5024 - Algorithms and Data Structures
Course information
Title
Algorithms and Data Structures
Course number
5024.24
Academic year
2024-2025
ECTS
7.50
Level
Bachelor
Faculties
Science and Tecnology
Educations
BSc in Software Engineering
Prerequisites
Upper secondary school with mathematics at level B
Language of instruction
The course is taught in English. The textbook is in English and other instructional materials are in English, and possibly Faroese. Exams will be in English.
Registration
Students on the first and third semester of Bachelor of Science in Software Engineering are automatically enrolled. Applicants for an individual course must apply via the Student Service Center at lss@setur.fo
Beginning date
Thursday, August 22, 2024
End date
Thursday, October 10, 2024
Academic content
Purpose
To introduce the notation, terminology, and techniques underpinning the study of algorithms - To introduce the standard algorithmic design paradigms employed in the development of efficient algorithmic solutions - To introduce the mathematical tools needed for the analysis of algorithms in terms of the use of formal models of Time and Space
Learning outcomes
By the end of the course the student is expected to be able to: - describe standard algorithms such as sorting algorithms, search algorithms, string matching algorithms, graph traversal algorithms; - apply these algorithms or a given pseudo code algorithm in order to solve a given problem; - carry out simple asymptotic analyses of algorithms involving sequence, selection, and iteration, and identify and compare simple properties of these algorithms; - describe the algorithm design principles of Divide-and-Conquer, greedy method, and dynamic programming and distinguish the differences between these principles; - apply the studied algorithms that illustrate these design principles; - apply the studied design principles to produce algorithmic solutions to a given problem; - explain and illustrate the distinction between different classes of problems, in particular, polynomial time and exponential time solvable problems.
Content
Introduction o Definition of an algorithm, counting elementary operations during execution, worst-case analysis of running time and storage requirements - on several examples of simple algorithms o Design of pseudo code algorithms • Complexity Issues o Asymptotics and "order of" notation for complexity o Comparison of polynomial time and exponential time complexities and examples of algorithms with such complexities o Brief introduction of the notion of computable and non-computable functions • Review of Graphs structures and their representation o Directed and Undirected graphs; Trees; representation by adjacency matrices and incidence lists, graph and tree traversals • Algorithm Design Techniques o Review of the standard algorithm design paradigms commonly used in Computer Science together with typical example problems solved by these o Overview: why a range of design methods is needed o Divide-and-Conquer algorithms: general overview of approach; run-time analysis of simple Divide-and-Conquer methods via solution of recurrence relations o Dynamic Programming: differences from Divide-and-Conquer; general overview; necessity for iterative implementation o Greedy Method: concept of optimisation problem and the distinction between 'exact' and 'approximate' solution algorithms
Learning and teaching approaches
Lectures, theoretical- and computer-based exercises
Assessment
Assessment method
▪ one or two assessments will be given during the lectures o 0% contribution to the final marks but we strongly recommend you to pass these assignments although it is not a necessary condition to get the permission for the examination ▪ 4-hour written examination (paper and pen based) o course related materials are NOT allowed o 100% contribution to the final marks
Examination (internal/external)
External
Grading scale
7-scale
Exam date/dates
The written exam is set for week 43
Deadline for withdrawal from exam
Thursday, August 22, 2024
Academic responsibility and teachers
Academic responsibility
Qin Xin
Teachers
Qin Xin
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