DD1352 Algorithms, Data Structures and Complexity 9.0 credits

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.

On completion of the course, the students should be able to:

• develop and implement algorithms with data structures and analyze them with respect to correctness and efficiency,
• compare alternative algorithms and data structures with respect to efficiency and reliability,
• define and translate central concepts such as P, NP, NP-completeness and undecidability,
• compare problems with respect to complexity using reductions,
• explain how problems of high complexity can be handled

so that they will be able to

• independently construct computer programs that use time and memory efficiently,
• in professional life identify and attack problems that are unrealistically resource demanding or not possible to solve on a computer.

For non-program students: completed upper secondary education including documented proficiency in Swedish corresponding to Swedish B, English corresponding to English A. Furthermore: 15 hp in mathematics, including discrete mathematics and probability, and 12 hp in computer science or programming.

DD1339/DD1340/DD1341 Introduction to Computer Science (or DD1320/DD1321/DD1345, SF1630/SF1631 Discrete Mathematics (can be taken concurrently), and SF1901 Probability Theory and Statistics, or the equivalent.

Kleinberg-Tardos: Algorithm Design, 2005, Pearson, ISBN 978-0321372918 +

Algorithms and Complexity, a supplement to Algorithm Design, Pearson Custom Publishing, ISBN 978-1847764126.

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

• LAB1 - Laboratory Assignments, 3.0 credits, grading scale: P, F
• MAS1 - Master's test, 1.5 credits, grading scale: A, B, C, D, E, FX, F
• MAS2 - Master's test, 1.5 credits, grading scale: A, B, C, D, E, FX, F
• TEN2 - Examination, 3.0 credits, grading scale: A, B, C, D, E, FX, 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.

Under special circumstances, other examination formats may be used.

In this course, the code of honor of the school is applied, see: http://www.kth.se/csc/student/hederskodex.

The final grade is the minimum grade of MAS1, MAS2 and TEN2. 

Viggo Kann

• 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.

Further information about the course can be found on the Course web at the link below. Information on the Course web will later be moved to this site.

DD2440 Advanced Algorithms, DD2441 Seminars in Theoretical Computer Science, DD2445 Complexity Theory, DD2448 Foundations of Cryptography, DD2450 Algorithmic Bioinformatics, and DD2458 Problem Solving and Programming under Pressure.

The course will be replaced from 2017/2018 by the new course DD2350.

Only one of the following courses may be included in your degree: 2D1352, 2D1353, 2D1354, DD1352, DD2350, DD2352, DD2354.