TÜRKÇE
ENGLISH
Information
| Unit | FACULTY OF ENGINEERING |
| COMPUTER ENGINEERING PR. (ENGLISH) | |
| Code | CEN213 |
| Name | Data Structures |
| Term | 2018-2019 Academic Year |
| Semester | 3. Semester |
| Duration (T+A) | 3-0 (T-A) (17 Week) |
| ECTS | 5 ECTS |
| National Credit | 3 National Credit |
| Teaching Language | İngilizce |
| Level | Lisans Dersi |
| Type | Normal |
| Label | C Compulsory |
| Mode of study | Yüz Yüze Öğretim |
| Catalog Information Coordinator | Prof. Dr. SELMA AYŞE ÖZEL |
| Course Instructor |
Doç. Dr. SERKAN KARTAL
(Güz)
(A Group)
(Ins. in Charge)
|
Course Goal / Objective
To learn program execution speed and memory requirement calculation methods
Course Content
Analysis of running time and memory requirements of data structures and algorithms, linked list, stack, queue, tree, graph data structures and their applications
Course Precondition
Resources
Notes
Course Learning Outcomes
| Order | Course Learning Outcomes |
|---|---|
| LO01 | Gains the ability to analyze the data structures and algorithms for runtime and memory requirements. |
| LO02 | Linked lists can be used to learn stack, queue, tree and graph data structures, and array and pointer based programming of these data structures and real life problems of these data structures. |
| LO03 | Gains deciding ability to which data structure and model should be used to solve real life problems in the most efficient way and apply this data structure. |
Relation with Program Learning Outcome
| Order | Type | Program Learning Outcomes | Level |
|---|---|---|---|
| PLO01 | - | Has capability in the fields of mathematics, science and computer that form the foundations of engineering | 5 |
| PLO02 | - | Identifies, formulates, and solves engineering problems, selects and applies appropriate analytical methods and modeling techniques, | 5 |
| PLO03 | - | Analyzes a system, its component, or process and designs under realistic constraints to meet the desired requirements,gains the ability to apply the methods of modern design accordingly. | 5 |
| PLO04 | - | Ability to use modern techniques and tools necessary for engineering practice and information technologies effectively. | 5 |
| PLO05 | - | Ability to design and to conduct experiments, to collect data, to analyze and to interpret results | 5 |
| PLO06 | - | Has ability to work effectively as an individual and in multi-disciplinary teams, take sresponsibility and builds self-confidence | 5 |
| PLO07 | - | Can access information,gains the ability to do resource research and uses information resources | 5 |
| PLO08 | - | Awareness of the requirement of lifelong learning, to follow developments in science and technology and continuous self-renewal ability | 5 |
| PLO09 | - | Ability to communicate effectively orally and in writing, and to read and understand technical publications in at least one foreign language | 3 |
| PLO10 | - | Professional and ethical responsibility, | 4 |
| PLO11 | - | Awareness about project management, workplace practices, employee health, environmental and occupational safety, and the legal implications of engineering applications, | 5 |
| PLO12 | - | Becomes aware of universal and social effects of engineering solutions and applications, entrepreneurship and innovation, and knowledge of contemporary issues | 5 |
Week Plan
| Week | Topic | Preparation | Methods |
|---|---|---|---|
| 1 | Explaining data structure and data model concepts, giving examples | Reading of course notes | |
| 2 | Explanation of program execution speed and memory requirement calculation methods with sample programs | Reading of course notes | |
| 3 | Explanation of program execution speed and memory requirement calculation methods with sample programs | Reading of course notes, homework | |
| 4 | Sorting algorithms and analysis (interleave sorting, selective sorting, bubble sorting algorithms and comparison) | Reading of course notes | |
| 5 | Sorting algorithms and analysis (unified sorting, clustering sorting, fast sorting algorithms and comparison of all sorting algorithms) | Reading of course notes, homework | |
| 6 | Sequence Search and Binary Search algorithms, analysis and applications | Reading of course notes | |
| 7 | Beat search algorithms, analysis, and applications | Reading of course notes, homework | |
| 8 | Mid-Term Exam | Reading of course notes | |
| 9 | Single and bidirectional linked lists and applications | Reading of course notes, homework | |
| 10 | Stack Data Structure and its applications | Reading of course notes | |
| 11 | Queue Data Structure and its applications | Reading of course notes, homework | |
| 12 | Identification of the Tree Data Model | Reading of course notes | |
| 13 | Binary Tree, Relation Tree, Clustering Tree, Coding Trees and applications | Reading of course notes, homework | |
| 14 | Defining the chart data model | Reading of course notes | |
| 15 | Final Exam | Reading of course notes | |
| 16 | Term Exams | Reading of course notes | |
| 17 | Term Exams | Reading of course notes |
Assessment (Exam) Methods and Criteria
| Assessment Type | Midterm / Year Impact | End of Term / End of Year Impact |
|---|---|---|
| 1. Midterm Exam | 100 | 40 |
| General Assessment | ||
| Midterm / Year Total | 100 | 40 |
| 1. Final Exam | - | 60 |
| Grand Total | - | 100 |
Student Workload - ECTS
| Works | Number | Time (Hour) | Workload (Hour) |
|---|---|---|---|
| Course Related Works | |||
| Class Time (Exam weeks are excluded) | 14 | 3 | 42 |
| Out of Class Study (Preliminary Work, Practice) | 14 | 3 | 42 |
| Assesment Related Works | |||
| Homeworks, Projects, Others | 0 | 0 | 0 |
| Mid-term Exams (Written, Oral, etc.) | 1 | 12 | 12 |
| Final Exam | 1 | 18 | 18 |
| Total Workload (Hour) | 114 | ||
| Total Workload / 25 (h) | 4,56 | ||
| ECTS | 5 ECTS | ||