Download Data Structures and Algorithms

Study program: INFORMATION TECHNOLOGY
Type and level of studies: Undergradueted Studies (first level of studies)
Course unit: Data Structures and Algorithms
Teacher in charge: Bratislav Iričanin
Language of instruction: English
ECTS: 6
Prerequisites: Introduction to programming, Programming Languages
Semester: Fall
Course unit objective
Upgrading the basic principles of programming; Introduction to basic data structures, abstract data types and
algorithms on data structures. Application of algorithms for solving specific problems is essential for software
development. Studying the underlying data structure is an important prerequisite for programming.
Learning outcomes of Course unit
Students are study modern techniques of programming and software development. Qualifying students for the
implementation of various data structures and algorithms in the Java programming language.
Course unit contents
Theoretical classes
Definitions and concepts of data structures. Abstract data types. Linear and nonlinear structures. A onedimensional and multidimensional arrays. The stacks. Queues. Lists. Time and space complexity of algorithms.
Sorting algorithms (Selection, Bubble, Insertion sort, ...). Algorithms for search data (sequential, binary,
interpolation, ...). Trees. Binary trees. The binary search tree. Graphs. Depth First Searach Algorithm (DFS),
Bredth First Searach Algorithm (BFS). The minimum spanning tree. Topological sorting.Practical classes
Students prepare for solving tasks of data structures and algorithms. Application of software MatrixPro
simulation and animation of data structures and algorithms. Solving exercise generated within the MatrixPro
software.
Literature
1.
Mark Allen Weiss: Data Structures and Algorithm Analysis in Java, Florida International University,
Publisher: Pearson, 2012, 614 p.
2.
Michael Goodreach, Roberto Tamassia, Michael Goldwasser: Data Structures & Algorithms in Java,
Wiley, 2014, 720 p.
5.
Clifford A. Shaffer: A Practical Introduction to Data Structures and Algorithm Analysis, Prentice Hall,
2009, 601 p.
Number of active teaching hours
Lectures: 2
Practice: 2
Other forms of classes
Independent work: 1
Other classes
Lectures and exercises based on the model of interactive teaching (dwell methods: public lecture, discussion,
methods of practice, workshops, enactment); activated forms of learning: meaningful verbal receptive learning,
discovery learning, cooperative learning, learning by doing.
Examination methods ( maximum 100 points)
Exam prerequisites
Student’s activity during lectures
Practical classes/tests
Seminars/homework
Project
Other
Grade
10
9
8
7
6
5
No. of points:
10
30
-
Final exam
oral examination
written examination
..........
Grading system
No. of points
91-100
81-90
71-80
61-70
51-60
less than 50
No. of points:
30
30
Description
Excellent
Exceptionally good
Very good
Good
Passing
Failing