SEN2212 Data Structures and Algorithms IIBahçeşehir UniversityDegree Programs ELECTRICAL AND ELECTRONICS ENGINEERINGGeneral Information For StudentsDiploma SupplementErasmus Policy StatementNational QualificationsBologna Commission
ELECTRICAL AND ELECTRONICS ENGINEERING
Bachelor TR-NQF-HE: Level 6 QF-EHEA: First Cycle EQF-LLL: Level 6

Course Introduction and Application Information

Course Code Course Name Semester Theoretical Practical Credit ECTS
SEN2212 Data Structures and Algorithms II Fall 2 2 3 7
This catalog is for information purposes. Course status is determined by the relevant department at the beginning of semester.

Basic information

Language of instruction: English
Type of course: Non-Departmental Elective
Course Level: Bachelor’s Degree (First Cycle)
Mode of Delivery: Face to face
Course Coordinator : Dr. Öğr. Üyesi BETÜL ERDOĞDU ŞAKAR
Course Lecturer(s): Dr. Öğr. Üyesi BETÜL ERDOĞDU ŞAKAR
Dr. Öğr. Üyesi YÜCEL BATU SALMAN
RA SEVGİ CANPOLAT
RA MERVE ARITÜRK
Recommended Optional Program Components: None
Course Objectives: The objective of this course is to analyze data structures and algorithms used in software engineering in detail. After completing the course, the student will have knowledge of applying, implementing and analysis of data structures, including, trees, binary search trees, balanced search trees, heaps and graphs. Certain fundamental techniques, such as sorting, hashing and greedy algorithms are also taught.

Learning Outcomes

The students who have succeeded in this course;
The students who have succeeded in this course;
1) Describe and apply basic object oriented programming principles.
2) Implement basic data structures such as trees, binary search trees, balanced search trees, heaps and graphs.
3) Describe and implement sorting algorithms on common data structures.
4) Describe and implement searching algorithms on common data structures.
5) Implement and use hashing algorithms.
6) Implement and use greedy algorithms.
7) Choose and design data structures for writing efficient programs.


Course Content

The course content is composed of basic data structures like trees, binary search trees, balanced search trees, heaps, graphs and sorting, hashing and greedy algorithms.

Weekly Detailed Course Contents

Week Subject Related Preparation
1) Introduction and Sorting Algorithms. Sorting algorithms.
2) Introduction to different tree structures. Trees.
3) Introduction to binary search trees. Binary search trees.
4) Implementing binary search tree using Java. Binary search trees.
5) Introduction to balanced trees and implementing AVL balanced tree structure using Java. AVL trees.
6) Using other balanced tree structure using Java. Other balanced trees.
7) Using heap structure and implementing them using Java. Heap.
8) Using heaps as priority queues. Midterm. Heap.
9) Analyzing and implementing hashing algorithms. Hashing algorithms.
10) Analyzing and implementing graph structure using Java. Graph.
11) Analyzing and implementing graph algorithms. Graph algorithms.
12) Analyzing and implementing greedy algorithms. Greedy algorithms.
13) Analyzing and implementing greedy algorithms. Quiz. Greedy algorithms.
14) Review.

Sources

Course Notes / Textbooks: Data Structures & Problem Solving Using Java (Mark Allen Weiss)
Data Structures and Algorithm Analysis in Java (Mark Allen Weiss)
Data Structures and Abstractions with Java (Frank Carrano)
References: Yok.

Evaluation System

Semester Requirements Number of Activities Level of Contribution
Application 4 % 10
Quizzes 1 % 10
Project 1 % 15
Midterms 1 % 25
Final 1 % 40
Total % 100
PERCENTAGE OF SEMESTER WORK % 45
PERCENTAGE OF FINAL WORK % 55
Total % 100

ECTS / Workload Table

Activities Number of Activities Duration (Hours) Workload
Course Hours 14 2 28
Laboratory 14 2 28
Study Hours Out of Class 12 2 24
Project 10 2 20
Homework Assignments 2 5 10
Quizzes 5 2 10
Midterms 5 3 15
Final 10 3 30
Total Workload 165

Contribution of Learning Outcomes to Programme Outcomes

No Effect 1 Lowest 2 Low 3 Average 4 High 5 Highest
           
Program Outcomes Level of Contribution
1) Adequate knowledge in mathematics, science and electric-electronic engineering subjects; ability to use theoretical and applied information in these areas to model and solve engineering problems.
2) Ability to identify, formulate, and solve complex engineering problems; ability to select and apply proper analysis and modeling methods for this purpose.
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. (Realistic constraints and conditions may include factors such as economic and environmental issues, sustainability, manufacturability, ethics, health, safety issues, and social and political issues, according to the nature of the design.)
4) Ability to devise, select, and use modern techniques and tools needed for electrical-electronic engineering practice; ability to employ information technologies effectively.
5) Ability to design and conduct experiments, gather data, analyze and interpret results for investigating engineering problems.
6) Ability to work efficiently in intra-disciplinary and multi-disciplinary teams; ability to work individually.
7) Ability to communicate effectively in English and Turkish (if he/she is a Turkish citizen), both orally and in writing.
8) Recognition 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) Awareness of professional and ethical responsibility.
10) Information about business life practices such as project management, risk management, and change management; awareness of entrepreneurship, innovation, and sustainable development.
11) Knowledge about contemporary issues and the global and societal effects of engineering practices on health, environment, and safety; awareness of the legal consequences of engineering solutions.