Algorithms and Data Structures III
Syllabus, Master's level, 1DL481
- Education cycle
- Second cycle
- Main field(s) of study and in-depth level
- Computer Science A1N
- Grading system
- Fail (U), Pass (3), Pass with credit (4), Pass with distinction (5)
- Finalised by
- The Faculty Board of Science and Technology, 27 April 2016
- Responsible department
- Department of Information Technology
120 credits including 30 credits in mathematics and 45 credits in computer science. Participation in Algorithms and Data Structures II.
To pass the course, the student must be able to
- analyse NP-completeness of an algorithmic problem;
- use advanced algorithm analysis methods, such as amortised analysis and probabilistic analysis;
- use advanced algorithm design methods in order to approach hard algorithmic problems in a pragmatic way, such as by using randomised algorithms (such as universal hashing), approximation algorithms, stochastic local search (such as simulated annealing and tabu search), integer programming, propositional satisfiability (SAT), and SAT modulo theories (SMT).
NP-completeness. Advanced techniques in algorithm analysis and design such as amortised and probabilistic analysis, universal hashing, integer programming, simulated annealing, tabu serach, probabilistic satisfiability (SAT). Connections to modern research in algorithmics.
Lectures, lessons and exercises.
Written and oral presentation of assignments, 2 credits, and written and oral exam, 3 credits.
The course cannot be included in a degree together with the courses Algorithms and data structures (DV)3/III (1DL104, 1DL113, 1DL030) and Advanced algorithmics (1DL480).