Objectives and competences
The objective of this course is for students to be able to demonstrate the basic knowledge of data structures and algorithms in telecommunications, to analyze them and to design new variants for the specific problems.
Content (Syllabus outline)
• Mathematical basics: combinatorics: variations, permutations, combinations; discrete structure: graph definitions and features, bipartite graphs, Eulerian graph, Hamiltonian graph, planar graph.
• Object-oriented programming: class, method, inheritance.
• Basic data structures: linear list, linked list, stack, queue, priority queues, hash table, trees.
• Graph: implementation of graphs and digraphs with static and dynamic data structures.
• Graph algorithms: searches in graphs and digraphs, shortest path, spanning tree, matchings in graphs, connectivity, graph coloring.
• Approximation and heuristic algorithms in edge-weighted graphs.
• Machine learning algorithms.
• Application to telecommunication: network design, routing in networks, accessibility, security, reliability, and fault tolerance.
Learning and teaching methods
• Lectures: in lectures, students get to know the theoretical contents of the course. Lectures are conducted as classical lectures in frontal form, interleaved with discussions on the practical application of data structures and algorithms.
• Tutorials: in tutorial exercises, students are informed about lab work.
• Lab work: in laboratory exercises, students apply acquired knowledge on problems from telecommunications. They improve their transferable skills by using an integrated development tool.
• Quizzes: in quizzes, students test their understanding of theoretical contents.
Intended learning outcomes - knowledge and understanding
• explain and describe basic discrete structures,
• apply basic algorithms on graphs,
• analyze the problem, select the appropriate data structure and algorithm, code and test the program,
• understand basic data structures
Intended learning outcomes - transferable/key skills and other attributes
• Communication skills: oral defense of computer skills.
• Use of information technology: use of software tools and programming environments.
• Problem-solving: problem analyzing, designing algorithms, coding, and testing of programs
Readings
• Mark A. Weiss, Data Structures and Algorithm Analysis in C++, Fourth Edition, Addison-Wesley, 2014.
• Thomas H. Cormen, Charles E. Leiserson, Ronald L. Rivest in Clifford Stein, Introduction to Algorithms, tretja izdaja. McGraw-Hill, 2001.
• S. Sartaj: Data Structures, Algorithms, and Applications in C++, Second Edition, Silicon Press, New York, 2005.
• M. T. Goodrich, R. Tamassia, D. M. Mount, Data Structures and Algorithms in C++, John Wiley & Sons, Inc., Second Edition, 2011.
Prerequisits
Basic programming skills are recommended.Conditions for course completion: to attend the written exam, the student must have at least 80% attendance on the laboratory work and a positive grade from the laboratory work.
Additional information on implementation and assessment The written exam may be substituted with continuous knowledge testing and assessment.
