ECTS - Advanced Algorithms
Advanced Algorithms (CMPE524) Course Detail
| Course Name | Course Code | Season | Lecture Hours | Application Hours | Lab Hours | Credit | ECTS |
|---|---|---|---|---|---|---|---|
| Advanced Algorithms | CMPE524 | Area Elective | 3 | 0 | 0 | 3 | 5 |
| Pre-requisite Course(s) |
|---|
| N/A |
| Course Language | English |
|---|---|
| Course Type | Elective Courses |
| Course Level | Natural & Applied Sciences Master's Degree |
| Mode of Delivery | Face To Face |
| Learning and Teaching Strategies | Lecture. |
| Course Lecturer(s) |
|
| Course Objectives | This course is designed to teach students how to analyse and design algorithms and measure their complexities. In addition, students will be able to develop efficient algorithms for the solution of real life computational problems. |
| Course Learning Outcomes |
The students who succeeded in this course;
|
| Course Content | Design and analysis of algorithms, O-notation, graph algorithms, topological sort, minimum spanning trees, single-shortest paths, all-pairs shortest paths, flow networks, NP-hard and NP-complete problems. |
Weekly Subjects and Releated Preparation Studies
| Week | Subjects | Preparation |
|---|---|---|
| 1 | Introduction: Growth of Functions | Chapters 1-3 (main text) |
| 2 | Introduction: Recurrences | Chapter 4 |
| 3 | Introduction: Sorting | Chapter 6-7 |
| 4 | Graphs, BFS, DFS | Chapter 22 |
| 5 | Topological Sort, Strongly Connected Components | Chapter 22 |
| 6 | Minimum Spanning Trees: Kruskall and Prim Algorithms | Chapter 23 |
| 7 | Single-Shortest Paths: Bellman-Ford Algorithm | Chapter 24 |
| 8 | Single-Shortest Paths: Dijkstra's Algorithm | Chapter 24 |
| 9 | All-Pairs Shortest Paths | Chapter 25 |
| 10 | Maximum-Flow: Flow networks | Chapter 26 |
| 11 | Maximum-Flow: Ford-Fulkerson's Algorithm | Chapter 26 |
| 12 | Maximum-Flow: Maximum Bipartite Matching | Chapter 26 |
| 13 | NP-Completeness | Chapter 34 |
| 14 | NP-Completeness | Chapter 34 |
| 15 | Review | |
| 16 | Review |
Sources
| Course Book | 1. T.H.Cormen, C.E.Leiserson, R.L.Rivest and C.Stein: Introduction to Algorithms, 2nd ed., MIT Press 2001. |
|---|---|
| Other Sources | 2. E.Horowitz, S.Sahni: Fundamentals of Computer Algorithms, Computer Science Press, 1989. |
| 3. E.Horowitz, S.Sahni, S.Rajasekeran, Computer Algorithms, ISBN: 978-0-929306-41-4, Silicon Press, 2008. | |
| 4. J.Kleinberg, E.Tardos, Algorithm Design, Addison – Wesley, ISBN: 0-321-29535-8, 2006. | |
| 5. A.V.Aho, J.E.Hopcroft, J.D.Ullman, The Design and Analysis of Computer Algorithms, Addison-Wesley Series in Computer Science and Information Processing, 1979. | |
| 6. S.S. Skiena, The Algorithm Design Manual, Springer – Verlag, New York, 1998. |
Evaluation System
| Requirements | Number | Percentage of Grade |
|---|---|---|
| Attendance/Participation | 1 | 5 |
| Laboratory | - | - |
| Application | - | - |
| Field Work | - | - |
| Special Course Internship | - | - |
| Quizzes/Studio Critics | - | - |
| Homework Assignments | 1 | 10 |
| Presentation | - | - |
| Project | - | - |
| Report | - | - |
| Seminar | - | - |
| Midterms Exams/Midterms Jury | 2 | 50 |
| Final Exam/Final Jury | 1 | 35 |
| Toplam | 5 | 100 |
| Percentage of Semester Work | 65 |
|---|---|
| Percentage of Final Work | 35 |
| Total | 100 |
Course Category
| Core Courses | X |
|---|---|
| Major Area Courses | |
| Supportive Courses | |
| Media and Managment Skills Courses | |
| Transferable Skill Courses |
The Relation Between Course Learning Competencies and Program Qualifications
| # | Program Qualifications / Competencies | Level of Contribution | ||||
|---|---|---|---|---|---|---|
| 1 | 2 | 3 | 4 | 5 | ||
| 1 | Gains the ability to apply advanced computing and/or information knowledge in solving software engineering problems. | X | ||||
| 2 | Develops solutions using different technologies, software architectures and life-cycle approaches. | X | ||||
| 3 | Gains the ability to design, implement, and evaluate a software system, component, process, or program using modern techniques and engineering tools for software engineering practices. | X | ||||
| 4 | Gains ability to gather/acquire, analyze, interpret data and make decisions to understand software requirements. | X | ||||
| 5 | Gains skills of effective oral and written communication and critical thinking about a wide range of issues arising in the context of working constructively on software projects. | X | ||||
| 6 | Gains the ability to access information to follow current developments in science and technology, conducts scientific research in the field of software engineering, and conducts a project. | X | ||||
| 7 | Acquires an understanding of professional, legal, ethical and social issues and responsibilities related to Software Engineering. | |||||
| 8 | Acquires project and risk management skills and gains awareness of the importance of entrepreneurship, innovation, and sustainable development, as well as international standards and methodologies. | X | ||||
| 9 | Understands the impact of Software Engineering solutions in a global, environmental, societal and legal context while making decisions. | |||||
| 10 | Gains awareness of the development, adoption, and ongoing support for the use of excellence standards in software engineering practices. | X | ||||
ECTS/Workload Table
| Activities | Number | Duration (Hours) | Total Workload |
|---|---|---|---|
| Course Hours (Including Exam Week: 16 x Total Hours) | 16 | 3 | 48 |
| Laboratory | |||
| Application | |||
| Special Course Internship | |||
| Field Work | |||
| Study Hours Out of Class | 16 | 3 | 48 |
| Presentation/Seminar Prepration | |||
| Project | |||
| Report | |||
| Homework Assignments | 1 | 5 | 5 |
| Quizzes/Studio Critics | |||
| Prepration of Midterm Exams/Midterm Jury | 2 | 8 | 16 |
| Prepration of Final Exams/Final Jury | 1 | 15 | 15 |
| Total Workload | 132 | ||