Survey

* Your assessment is very important for improving the workof artificial intelligence, which forms the content of this project

Survey

Transcript

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