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)
Mgr. Jan Horáček (seminar tutor)
Mgr. Jan Koniarik (seminar tutor)
Mgr. Karel Kubíček (seminar tutor)
RNDr. Henrich Lauko, Ph.D. (seminar tutor)
doc. RNDr. Tomáš Masopust, Ph.D., DSc. (seminar tutor)
doc. Mgr. Jan Obdržálek, PhD. (seminar tutor)
RNDr. 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, Ph.D. (seminar tutor)
Mgr. Viktória Vozárová (seminar tutor)
Mgr. Tatiana Zbončáková (seminar tutor)
Mgr. Adam Matoušek (assistant)
Bc. 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:
IB002/konzultace01: Mon 14:00–15:40 A420, 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
    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 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
Teacher's information
https://is.muni.cz/auth/el/1433/jaro2019/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 2019, Spring 2020, Spring 2021, Spring 2022, Spring 2023, Spring 2024, Spring 2025.
  • Enrolment Statistics (Spring 2018, recent)
  • Permalink: https://is.muni.cz/course/fi/spring2018/IB002