Algorithms and Data Structures, MSc
Computers help us compute things: To sort alphabetically the entries in a telephone directory; to compute the next frame of a video game; to find the seats available on an airplane. However, there are faster and slower ways to compute things. To be an effective programmer, you must know not only how to make a computer compute things, but how to efficiently compute things.
This course provides the basic algorithmic tools indispensible for every software developer.
Topics covered are among others complexity analysis, big-O, algorithmic problem solving techniques including divide-and-conquer, concrete algorithms and data structures for search trees, sorting, hashing, graphs, shortest paths.
Formal prerequisitesThe course Discrete Mathematics or similar. The course Introductory Programming or similar. ----- Information about the course of study This course is mandatory for students who are enrolled on the MSc in Software Design.
Intended learning outcomes
After the course, the student should be able to:
- Discuss and clearly explain the mechanics of computations and data structures involving manipulation of references, nested loops and recursion, specified in natural language, in abstract pseudocode or in concrete programming language (Java/Python).
- Implement abstractly specified computations and data structures in an imperative programming language (Java/Python).
- Analyze time and space usage of algorithms/programs.
- Assess scalability of a given single-threaded software application, using asymptotic analysis.
- Choose among and make use of the most important algorithms and data structures in libraries, based on knowledge of their complexity.
- Design algorithms for ad hoc problems by using and combining known algorithms and data structures
- Describe the most important hardware and programming language factors influencing the speed at which a program runs and take them into account in assessment of speed of algorithms.