IB002 Algorithms and Data Structures I

Faculty of Informatics
Spring 2026
Extent and Intensity
2/2/1. 4 credit(s) (plus extra credits for completion). Recommended Type of Completion: zk (examination). Other types of completion: k (colloquium).
In-person direct teaching
Teacher(s)
prof. RNDr. Ivana Černá, CSc. (lecturer)
doc. RNDr. Vojtěch Řehák, Ph.D. (seminar tutor)
doc. Mgr. Jan Obdržálek, PhD. (seminar tutor)
RNDr. Jakub Gajarský, Ph.D. (seminar tutor)
RNDr. Jaromír Plhák, Ph.D. (seminar tutor)
prof. RNDr. Jiří Barnat, Ph.D. (seminar tutor)
RNDr. Nikola Beneš, Ph.D. (seminar tutor)
Bc. Kateřina Borošová (seminar tutor)
Bc. Stanislav Valluš (seminar tutor)
Michal Rábek (seminar tutor)
Jana Jarošová (seminar tutor)
Bc. Vojtěch Brdečko (seminar tutor)
Bc. Jindřich Halabala (seminar tutor)
Ondřej Pupík (seminar tutor)
Bc. Tomáš Dang (seminar tutor)
Anna Tomalová (seminar tutor)
Tomáš Hutňan (seminar tutor)
Ondřej Vala (seminar tutor)
Bc. Martin Michal Dyttert (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
Wed 18. 2. to Wed 13. 5. Wed 10:00–11:50 A217
  • Timetable of Seminar Groups:
IB002/K01: Tue 17. 2. to Tue 12. 5. Tue 16:00–17:50 C123, V. Brdečko
IB002/01: Mon 16. 2. to Mon 11. 5. Mon 8:00–9:50 A321, V. Řehák
IB002/02: Mon 16. 2. to Mon 11. 5. Mon 8:00–9:50 A220, S. Valluš
IB002/03: Mon 16. 2. to Mon 11. 5. Mon 10:00–11:50 A321, J. Plhák
IB002/04: Mon 16. 2. to Mon 11. 5. Mon 10:00–11:50 A319, N. Beneš
IB002/05: Mon 16. 2. to Mon 11. 5. Mon 12:00–13:50 A321, J. Plhák
IB002/06: Mon 16. 2. to Mon 11. 5. Mon 12:00–13:50 A220, O. Pupík
IB002/07: Mon 16. 2. to Mon 11. 5. Mon 14:00–15:50 A321, O. Vala
IB002/08: Tue 17. 2. to Tue 12. 5. Tue 8:00–9:50 A220, V. Řehák
IB002/09: Tue 17. 2. to Tue 12. 5. Tue 14:00–15:50 A321, M. Dyttert
IB002/10: Tue 17. 2. to Tue 12. 5. Tue 16:00–17:50 A220, J. Gajarský
IB002/11: Tue 17. 2. to Tue 12. 5. Tue 18:00–19:50 A321, T. Hutňan
IB002/12: Wed 18. 2. to Wed 13. 5. Wed 8:00–9:50 A220, V. Řehák
IB002/13: Wed 18. 2. to Wed 13. 5. Wed 8:00–9:50 A319, J. Obdržálek
IB002/14: Wed 18. 2. to Wed 13. 5. Wed 12:00–13:50 A218, M. Rábek
IB002/15: Wed 18. 2. to Wed 13. 5. Wed 12:00–13:50 A220, J. Jarošová
IB002/16: Wed 18. 2. to Wed 13. 5. Wed 14:00–15:50 A321, V. Brdečko
IB002/17: Thu 19. 2. to Thu 14. 5. Thu 8:00–9:50 A321, J. Obdržálek
IB002/18: Thu 19. 2. to Thu 14. 5. Thu 8:00–9:50 A220, T. Dang
IB002/19: Thu 19. 2. to Thu 14. 5. Thu 10:00–11:50 A321, J. Obdržálek
IB002/20: Thu 19. 2. to Thu 14. 5. Thu 10:00–11:50 A220, J. Barnat
IB002/21: Thu 19. 2. to Thu 14. 5. Thu 14:00–15:50 A220, J. Gajarský
IB002/22: Thu 19. 2. to Thu 14. 5. Thu 18:00–19:50 A220, A. Tomalová
IB002/23: Fri 20. 2. to Fri 15. 5. Fri 12:00–13:50 A321, J. Gajarský
IB002/24: Fri 20. 2. to Fri 15. 5. Fri 12:00–13:50 A220, K. Borošová
IB002/25: Fri 20. 2. to Fri 15. 5. Fri 14:00–15:50 A220, J. Halabala
Prerequisites
( IB015 Non-Imperative Programming || IB111 Foundations of Programming ) && !NOW( IB114 Intro to Programming & Algs II )
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 similar course designed for a different curriculum.
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 37 fields of study the course is directly associated with, display
Abstract
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).
Key topics
  • 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.
Study resources and literature
    required literature
  • CORMEN, Thomas H. Introduction to algorithms. 3rd ed. Cambridge, Mass.: MIT Press, 2009, xix, 1292. ISBN 9780262533058. URL info
    recommended literature
  • SKIENA, Steven S. The algorithm design manual. New York: Springer, 1998, xvi, 486. ISBN 0387948600. info
Approaches, practices, and methods used in teaching
The course is organized as a series of lectures accompanied by exercises.
Method of verifying learning outcomes and course completion requirements
The evaluation consists of written final exam and written exams during the term. Details can be found in Interactive Syllabus in IS.
Language of instruction
Czech
Follow-Up Courses
Further Comments
Study Materials
The course is taught annually.
Listed among pre-requisites of other courses
Teacher's information
https://is.muni.cz/auth/el/1433/jaro2026/IB002/index.qwarp
The course is also listed under the following terms Spring 2003, Spring 2004, Spring 2005, Spring 2006, Spring 2007, Spring 2008, Spring 2009, Spring 2010, Spring 2011, Spring 2012, Spring 2013, Spring 2014, Spring 2015, Spring 2016, Spring 2017, Spring 2018, Spring 2019, Spring 2020, Spring 2021, Spring 2022, Spring 2023, Spring 2024, Spring 2025.
  • Enrolment Statistics (recent)
  • Permalink: https://is.muni.cz/course/fi/spring2026/IB002