On completion of the course, the student should be able to:
analyse the runtime performance of a (simple) algorithm/program in terms of the size of its inputs, and this in the average, best, and worst cases.
choose appropriate algorithms and data structures for storing data, searching and sorting, as well as implement those algorithms.
use and implement basic graph algorithms.
Mathematical foundations: asymptotic notation, summations, recurrence relations. Data structures: trees, FIFO queue, stack, priority queues, heaps. Searching: binary search trees, balanced search trees, hash tables. Sorting: insertion sort, merge sort, quick sort, heap sort. Graph algorithms: depth first and breadth first search, topological sort and (strongly) connected components. Design techniques: divide-and-conquer. Implementation of algorithms and data structures.
Lectures, laboratory work, lessons, and mandatory assignments.
Written exam (4 p). Assignments (1 p).
If there are special reasons for doing so, an examiner may make an exception from the method of assessment indicated and allow a student to be assessed by another method. An example of special reasons might be a certificate regarding special pedagogical support from the disability coordinator of the university.
The unit cannot be included in a degree with Program Design II (1IT022), nor with Data Structures (1DL009, 1TD191, 1MB026).