Data Structures and Algorithms IILaajuus (4 cr)

Objective

After completing the course:
- Student knows how to analyse asymptotic time complexity of algorithms, including recursive algorithms.
- Student can measure and extrapolate running real time of programs.
- Student understands basic concepts of graphs, graph properties and graphs as abstract data types.
- Student understands elementary graph algorithms and is able to design, implement, and analyse simple graph algorithms.
- Student knows elementary algorithm strategies and is able to apply those.
- Student knows how to use mass storage efficiently and is able to analyse running time of algorithms using mass storage.

Content

- Algorithms and running time analysis.
- Experimental time complexity analysis.
- Graphs, graph algorithms, and applying graph algorithms.
- Using mass storage efficiently.

Qualifications

Data Structures and Algorithms I, or similar skills.

Materials

Thomas H. Cormen, Charles E. Leiserson, Ronald L. Rivest, Clifford Stein: Introduction to Algorithms, 3rd Ed. The MIT Press, 2009. Lecture notes.

Execution methods

Lectures 26 h, exercises 14 h, exam 3h, exercise implementation 50h, other study 14h.

Accomplishment methods

Exam + exercises.