# FI:IB002 Algorithms I - Course Information

## IB002 Algorithms and data structures I

**Faculty of Informatics**

Spring 2024

**Extent and Intensity**- 2/2/1. 4 credit(s) (plus extra credits for completion). Type of Completion: zk (examination).

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

Mgr. Jakub Balabán (seminar tutor)

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

Kateřina Borošová (seminar tutor)

Vojtěch Brdečko (seminar tutor)

Mgr. Tomáš Foltýnek, Ph.D. (seminar tutor)

Vojtěch Kůr (seminar tutor)

Bc. Tomáš Macháček (seminar tutor)

RNDr. Vít Musil, Ph.D. (seminar tutor)

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

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

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

Tereza Siková (seminar tutor)

Bc. Jakub Šárník (seminar tutor)

Mgr. Matěj Žáček (seminar tutor) **Guaranteed by**- prof. RNDr. Ivana Černá, CSc.

Department of Computer Science – Faculty of Informatics

Supplier department: Department of Computer Science – Faculty of Informatics **Timetable**- Mon 19. 2. to Thu 9. 5. Thu 10:00–11:50 D3, Thu 10:00–11:50 D1, except Thu 25. 4. ; and Thu 25. 4. 10:00–11:50 D1
- Timetable of Seminar Groups:

*M. Žáček*, Pravidelná konzultace, není potřeba se přihlašovat. První bude 27. 2. 2024

IB002/N01: No timetable has been entered into IS.

IB002/N02: No timetable has been entered into IS.

IB002/N03: No timetable has been entered into IS.

IB002/N04: No timetable has been entered into IS.

IB002/N05: No timetable has been entered into IS.

IB002/N06: No timetable has been entered into IS.

IB002/N07: No timetable has been entered into IS.

IB002/N08: No timetable has been entered into IS.

IB002/N09: No timetable has been entered into IS.

IB002/N10: No timetable has been entered into IS.

IB002/N11: No timetable has been entered into IS.

IB002/N12: No timetable has been entered into IS.

IB002/N13: No timetable has been entered into IS.

IB002/N14: No timetable has been entered into IS.

IB002/N15: No timetable has been entered into IS.

IB002/N16: No timetable has been entered into IS.

IB002/N17: No timetable has been entered into IS.

IB002/N18: No timetable has been entered into IS.

IB002/N20: No timetable has been entered into IS.

IB002/N21: No timetable has been entered into IS.

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

IB002/02: Mon 8:00–9:50 A319,*J. Obdržálek*

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

IB002/04: Mon 14:00–15:50 A218,*J. Plhák*

IB002/05: Mon 16:00–17:50 B411,*V. Musil*

IB002/06: Mon 18:00–19:50 A319,*V. Kůr*

IB002/07: Tue 8:00–9:50 A218,*V. Řehák*

IB002/08: Tue 12:00–13:50 A319,*V. Řehák*

IB002/09: Wed 8:00–9:50 A318,*J. Obdržálek*

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

IB002/11: Wed 12:00–13:50 A319,*V. Musil*

IB002/12: Wed 16:00–17:50 B204,*T. Macháček*

IB002/13: Wed 18:00–19:50 A217,*T. Siková*

IB002/14: Thu 8:00–9:50 A218,*T. Foltýnek*

IB002/15: Thu 16:00–17:50 B411,*K. Borošová*

IB002/16: Mon 19. 2. to Thu 9. 5. Thu 16:00–17:50 A218; and Thu 16. 5. 16:00–17:50 C525,*V. Brdečko*

IB002/17: Fri 8:00–9:50 A218,*J. Šárník*

IB002/18: Fri 10:00–11:50 A218,*J. Balabán* **Prerequisites**-
**IB015**Non-Imperative Programming ||**IB111**Foundations of Programming

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. IB114 is a lightweight version of IB002. **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 58 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 basic 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 the correctness of simple iterative and recursive algorithms,

- implement algorithms in the selected programming language (Python). **Syllabus**- Basic analysis of algorithms: The 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 the time complexity of sorting.
- Graphs and their representation. Graph search. Depth-first traversal, topological sort, strongly connected components. Breadth-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. URL 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 by 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/jaro2021/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

(IB111 || IB113) && !IB002 && !NOW(IB002)**IV003**Algorithms and Data Structures II

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

IB002**MA015**Graph Algorithms

fi/IB002">IB002||(typ_studia(N)&&fakulta(fi))

**Teacher's information**- https://is.muni.cz/auth/el/1433/jaro2021/IB002/index.qwarp

- Enrolment Statistics (recent)

- Permalink: https://is.muni.cz/course/fi/spring2024/IB002