
---|---|---|
1 | Introduction to data structures and algorithms; Introduction to Basics of C | Book Chapter 1, Lecture Slides 1 |
2 | Functions, Arrays, and Pointers | Book Chapter 1 and 3, Lecture Slides 2 |
3 | Strings, Structs, and Memory Allocation | Book Chapter 4 ve 5, Lecture Slides 3 |
4 | Algorithm analysis and complexity notations | Book Chapter 2, Lecture Slides 4 |
5 | Fundamental data structures: Linked Lists | Book Chapter 6, Lecture Slides 4 |
6 | Abstract data types: Stack | Book Chapter 7, Lecture Slides 6 |
7 | Abstract data types: Queues | Book Chapter 8, Lecture Slides 7 |
8 | Trees and Binary Search Trees | Book Chapter 9, Lecture Slides 8 |
9 | Efficient Binary Trees and Multi-way Search Trees | Book Chapter 10-11, Lecture Slides 9 |
10 | Priority Queues and Heaps | Book Chapter 12, Lecture Slides 10 |
11 | Graphs | Book Chapter 13, Lecture Slides 11 |
12 | Searching and Sorting | Book Chapter 14, Lecture Slides 12 |
13 | Hashing and Collision | Book Chapter 15, Lecture Slides 13 |
14 | Files and Their Organization | Book Chapter 16, Lecture Slides 14 |
Resources |
Course Textbook: Data Structures Using C 2nd Edition by Reema Thareja ISBN-10 : 0198099304 |
Supplementary Material: Data Structures and Algorithms in C++, 4th Edition, Mark A. Weiss, ISBN: 978-0132847377 Lecture presentations and notes |
Course Contribution to Program Qualifications
Course Contribution to Program Qualifications | |||||||
No | Program Qualification | Contribution Level | |||||
1 | 2 | 3 | 4 | 5 | |||
1 | Adequate knowledge in mathematics, science and engineering subjects pertaining to the relevant discipline; ability to use theoretical and applied knowledge in these areas in the solution of complex engineering problems. | X | |||||
2 | Ability to formulate, and solve complex engineering problems; ability to select and apply proper analysis and modeling methods for this purpose. | X | |||||
3 | Ability to design a complex system, process, device or product under realistic constraints and conditions, in such a way as to meet the desired result; ability to apply modern design methods for this purpose. | X | |||||
4 | Ability to select and use modern techniques and tools needed for analyzing and solving complex problems encountered in engineering practice; ability to employ information technologies effectively. | X | |||||
5 | Ability to design and conduct experiments, gather data, analyze and interpret results for investigating complex engineering problems or discipline specific research questions. | ||||||
6 | Ability to work efficiently in intra-disciplinary and multi-disciplinary teams; ability to work individually. | ||||||
7 | Ability to communicate effectively, both orally and in writing; knowledge of a minimum of one foreign language; ability to write effective reports and comprehend written reports, prepare design and production reports, make effective presentations, and give and receive clear and intelligible instructions. | ||||||
8 | Awareness of the need for lifelong learning; ability to access information, to follow developments in science and technology, and to continue to educate him/herself. | ||||||
9 | Knowledge on behavior according ethical principles, professional and ethical responsibility and standards used in engineering practices. | ||||||
10 | Knowledge about business life practices such as project management, risk management, and change management; awareness in entrepreneurship, innovation; knowledge about sustainable development. | ||||||
11 | Knowledge about the global and social effects of engineering practices on health, environment, and safety, and contemporary issues of the century reflected into the field of engineering; awareness of the legal consequences of engineering solutions. |
Assessment Methods
Contribution Level | Absolute Evaluation | |
Rate of Midterm Exam to Success | 30 | |
Rate of Final Exam to Success | 70 | |
Total | 100 |