ECTS - Algorithms
Algorithms (CMPE323) Course Detail
| Course Name | Course Code | Season | Lecture Hours | Application Hours | Lab Hours | Credit | ECTS |
|---|---|---|---|---|---|---|---|
| Algorithms | CMPE323 | Area Elective | 3 | 0 | 0 | 3 | 7 |
| Pre-requisite Course(s) |
|---|
| CMPE226 |
| Course Language | English |
|---|---|
| Course Type | Elective Courses |
| Course Level | Bachelor’s Degree (First Cycle) |
| 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, divide and conquer algorithms, dynamic programming, backtracking and branch and bound, lower bound theory, complexity of sorting and searching algorithms, graph algorithms, NP-hard and NP-complete problems, basic NPC problems, proving problems to be NPC, analysis of some string processing algorithms. |
Weekly Subjects and Releated Preparation Studies
| Week | Subjects | Preparation |
|---|---|---|
| 1 | Introduction; Growth Functions | Chapters 1.1, 1.2, 3.1, 3.2 (main text) |
| 2 | Analyzing Algorithms: Insertion Sort | Chapters 2.1, 2.2 |
| 3 | Analyzing Algorithms: Merge Sort, Recurrences (The Recursion-Tree Method) | Chapter 2.3, 4 (introduction of chapter), 4.2 |
| 4 | Analyzing Algorithms: Quicksort and Analysis of Quicksort | Chapter 7.1, 7.2, 7.4, 5.2 |
| 5 | Red-Black Trees | Chapter 13.1, 13.2, 13.3 |
| 6 | Dynamic Programming | Chapter 15 (introduction of chapter), 15.1 |
| 7 | Dynamic Programming | Chapter 15.3, 15.2 |
| 8 | Dynamic Programming | Chapter 15.2 (cont.), 15.4 |
| 9 | Greedy Algorithms | Chapter 16.1, 16.2 |
| 10 | Greedy Algorithms | Chapter 16.2 (cont.), 16.3 |
| 11 | Graph Algorithms | Chapters 22.1, 22.2, 22.3 |
| 12 | Graph Algorithms | Chapters 22.4, 23 (introduction of chapter), 23.1, 23.2 (Kruskal) |
| 13 | Graph Algorithms | Chapters 24 (introduction of chapter), 24.1, 24.2 |
| 14 | Graph Algorithms, NP-Completeness | Chapter 24.2 (cont.), 24.3, 34 (introduction of chapter) |
| 15 | Review | - |
| 16 | Review |
Sources
| Course Book | 1. T.H.Cormen, C.E.Leiserson, R.L.Rivest and C.Stein: Introduction to Algorithms, MIT Press 2001. |
|---|---|
| Other Sources | 2. Anany Levitin, Introduction to the Design & Analysis of Algorithms, 3rd edition, Pearson, 2012. |
| 3. E.Horowitz, S.Sahni: Fundamentals of Computer Algorithms, Computer Science Press, 1989 | |
| 4. E.Horowitz, S.Sahni, S.Rajasekeran, Computer Algorithms, ISBN: 978-0-929306-41-4, Silicon Press, 2008. | |
| 5. J.Kleinberg, E.Tardos, Algorithm Design, Addison – Wesley, ISBN: 0-321-29535-8, 2006. | |
| 6. 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. | |
| 7. 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 | 3 | 10 |
| Presentation | - | - |
| Project | - | - |
| Report | - | - |
| Seminar | - | - |
| Midterms Exams/Midterms Jury | 2 | 50 |
| Final Exam/Final Jury | 1 | 35 |
| Toplam | 7 | 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 | Gain sufficient knowledge in mathematics, science and computing; be able to use theoretical and applied knowledge in these areas to solve engineering problems related to information systems. | |||||
| 2 | To be able to identify, define, formulate and solve complex engineering problems; to be able to select and apply appropriate analysis and modeling methods for this purpose. | X | ||||
| 3 | Designs a complex system, process, device or product under realistic constraints and conditions to meet specific requirements; applies modern design methods for this purpose. | X | ||||
| 4 | To be able to develop, select and use modern techniques and tools required for the analysis and solution of complex problems encountered in information systems engineering applications; to be able to use information technologies effectively. | X | ||||
| 5 | Designs and conducts experiments, collects data, analyzes and interprets results to investigate complex engineering problems or research topics specific to the discipline of information systems engineering. | |||||
| 6 | Can work effectively in disciplinary and multidisciplinary teams; can work individually. | |||||
| 7 | a. Communicates effectively both orally and in writing; writes effective reports and understands written reports, prepares design and production reports, makes effective presentations, gives and receives clear and understandable instructions. b. Knows at least one foreign language. | |||||
| 8 | To be aware of the necessity of lifelong learning; to be able to access information, to be able to follow developments in science and technology and to be able to renew himself/herself continuously. | |||||
| 9 | a. Acts in accordance with the principles of ethics, gains awareness of professional and ethical responsibility. b. Gains knowledge about the standards used in information systems engineering applications. | |||||
| 10 | a. Gains knowledge about business life practices such as project management, risk management and change management. b. Gains awareness about entrepreneurship and innovation. c. Gains knowledge about sustainable development. | |||||
| 11 | a. To be able to acquire knowledge about the universal and social effects of information systems engineering applications on health, environment and safety and the problems of the era reflected in the field of engineering. b. Gains awareness of the legal consequences of engineering solutions. | |||||
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 | 3 | 6 | 18 |
| Quizzes/Studio Critics | |||
| Prepration of Midterm Exams/Midterm Jury | 2 | 20 | 40 |
| Prepration of Final Exams/Final Jury | 1 | 20 | 20 |
| Total Workload | 174 | ||