Undergraduate study programme

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Algorithms and Data Structures PR302

ECTS 6 | P 45 | A 15 | L 15 | K 0 | ISVU 41086 | Academic year: 2019./2020.

Course groups

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Course lecturers

GALBA TOMISLAV, Associate
BAUMGARTNER ALFONZO, Lecturer

Course description

Algorithm, representation, computer implementation. Algorithm complexity. Errors caused by numeric data representation in a digital computer. Complex data structures: list, tree, graph; computer implementation. Searching and sorting algorithms. Random number generation by uniform, exponential and normal distribution. Generator evaluation, statistical tests. Recursive algorithms. Recursion, computer implementation, resource allocation.

Knowledge and skills acquired

Algorithm development and implementation. Implementation of complex programming solutions in C programming language.

Teaching methods

Lectures and laboratory exercises.

Student requirements

Defined by the Student evaluation criteria of the Faculty of Electrical Engineering, Computer Science and Information Technology Osijek and paragraph 1.9

Monitoring of students

Defined by the Student evaluation criteria of the Faculty of Electrical Engineering, Computer Science and Information Technology Osijek and paragraph 1.9

Student assessment

Assessment of laboratory exercises, revision exams.

Obligatory literature

1. 1 Cormen, Thomas H.; Leiserson, Charles E.; Rivest, Ronald L.; Stein, Clifford Introduction to Algorithms (3rd ed.) MIT Press and McGraw-Hill. ISBN 0-262-03384-4. (2009) [1990]

2. 2 D. E. Knuth The Art of Computer Programming, Vol. 1., Fundamental Algorithms Addison-Wesley, Reading, MA, 1997.

3. 3 D. E. Knuth The Art of Computer Programming, Vol. 2., Seminumerical Algorithms Addison-Wesley, Reading, MA, 1998.


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Examination methods

Written and oral exam.

Course assessment

Conducting university questionnaires on teachers (student-teacher relationship, transparency of assessment criteria, motivation for teaching, teaching clarity, etc.). Conducting Faculty surveys on courses (upon passing the exam, student self-assessment of the adopted learning outcomes and student workload in relation to the number of ECTS credits allocated to activities and courses as a whole).

Overview of course assesment

Learning outcomes
Upon successful completion of the course, students will be able to:

1. describe basic terms related to algorithms and data structures

2. use basic linear and non-linear data structures: linked list, queue, stack, tree, graph

3. use known and important efficient algorithms for sorting and searching

4. write new algorithms by using a pseudocode or flow diagram

5. evaluate algorithms by using the basics of computational complexity theory



Aktivnosti studenta: Vidi tablicu aktivnosti