Principles for construction of algorithms: Divide and conquer, greedy algorithms, dynamic programming, local and exhaustive search. Algorithm analysis. Approximation algorithms and heuristics. Selected applications to sets, graphs, arithmetic, and geometry.
Data structures: Review of hash tables and heaps; balanced trees and Bloom filters. Use and implementation of data structures.
Computability and complexity: Reductions. Complexity classes P (polynomial time) and NP (non-deterministic polynomial time). NP-complete problems. Undecidable problems. Coping with untractable problems.
Terminology in Swedish and English.