Design principles of algorithms: Divide and conquer, greedy algorithms, dynamic programming. Algorithm analysis. Probabilistic algorithms. Approximation algorithms. Selected applications in sets, graphs, arithmetic and geometry. Implementation of algorithms.

Computability and complexity: Reductions. The complexity classes P (polynomial time), NP (non-deterministic polynomial time), PSPACE (polynomial space) and BPP (probabilistic polynomial time with bounded error). NP completeness and NP hardness reductions. Undecidable problems.

After passing the course, the student should be able to

• develop and implement algorithms and reductions, and analyse them with respect to correctness and efficiency
• compare alternative algorithms considering efficiency
• define and explain central concepts such as P, NP, NP-completeness and undecidability
• compare problems with respect to complexity by means of reductions

in order to

• independently be able to design computer programs that use time and memory efficiently and thereby can contribute to economically and environmentally sustainable development
• in professional life identify problems that are unrealistically resource demanding or not possible to solve on a computer.

All details are found in the course Canvas room which for 2026 is located at https://canvas.kth.se/courses/59186 

Knowledge of discrete mathematics is necessary. A student who, at the beginning of the course, has not completed 7.5 higher education credits of discrete mathematics, equivalent to SF1610/SF1662/SF1679/SF1688, must take one of these courses in parallel with DD2352, see Additional Regulations in the course syllabus.

Knowledge of probability theory equvalent to for example SF1901 Probability Theory and Statistics is recommended but could be learnt during the course.

Kleinberg, Tardos; "Algorithm Design", Pearson Addison-Wesley.

Students at KTH with a permanent disability can get support during studies from Funka:

Funka - compensatory support for students with disabilities

• MAS2 - Mastery Test, 1.5 credits, grading scale: A, B, C, D, E, FX, F
• MAS1 - Mastery Test, 1.5 credits, grading scale: A, B, C, D, E, FX, F
• TEN1 - Examination, 3.0 credits, grading scale: A, B, C, D, E, FX, F
• LAB1 - Laboratory Work, 1.5 credits, grading scale: P, F

Based on recommendation from KTH’s coordinator for disabilities, the examiner will decide how to adapt an examination for students with documented disability.

The examiner may apply another examination format when re-examining individual students.

If the course is discontinued, students may request to be examined during the following two academic years.

Labs and mastery tests are examined both orally and in writing. The exam is written.

The grading criteria for 2026 are documented here.

• All members of a group are responsible for the group's work.
• In any assessment, every student shall honestly disclose any help received and sources used.
• In an oral assessment, every student shall be able to present and answer questions about the entire assignment and solution.

A student who, at the beginning of the course, has not completed 7.5 higher education credits of discrete mathematics, equivalent to SF1610/SF1662/SF1679/SF1688, must take one of these courses in parallel with DD2352.