# FI:IV003 Algorithms II - Course Information

## IV003 Algorithms and Data Structures II

**Faculty of Informatics**

Spring 2021

**Extent and Intensity**- 2/2/0. 3 credit(s) (plus extra credits for completion). Type of Completion: zk (examination).

Taught online. **Teacher(s)**- prof. RNDr. Ivana Černá, CSc. (lecturer)

RNDr. Jan Mrázek (seminar tutor)

RNDr. Petr Novotný, Ph.D. (seminar tutor)

RNDr. Samuel Pastva, Ph.D. (seminar tutor)

RNDr. Jaroslav Bendík, Ph.D. (assistant)

RNDr. Nikola Beneš, Ph.D. (assistant)

Mgr. Jan Horáček (assistant)

Mgr. Tomáš Jelínek (assistant)

RNDr. David Klaška (assistant)

doc. RNDr. Barbora Kozlíková, Ph.D. (assistant)

doc. RNDr. Petr Matula, Ph.D. (assistant) **Guaranteed by**- prof. RNDr. Ivana Černá, CSc.

Department of Computer Science - Faculty of Informatics

Supplier department: Department of Computer Science - Faculty of Informatics **Timetable**- Tue 16:00–17:50 Virtuální místnost
- Timetable of Seminar Groups:

*S. Pastva*

IV003/02: Wed 12:00–13:50 Virtuální místnost,*J. Mrázek*

IV003/03: Wed 16:00–17:50 Virtuální místnost,*P. Novotný* **Prerequisites**- (
**IB002**Algorithms I || PROGRAM ( 1431:N - MA )) && !**IB108**Algorithms II

The course expands on courses IB002 Algorithms and Data Structures I. **Course Enrolment Limitations**- The course is also offered to the students of the fields other than those the course is directly associated with.

The capacity limit for the course is 99 student(s).

Current registration and enrolment status: enrolled:**32**/99, only registered:**0**/99, only registered with preference (fields directly associated with the programme):**0**/99 **fields of study / plans the course is directly associated with**- there are 55 fields of study the course is directly associated with, display
**Course objectives**- The course expands on the introductory course Algortihm Design I. It presents algorithmic concepts without their direct connection to any particular programming language. The aim is to introduce students into design and analysis of advanced algorithms. The course presents advanced techniques of algorithm analysis and a wide spectrum of strategies together with algorithms built up on these strategies. Students are introduced into new data structures which are displayed in a row with algorithms based on them.
**Learning outcomes**- After enrolling the course students are able to:

- actively use and modify advanced graph and string algorithms,

- actively used advanced techniques for designing algorithms (dynamic programming, greedy techniques) for designing algorithms, expain their specific properties and limits,

- actively used and modify advanced dynamic data structures and use them for designing effective algorithsm,

- analyze time complexity and prove correctness of algorithms. **Syllabus**- Advanced design and analysis techniques: dynamic programming, greedy strategies,backtracking. Amortized analysis.
- Advanced data structures: binomial and Fibonacci heaps, data structures for disjoint sets.
- Graph algorithms: Single-Source Shortest Paths (The Bellman-Ford algorithm). All-Pairs Shortest Paths (Shortest paths and matrix multiplication, The Floyd-Warshall algorithm, Johnson's algorithm for sparse graphs). Maximum Flow (The Ford-Fulkerson method, The Push-Relabel method). Maximum bipartite matching.
- String matching: the naive string-matching algorithm, Karp-Rabin algorithm, string matching with finite automata. The Knuth-Morris-Pratt algorithm.

**Literature**- KLEINBERG, Jon and Éva TARDOS.
*Algorithm design*. Boston: Pearson/Addison-Wesley, 2006. xxiii, 838. ISBN 0321372913. URL info

*required literature*- DASGUPTA, Sanjoy, Christos Ch. PAPADIMITRIOU and Umesh Virkumar VAZIRANI.
*Algorithms*. 1st ed. Boston: McGraw-Hill Companies, 2008. x, 320. ISBN 9780073523408. info - CORMEN, Thomas H., Charles Eric LEISERSON and Ronald L. RIVEST.
*Introduction to algorithms*. Cambridge: MIT Press, 1989. xvii, 1028. ISBN 0070131430. info

*recommended literature*- KLEINBERG, Jon and Éva TARDOS.
**Teaching methods**- Lectures and seminars. Students are required to solve given algorithmic problems.
**Assessment methods**- The course has a form of a lecture with a seminar. During the term students separately solve sets of algorithmic problems. The course is concluded by the written exam. A student can attend the final exam providing she/he has acquired given number of points from problem sets.
**Language of instruction**- English
**Follow-Up Courses****Further comments (probably available only in Czech)**- Study Materials

The course is taught annually.

General note: Předmět byl dříve vypisován pod kódem IB108. **Teacher's information**- https://is.muni.cz/auth/el/1433/jaro2021/IV003/index.qwarp

- Enrolment Statistics (Spring 2021, recent)
- Permalink: https://is.muni.cz/course/fi/spring2021/IV003