Algorithms and Data Structures

Methods for analysing the efficiency of algorithms, divide and conquer techniques, recursive solution methods. Methods for ordering, searching and sorting. Data structures for efficient retrieval of data, dynamic programming and greedy algorithms. Data structures for implementing graphs and networks, as well as methods for traversals and searches. Algorithms for finding the best path(s) and matchings, spanning trees and maximum flow. Theory of problem complexity. Algorithms are expressed in a language-independent manner.

Knowledge: The candidate should have knowledge about (1) a broad spectrum of established algorithms that are useful in several areas of application, (2) classical algorithmic problems with known efficient solutions, and (3) complex problems without known efficient solutions.

Skills: The candidate should be able to (1) analyze the efficiency of an algorithm to achieve good solutions for a given problem, (2) formulate a problem so it can be handled in a rational manner by an algorithm, and (3) use well-known design methods to construct new efficient algorithms.

General competence: The candidate should be able to (1) use well-known algorithms and available program modules on new problems, and (2) develop and implement new solutions for complex problems with a basis in practical reality.

Lectures and individual exercises.