CEN215 Data Structures Lab.

2 ECTS - 0-2 Duration (T+A)- 3. Semester- 1 National Credit

Information

Code CEN215
Name Data Structures Lab.
Term 2022-2023 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 EZGİ ZORARPACI (A Group) (Ins. in Charge)
EZGİ ZORARPACI (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

Update Time: 17.11.2022 05:05