Main Field of Study and progress level:
Computing Science: Second cycle, has only first-cycle course/s as entry requirements
Grading scale: Pass with distinction, Pass with merit, Pass, Pass with distinction, Pass, Fail
Responsible department: Department of Computing Science
Established by: Faculty Board of Science and Technology, 2016-08-29
Revised by: Faculty Board of Science and Technology, 2017-10-02
Contents
The course covers data structures and techniques for constructing efficient algorithms, including their analysis with respect to efficiency. It stresses the importance of adapting standard algorithms and data structures to the peculiarities of both the given problem and the underlying hardware, because efficiency does not only depend on the intrinsic asymptotic efficiency of an algorithm, but also on the context in which it is applied.
Typical algorithmic techniques are divide-and-conquer, greedy methods, and dynamic programming. As efficient data structures form the basis for many of these techniques, important data structures, their analysis and advantages and disadvantages depending on circumstances are covered as well. Examples of data structures to be covered are heaps, priority queues, and tree data structures.
Required Knowledge
Univ: To be admitted you must have (or equivalent) 60 ECTS-credits in Computing Science or two years of completed studies (120 ECTS-credits). In both cases, the studies must include at least 7.5 ECTS-credits with in discrete mathematics and at least 7.5 ECTS-credits within data strutuces and algorithms.
Proficiency in English equivalent to Swedish upper Secondary course English A/5. Where the language of instruction is Swedish, applicants must prove proficiency in Swedish to the level required for basic eligibility for higher studies.
Literature
The literature list is not available through the web.
Please contact the faculty.
