IB002 Algorithms and data structures I

Faculty of Informatics
Spring 2023
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)
prof. RNDr. Jiří Barnat, Ph.D. (seminar tutor)
RNDr. Nikola Beneš, Ph.D. (seminar tutor)
Mgr. Tomáš Foltýnek, Ph.D. (seminar tutor)
Vojtěch Kůr (seminar tutor)
Bc. Tomáš Macháček (seminar tutor)
doc. Mgr. Jan Obdržálek, PhD. (seminar tutor)
Bc. Matěj Pavlík (seminar tutor)
Mgr. Kristýna Pekárková (seminar tutor)
RNDr. Jaromír Plhák, Ph.D. (seminar tutor)
doc. RNDr. Vojtěch Řehák, Ph.D. (seminar tutor)
Bc. Jakub Šárník (seminar tutor)
Dávid Šutor (seminar tutor)
Bc. 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
Tue 14. 2. to Tue 9. 5. Tue 12:00–13:50 D3, Tue 12:00–13:50 D1
  • Timetable of Seminar Groups:
IB002/konzultace: Tue 14. 2. to Tue 9. 5. Tue 10:00–11:50 D3, M. Žáček, Není normální cvičení, ale konzultace. Nepřihlašuje se. Přijďte dle potřeby.
IB002/01: Mon 13. 2. to Mon 15. 5. Mon 10:00–11:50 A218, V. Řehák
IB002/02: Mon 13. 2. to Mon 15. 5. Mon 14:00–15:50 A319, V. Řehák
IB002/03: Tue 14. 2. to Tue 9. 5. Tue 8:00–9:50 A218, T. Foltýnek
IB002/04: Tue 14. 2. to Tue 9. 5. Tue 8:00–9:50 A320, V. Kůr
IB002/05: Tue 14. 2. to Tue 9. 5. Tue 18:00–19:50 A320, J. Šárník
IB002/06: Wed 15. 2. to Wed 10. 5. Wed 8:00–9:50 A217, J. Obdržálek
IB002/07: Wed 15. 2. to Wed 10. 5. Wed 10:00–11:50 A217, J. Obdržálek
IB002/08: Wed 15. 2. to Wed 10. 5. Wed 10:00–11:50 A318, except Wed 19. 4. ; and Wed 19. 4. 10:00–11:50 B517, T. Foltýnek
IB002/09: Wed 15. 2. to Wed 10. 5. Wed 12:00–13:50 A318, except Wed 19. 4. ; and Wed 19. 4. 12:00–13:50 B517, T. Foltýnek
IB002/10: Wed 15. 2. to Wed 10. 5. Wed 14:00–15:50 A217, V. Řehák
IB002/11: Wed 15. 2. to Wed 10. 5. Wed 14:00–15:50 A318, except Wed 19. 4. ; and Wed 19. 4. 14:00–15:50 B517, J. Plhák
IB002/12: Wed 15. 2. to Wed 10. 5. Wed 16:00–17:50 A318, except Wed 19. 4. ; and Wed 19. 4. 16:00–17:50 B517, J. Plhák
IB002/13: Thu 16. 2. to Thu 11. 5. Thu 8:00–9:50 A319, T. Macháček
IB002/14: Thu 16. 2. to Thu 11. 5. Thu 10:00–11:50 B411, N. Beneš
IB002/15: Thu 16. 2. to Thu 11. 5. Thu 10:00–11:50 A318, except Thu 20. 4. ; and Thu 20. 4. 10:00–11:50 B517, J. Barnat
IB002/16: Thu 16. 2. to Thu 11. 5. Thu 16:00–17:50 A318, K. Pekárková
IB002/17: Thu 16. 2. to Thu 11. 5. Thu 18:00–19:50 A320, M. Pavlík
IB002/18: Fri 17. 2. to Fri 12. 5. Fri 12:00–13:50 A217, D. Šutor
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.
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
    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
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
Teacher's information
https://is.muni.cz/auth/el/1433/jaro2021/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.
  • Enrolment Statistics (recent)
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