#
FI:IB002 Algorithms I - Course Information

## IB002 Algorithms and data structures I

**Faculty of Informatics**

Spring 2018

**Extent and Intensity**- 2/2. 4 credit(s) (plus extra credits for completion). Type of Completion: zk (examination).
**Teacher(s)**- prof. RNDr. Ivana Černá, CSc. (lecturer)

RNDr. Nikola Beneš, Ph.D. (seminar tutor)

RNDr. František Blahoudek, Ph.D. (seminar tutor)

doc. RNDr. Tomáš Brázdil, Ph.D. (seminar tutor)

Mgr. Radka Cieslarová (seminar tutor)

doc. RNDr. Vlastislav Dohnal, Ph.D. (seminar tutor)

Bc. Jan Horáček (seminar tutor)

Mgr. Jan Koniarik (seminar tutor)

Mgr. Karel Kubíček (seminar tutor)

RNDr. Henrich Lauko (seminar tutor)

RNDr. Tomáš Masopust, Ph.D., DSc. (seminar tutor)

doc. Mgr. Jan Obdržálek, PhD. (seminar tutor)

Mgr. Filip Opálený (seminar tutor)

RNDr. Jaromír Plhák, Ph.D. (seminar tutor)

Bc. Miriama Rajčanová (seminar tutor)

Bc. Oliver Roch (seminar tutor)

doc. RNDr. Vojtěch Řehák, Ph.D. (seminar tutor)

Mgr. Bc. Kateřina Sloupová (seminar tutor)

Mgr. Miloslav Staněk (seminar tutor)

RNDr. Bc. Dominik Velan (seminar tutor)

Mgr. Viktória Vozárová (seminar tutor)

Mgr. Tatiana Zbončáková (seminar tutor)

Bc. Adam Matoušek (assistant)

Mikoláš Stuchlík (assistant)

RNDr. Vladimír Štill, Ph.D. (assistant) **Guaranteed by**- prof. RNDr. Mojmír Křetínský, CSc.

Department of Computer Science - Faculty of Informatics

Supplier department: Department of Computer Science - Faculty of Informatics **Timetable**- Thu 14:00–15:50 D1, Thu 14:00–15:50 D3
- Timetable of Seminar Groups:

*J. Koniarik*, pondeli 14-16 v A420

IB002/konzultace02: Tue 10:00–11:40 A420,*T. Zbončáková*, utery 10-12 v A420

IB002/konzultace03: Tue 14:00–15:40 A420,*J. Horáček*, utery 14-16 v A420

IB002/01: Mon 8:00–9:50 A218,*V. Řehák*

IB002/02: Mon 10:00–11:50 A218,*V. Řehák*

IB002/03: Mon 12:00–13:50 A218,*J. Obdržálek*

IB002/04: Mon 12:00–13:50 A318,*M. Rajčanová, T. Zbončáková*

IB002/05: Mon 14:00–15:50 A319,*O. Roch*

IB002/06: Mon 14:00–15:50 B204,*J. Horáček*

IB002/07: Mon 16:00–17:50 B411,*J. Koniarik, M. Staněk*

IB002/08: Mon 18:00–19:50 B410,*R. Cieslarová, K. Sloupová*

IB002/09: Tue 8:00–9:50 B411,*V. Vozárová*

IB002/10: Tue 10:00–11:50 B411,*V. Dohnal*

IB002/11: Tue 14:00–15:50 B411,*J. Koniarik, M. Staněk*

IB002/12: Wed 10:00–11:50 A318,*J. Obdržálek*

IB002/13: Wed 10:00–11:50 B411,*H. Lauko*

IB002/14: Wed 12:00–13:50 A217,*V. Vozárová*

IB002/15: Wed 12:00–13:50 C511,*R. Cieslarová*

IB002/16: Wed 14:00–15:50 A218,*J. Obdržálek*

IB002/17: Wed 16:00–17:50 B204,*K. Sloupová*

IB002/18: Thu 16:00–17:50 A318,*N. Beneš*

IB002/19: Fri 8:00–9:50 B411,*T. Masopust*

IB002/20: Fri 8:00–9:50 B204,*D. Velan*

IB002/21: Fri 10:00–11:50 B204,*D. Velan*

IB002/22: Fri 10:00–11:50 B410,*T. Brázdil* **Prerequisites**-
**IB001**Intro to Prog. using C ||**IB111**Foundations of Programming ||**IB999**Programming Test

