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Information
| Code | CEN215 |
| Name | Data Structures Lab. |
| Term | 2024-2025 Academic Year |
| Semester | 3. Semester |
| Duration (T+A) | 0-2 (T-A) (17 Week) |
| ECTS | 2 ECTS |
| National Credit | 1 National Credit |
| Teaching Language | İngilizce |
| Level | Lisans Dersi |
| Type | Normal |
| Mode of study | Yüz Yüze Öğretim |
| Catalog Information Coordinator | Prof. Dr. SELMA AYŞE ÖZEL |
| Course Instructor |
Dr. Öğr. Üyesi SERKAN KARTAL
(A Group)
(Ins. in Charge)
Dr. Öğr. Üyesi SERKAN KARTAL (B Group) (Ins. in Charge) |
Course Goal / Objective
Application of basic data structures designed to store and retrieve information in computer memory
Course Content
Data concept and data types, Lists, linked lists, queues, stacks, binary trees, compression algorithms, sorting algorithms, search algorithms and their applications
Course Precondition
Basic C programming knowledge is required.
Resources
WEISS M.A., DATA STRUCTURES ALGORITHM ANALYSIS IN C++, Addison Wesley, 1999.
Notes
Any reference related to C and C++
Course Learning Outcomes
| Order | Course Learning Outcomes |
|---|---|
| LO01 | Designing data structure |
| LO02 | Select the appropriate data structure |
| LO03 | Comparison of algorithms |
| LO04 | Data abstraction ability |
| LO05 | Writing more efficient programs |
Relation with Program Learning Outcome
| Order | Type | Program Learning Outcomes | Level |
|---|---|---|---|
| PLO01 | Bilgi - Kuramsal, Olgusal | Adequate knowledge of mathematics, science and related engineering disciplines; ability to use theoretical and applied knowledge in these fields in solving complex engineering problems. | 3 |
| PLO02 | Bilgi - Kuramsal, Olgusal | Ability to identify, formulate and solve complex engineering problems; ability to select and apply appropriate analysis and modeling methods for this purpose. | 4 |
| PLO03 | Bilgi - Kuramsal, Olgusal | 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. | |
| PLO04 | Bilgi - Kuramsal, Olgusal | Ability to select and use modern techniques and tools necessary for the analysis and solution of complex problems encountered in engineering practice; ability to use information technologies effectively. | |
| PLO05 | Bilgi - Kuramsal, Olgusal | Ability to design and conduct experiments, collect data, analyze and interpret results to investigate complex engineering problems or discipline-specific research topics. | 2 |
| PLO06 | Bilgi - Kuramsal, Olgusal | Ability to work effectively in interdisciplinary and multidisciplinary teams; individual working skills. | |
| PLO07 | Bilgi - Kuramsal, Olgusal | Ability to communicate effectively verbally and in writing; knowledge of at least one foreign language; ability to write effective reports and understand written reports, prepare design and production reports, make effective presentations, and give and receive clear and understandable instructions. | 4 |
| PLO08 | Bilgi - Kuramsal, Olgusal | Awareness of the necessity of lifelong learning; ability to access information, follow developments in science and technology, and constantly renew oneself. | 3 |
| PLO09 | Bilgi - Kuramsal, Olgusal | Knowledge of ethical principles, professional and ethical responsibility, and standards used in engineering practice. | 2 |
| PLO10 | Bilgi - Kuramsal, Olgusal | Knowledge of business practices such as project management, risk management and change management; awareness of entrepreneurship and innovation; knowledge of sustainable development. | |
| PLO11 | Bilgi - Kuramsal, Olgusal | Knowledge of the effects of engineering practices on health, environment and safety in universal and social dimensions and the problems of the age reflected in the field of engineering; awareness of the legal consequences of engineering solutions. |
Week Plan
| Week | Topic | Preparation | Methods |
|---|---|---|---|
| 1 | Basic data types and data concept | Reading the lecture notes | Öğretim Yöntemleri: Gösterip Yaptırma, Deney / Laboratuvar |
| 2 | Recursion concept | Reading the lecture notes | Öğretim Yöntemleri: Gösterip Yaptırma, Deney / Laboratuvar |
| 3 | Insertion, selection, buble sort algorithms | Reading the lecture notes | Öğretim Yöntemleri: Gösterip Yaptırma, Deney / Laboratuvar |
| 4 | Merge, heap, quick sort algorithms | Reading the lecture notes | Öğretim Yöntemleri: Gösterip Yaptırma, Deney / Laboratuvar |
| 5 | Sequential and binary search algorithms | Reading the lecture notes | Öğretim Yöntemleri: Gösterip Yaptırma, Deney / Laboratuvar |
| 6 | Hash search | Reading the lecture notes | Öğretim Yöntemleri: Gösterip Yaptırma, Deney / Laboratuvar |
| 7 | Single directional linked lists | Reading the lecture notes | Öğretim Yöntemleri: Gösterip Yaptırma, Deney / Laboratuvar |
| 8 | Mid-Term Exam | Reading the lecture notes | Ölçme Yöntemleri: Yazılı Sınav |
| 9 | Doubly linked lists | Reading the lecture notes | Öğretim Yöntemleri: Gösterip Yaptırma, Deney / Laboratuvar |
| 10 | Stack data structure | Reading the lecture notes | Öğretim Yöntemleri: Gösterip Yaptırma, Deney / Laboratuvar |
| 11 | Queue data structure | Reading the lecture notes | Öğretim Yöntemleri: Gösterip Yaptırma, Deney / Laboratuvar |
| 12 | Binary search tree data structure | Reading the lecture notes | Öğretim Yöntemleri: Gösterip Yaptırma, Deney / Laboratuvar |
| 13 | Other tree structures | Reading the lecture notes | Öğretim Yöntemleri: Gösterip Yaptırma, Deney / Laboratuvar |
| 14 | Data compression methods | Reading the lecture notes | Öğretim Yöntemleri: Gösterip Yaptırma, Deney / Laboratuvar |
| 15 | Graph algorithms | Reading the lecture notes | Öğretim Yöntemleri: Gösterip Yaptırma, Deney / Laboratuvar |
| 16 | Preparation to the Final Exam | Reading the lecture notes | Öğretim Yöntemleri: Soru-Cevap |
| 17 | Term Exams | Reading the lecture notes | Ölçme Yöntemleri: Yazılı Sınav |
Student Workload - ECTS
| Works | Number | Time (Hour) | Workload (Hour) |
|---|---|---|---|
| Course Related Works | |||
| Class Time (Exam weeks are excluded) | 14 | 2 | 28 |
| Out of Class Study (Preliminary Work, Practice) | 14 | 1 | 14 |
| Assesment Related Works | |||
| Homeworks, Projects, Others | 0 | 0 | 0 |
| Mid-term Exams (Written, Oral, etc.) | 1 | 4 | 4 |
| Final Exam | 1 | 8 | 8 |
| Total Workload (Hour) | 54 | ||
| Total Workload / 25 (h) | 2,16 | ||
| ECTS | 2 ECTS | ||