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Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS BIL 2009 GRAPHY THEORY COMPULSORY 4 0 0 6

Offered By

Computer Science

Level of Course Unit

First Cycle Programmes (Bachelor's Degree)

Course Coordinator

ASSOCIATE PROFESSOR ZEYNEP NIHAN BERBERLER

Offered to

Computer Science

Course Objective

To teach graph theory concepts to solve computer science problems.

Learning Outcomes of the Course Unit

1   Have a knowledge of basic concepts of graph theory. 2   Be able to solve problems of graph theory. 3   Be able to solve computer science problems by using graph theory concepts. 4   Be able to design efficient algorithms by using graph theory concepts. 5   Be able to solve problems of different type of disciplines by using concepts of graph theory.

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description 1 Fundamental Concepts What is a graph Paths, cycles and trails 2 Fundamental Concepts (continues to ) Vertex degrees and counting Directed graphs 3 Trees and distance Basic properties Spanning trees and enumeration 4 Trees and distance (continues to ) Optimization and trees Quiz 1 5 Matching Matching and covers Matching algorithms and applications Matching in general graphs 6 Connectivity and paths Cuts and connectivity k-connected graphs 7 Connectivity and paths (continues to ) Network flow problems 8 Mid-term exam 9 Coloring of graphs Vertex coloring and upper bounds Structure of k-chromatic graphs 10 Coloring of graphs (continues to ) Enumerative aspects 11 Edge and cycles Line graphs and edge-coloring Hamiltonian cycles Planarity, coloring and cycles 12 Basic graph theory algorithms Representation of graphs on computers Breadth-first search Depth-first search Strongly connected components Quiz 2 13 Minimum Spanning Trees The algorithm of Prim The algorithm of Kruskal 14 Shortest Path Algorithms The algorithm of Dijkstra The algorithm of Bellman-Ford The algorithm of Floyd-Warshall Maximum Flow Algorithms The algorithm of Ford-Fulkerson The algorithm of Edmonds-Karp

Recomended or Required Reading

Textbook(s): Introduction to Graph Theory, Dougles West, ISBN 0130144002. Supplementary Book(s): Handbook of Graph Theory, Jonathan L. Gross, Jay Yellen, ISBN 1-58488-090-2.

Planned Learning Activities and Teaching Methods

The course is taught in a lecture, class presentation and discussion format. Besides the taught lecture, group presentations are to be prepared by the groups assigned and presented in a discussion session. In some weeks of the course, results of the homework given previously are discussed.

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA 1 MTE MIDTERM EXAM 2 FIN FINAL EXAM 3 FCG FINAL COURSE GRADE MTE * 0.40 + FIN * 0.60 4 RST RESIT 5 FCGR FINAL COURSE GRADE (RESIT) MTE * 0.40 + FIN * 0.60 *** Resit Exam is Not Administered in Institutions Where Resit is not Applicable.

Further Notes About Assessment Methods

None

Assessment Criteria

To be announced.

Language of Instruction

Turkish

Course Policies and Rules

To be announced.

Contact Details for the Lecturer(s)

zeynep.berberler@deu.edu.tr

Office Hours

Will be announced.

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours) Lectures 13 4 52 Preparations before/after weekly lectures 12 5 60 Preparation for midterm exam 1 12 12 Preparation for final exam 1 12 12 Final 1 2 2 Midterm 1 2 2 TOTAL WORKLOAD (hours) 140

Contribution of Learning Outcomes to Programme Outcomes

PO/LO PO.1 PO.2 PO.3 PO.4 PO.5 PO.6 PO.7 PO.8 PO.9 PO.10 PO.11 PO.12 PO.13 LO.1 5 LO.2 5 5 LO.3 5 5 5 LO.4 5 5 LO.5 5 5