The students should comprehend the basic notions on the level of IB111 Introduction to Programming and IB000 Mathematical Foundations of Computer Science Students should be able to: understand and apply basic constructs of programming languages (e.g., conditions, loops, functions, basic data types) in Python, know principles of recursion, and several basic algorithms. Students should know the basic mathematical notions; understand the logical structure of mathematical statements and mathematical proofs, specially mathematical induction; know discrete mathematical structures such as finite sets, relations, functions, and graph including their applications in informatics. **Course Enrolment Limitations**- The course is also offered to the students of the fields other than those the course is directly associated with.
**fields of study / plans the course is directly associated with**- there are 21 fields of study the course is directly associated with, display
**Course objectives**- The course presents basic techniques of the analysis of algorithms, data structures, and operations. Students should correctly apply the basic data structures and algorithms as well as apply the algorithm design and analysis techniques when designing new algorithms. Students implement their algorithms in programming language Python.
**Learning outcomes**- After enrolling the course students are able to:

- actively use and modify basis sorting algorithms and graph algorithms,

- actively used basic techniques for designing algorithms (divide et impera, recursion) and design simple algorithms,

- actively used and modify basic static and dynamic data structures,

- employ time complexity and correctness of algorithms,

- analyze time complexity and prove correctness of simple iterative and recursive algorithms,

- implement algorithms in the selected programming language (Python). **Syllabus**- Basic analysis of algorithms: Correctness of algorithms, input and output conditions, partial correctness, convergence, verification.
- Length of computation, algorithm complexity, problem complexity. Asymptotical analysis of time and space complexity, growth of functions.
- Algorithm design techniques. Divide et impera and recursive algorithms.
- Fundamental data structures: lists, queues. Representation of sets, hash tables. Binary heaps. Binary search trees, balanced trees (B trees, Red-black trees).
- Sorting algorithms: quicksort, mergesort, heapsort, lower bound for time complexity of sorting.
- Graphs and their representation. Graph search. Depth-first traversal, topological sort, strongly connected components. Breath-first traversal, bipartite graphs. Shortest paths, algorithm Bellman - Ford, Dijkstra's algorithm.

**Literature**- CORMEN, Thomas H.
*Introduction to algorithms*. 3rd ed. Cambridge, Mass.: MIT Press, 2009. xix, 1292. ISBN 9780262533058. info

*required literature*- SKIENA, Steven S.
*The algorithm design manual*. New York: Springer, 1998. xvi, 486. ISBN 0387948600. info

*recommended literature*- CORMEN, Thomas H.
**Teaching methods**- The course is organized as a series of lectures accompanied with exercises.
**Assessment methods**- The evaluation consists of written final exam and written exams during the term. Details can be found in learning materials https://is.muni.cz/auth/el/1433/jaro2019/IB002/index.qwarp
**Language of instruction**- Czech
**Follow-Up Courses****Further Comments**- Study Materials

The course is taught annually. **Listed among pre-requisites of other courses****IB114**Introduction to Programming and Algorithms II

IB113 && !IB002 && !NOW(IB002)**IV003**Algorithms and Data Structures II

(IB002 || program(PřF:N-MA)) && !IB108**IV100**Parallel and distributed computations

IB002**PB006**Principles of Programming Languages and OOP

(IB111 || IB002) && PB071

**Teacher's information**- https://is.muni.cz/auth/el/1433/jaro2019/IB002/index.qwarp

- Enrolment Statistics (Spring 2018, recent)
- Permalink: https://is.muni.cz/course/fi/spring2018/IB002