Explain the basic types of data structures to students; Introduce students to typical computer problems and algorithms that use specified data structures as efficient solutions to these problems; Show students how to measure algorithm complexity and what it depends on; in the exercises, students learn to implement many known algorithms using efficient data structures.

Conditions for enrollment

The necessary requirements to enrol in the second year of the studies.

Course description

Introduction. From elementary data types to abstract data structures. The term algorithm. Algorithm complexity. Complexity analysis. “Big-O” notation. Linear data structures: arrays, linked lists, stacks, queues. Recursion. Sorting and searching algorithms and their implementation. Nonlinear data structures: multiple linked lists, trees. Binary trees and their special cases like binary search trees, Huffman trees and heaps.

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

Obligatory literature

1. 1 R. Manger Strukture podataka i algoritmi Element; 2014; ISBN: 978-953-197-596-4

2. 2 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]

Pretraži literaturu na:

1. 1 R. Sedgewick Algorithms in C: Fundamentals, Data Structures, Sorting, Searching and Graph Algorithms in C Addison Wesley; 2001; ISBN: 978-020-131-452-6

2. 2 Adam Drozdek Data Structures and Algorithms in C++ Course Technology; 2000; ISBN: 978-053-449-182-6

3. 3 D. E. Knuth The Art of Computer Programming, Vol. 1., Fundamental Algorithms Addison-Wesley, Reading, MA, 1997.

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

1. describe basic concepts related to algorithms and data structures

2. identify a suitable algorithm for a specific problem

3. select a suitable data structure for the purpose of building a software solution

4. perform complexity analysis of simpler algorithms

5. implement and use different algorithms and data structures

6. enable the use of known algorithms in combination with built-in data structures

7. apply the acquired knowledge in shaping software support that implies data management

Aktivnosti studenta: Vidi tablicu aktivnosti