IB108 Algorithms and data structures II

Faculty of Informatics
Spring 2013
Extent and Intensity
2/1. 3 credit(s) (plus extra credits for completion). Type of Completion: zk (examination).
prof. RNDr. Ivana Černá, CSc. (lecturer)
RNDr. Nikola Beneš, Ph.D. (seminar tutor)
RNDr. Mária Svoreňová, Ph.D. (seminar tutor)
Mgr. Petr Bauch, Ph.D. (assistant)
RNDr. Peter Bezděk, Ph.D. (assistant)
RNDr. Petra Budíková, Ph.D. (assistant)
Mgr. Vojtěch Havel (assistant)
Mgr. Jan Havlíček (assistant)
Mgr. David Klaška (assistant)
Mgr. Miroslav Klimoš (assistant)
RNDr. Petr Novotný, Ph.D. (assistant)
prof. RNDr. Mojmír Křetínský, CSc.
Department of Computer Science - Faculty of Informatics
Supplier department: Department of Computer Science - Faculty of Informatics
Mon 14:00–15:50 D2
  • Timetable of Seminar Groups:
IB108/01: each even Thursday 16:00–17:50 C511, N. Beneš
IB108/02: each odd Thursday 16:00–17:50 C511, N. Beneš
IB108/03: each even Friday 8:00–9:50 C511, M. Svoreňová
IB108/04: each odd Friday 8:00–9:50 C511, M. Svoreňová
Prerequisites (in Czech)
IB002 Algorithms I
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 the course is directly associated with
there are 18 fields of study the course is directly associated with, display
Course objectives
The course expands on the introductory course Algortihm Design I. It presents algorithmic concepts without their direct connection to any particular programming language. The aim is to introduce students into design and analysis of advanced algorithms. The course presents advanced techniques of algorithm analysis and a wide spectrum of strategies together with algorithms built up on these strategies. Students are introduced into new data structures which are displayed in a row with algorithms based on them.
  • Advanced design and analysis techniques: dynamic programming, greedy strategies,backtracking. Amortized analysis.
  • Advanced data structures: binomial and Fibonacci heaps, data structures for disjoint sets.
  • Graph algorithms: Single-Source Shortest Paths (The Bellman-Ford algorithm). All-Pairs Shortest Paths (Shortest paths and matrix multiplication, The Floyd-Warshall algorithm, Johnson's algorithm for sparse graphs). Maximum Flow (The Ford-Fulkerson method, The Push-Relabel method). Maximum bipartite matching.
  • String matching: the naive string-matching algorithm, Karp-Rabin algorithm, string matching with finite automata. The Knuth-Morris-Pratt algorithm.
  • DASGUPTA, Sanjoy, Christos Ch. PAPADIMITRIOU and Umesh Virkumar VAZIRANI. Algorithms. 1st ed. Boston: McGraw-Hill Companies, 2008. x, 320. ISBN 9780073523408. info
  • KLEINBERG, Jon and Éva TARDOS. Algorithm design. Boston: Pearson/Addison-Wesley, 2006. xxiii, 838. ISBN 0321372913. info
  • CORMEN, Thomas H., Charles E. LEISERSON and Ronald L. RIVEST. Introduction to algorithms. Cambridge: MIT Press, 1989. xvii, 1028. ISBN 0070131430. info
Teaching methods
Lectures and seminars. Students are required to solve given algorithmical problems.
Assessment methods
The course has a form of a lecture with a seminar. During the term students separately solve sets of algorithmic problems. The course is concluded by the written exam. Student can attend the final exam providing she/he has acquired given number of points from problem sets.
Language of instruction
Follow-Up Courses
Further Comments
Study Materials
The course is taught annually.
Listed among pre-requisites of other courses
Teacher's information
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.
  • Enrolment Statistics (recent)
  • Permalink: https://is.muni.cz/course/fi/spring2013/IB108

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