TÜRKÇE
ENGLISH
Information
| Code | CEN215 |
| Name | Data Structures Lab. |
| Term | 2023-2024 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 | Has capability in the fields of mathematics, science and computer that form the foundations of engineering | 3 |
| PLO02 | Bilgi - Kuramsal, Olgusal | Identifies, formulates, and solves engineering problems, selects and applies appropriate analytical methods and modeling techniques, | 4 |
| PLO03 | Bilgi - Kuramsal, Olgusal | 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. | |
| PLO04 | Bilgi - Kuramsal, Olgusal | Ability to use modern techniques and tools necessary for engineering practice and information technologies effectively. | |
| PLO05 | Bilgi - Kuramsal, Olgusal | Ability to design and to conduct experiments, to collect data, to analyze and to interpret results | 2 |
| PLO06 | Bilgi - Kuramsal, Olgusal | Has ability to work effectively as an individual and in multi-disciplinary teams, take sresponsibility and builds self-confidence | |
| PLO07 | Beceriler - Bilişsel, Uygulamalı | Can access information,gains the ability to do resource research and uses information resources | 4 |
| PLO08 | Beceriler - Bilişsel, Uygulamalı | Awareness of the requirement of lifelong learning, to follow developments in science and technology and continuous self-renewal ability | 3 |
| PLO09 | Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği | Ability to communicate effectively orally and in writing, and to read and understand technical publications in at least one foreign language | 2 |
| PLO10 | Yetkinlikler - Öğrenme Yetkinliği | Professional and ethical responsibility, | |
| PLO11 | Yetkinlikler - Öğrenme Yetkinliği | Awareness about project management, workplace practices, employee health, environmental and occupational safety, and the legal implications of engineering applications, | |
| PLO12 | Yetkinlikler - Öğrenme Yetkinliği | Becomes aware of universal and social effects of engineering solutions and applications, entrepreneurship and innovation, and knowledge of contemporary issues |
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 | ||