(KUOPIO): Data Structures and Algorithms I (TRAI) (5 cr)

Evaluation scale

Five step scale

Objective

Learning outcomes: The student will understand the importance of algorithms and can analyse asymptotic time complexity of simple algorithms can select and reason about a correct data structure (abstract data type) for an application and use the chosen structure efficiently can use efficiently the standard library of his/her programming language knows and can implement most common abstract data types, list, tree, and set can design and implement an algorithm for a simple problem knows the principle of recursion and can implement a recursive algorithm

Content

Algorithms and running time analysis. Abstract data types. Implementing data structures. Searching and sorting algorithms. Simple recursive algorithms

Materials

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

Teaching methods

Modes of study: Course exam and exercises, or general exam. Lectures 32h, exercises 16h, course exam 3h, making exercises 64h, other independent learning 18h. Evaluation criteria: Course exam 35%, graded exercises 35%, weekly tests 20%, other exercises 10% + bonus max 10% (attendance required for this 10+10%).

Qualifications

Object-oriented programming