IV003 Algorithms and Data Structures II

Faculty of Informatics
Spring 2022
Extent and Intensity
2/2/0. 3 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. Jan Mrázek (seminar tutor)
doc. RNDr. Petr Novotný, Ph.D. (seminar tutor)
RNDr. Martin Jonáš, Ph.D. (assistant)
RNDr. David Klaška (assistant)
RNDr. Henrich Lauko, Ph.D. (assistant)
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 16. 2. to Wed 11. 5. Wed 12:00–13:50 D2
  • Timetable of Seminar Groups:
IV003/A: Thu 17. 2. to Thu 12. 5. Thu 16:00–17:50 B204, N. Beneš
IV003/02: Thu 17. 2. to Thu 12. 5. Thu 12:00–13:50 A218, P. Novotný
IV003/03: Thu 17. 2. to Thu 12. 5. Thu 14:00–15:50 A218, P. Novotný
IV003/04: Thu 17. 2. to Thu 12. 5. Thu 8:00–9:50 C525, J. Mrázek
IV003/2P: Wed 23. 2. to Wed 11. 5. Wed 8:00–9:50 C416, I. Černá, lecture in English
Prerequisites
( IB002 Algorithms I || PROGRAM(1431:N-MA)) && ! IB108 Algorithms II
The course expands on courses IB002 Algorithms and Data Structures I.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
The capacity limit for the course is 99 student(s).
Current registration and enrolment status: enrolled: 7/99, only registered: 0/99, only registered with preference (fields directly associated with the programme): 0/99
fields of study / plans the course is directly associated with
there are 55 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 data structures and 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.
Learning outcomes
After enrolling the course students are able to:
- actively use and modify advanced graph and string algorithms,
- actively used advanced techniques for designing algorithms (dynamic programming, greedy techniques) for designing algorithms, expain their specific properties and limits,
- actively used and modify advanced dynamic data structures and use them for designing effective algorithsm,
- analyze time complexity and prove correctness of algorithms.
Syllabus
  • Advanced analysis techniques: amortized analysis.
  • Advanced design techniques: dynamic programming, greedy strategies, backtracking.
  • Advanced data structures: binomial and Fibonacci heaps, data structures for disjoint sets.
  • Graph algorithms: shortest paths (Bellman-Ford-Moore algorithm, Dijkstra's algorithm, Floyd-Warshall algorithm, Johnson's algorithm for sparse graphs); spanning trees (algorithms Prim, Krusal, and Borůvka); maximum flow (Ford-Fulkerson algorithm, push-relabel method, applications).
  • String matching: the naive string-matching algorithm, Karp-Rabin algorithm, string matching with finite automata, Knuth-Morris-Pratt algorithm.
Literature
    required literature
  • KLEINBERG, Jon and Éva TARDOS. Algorithm design. Boston: Pearson/Addison-Wesley, 2006, xxiii, 838. ISBN 0321372913. URL info
    recommended literature
  • DASGUPTA, Sanjoy, Christos Ch. PAPADIMITRIOU and Umesh Virkumar VAZIRANI. Algorithms. 1st ed. Boston: McGraw-Hill Companies, 2008, x, 320. ISBN 9780073523408. info
  • CORMEN, Thomas H., Charles Eric 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 algorithmic 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. A student can attend the final exam providing she/he has acquired given number of points from problem sets.
Language of instruction
English
Follow-Up Courses
Further comments (probably available only in Czech)
Study Materials
The course is taught annually.
General note: Předmět byl dříve vypisován pod kódem IB108.
Teacher's information
https://is.muni.cz/auth/el/1433/jaro2021/IV003/index.qwarp
The course is also listed under the following terms Spring 2014, Spring 2015, Spring 2016, Spring 2017, Spring 2018, Spring 2019, Spring 2020, Spring 2021, Spring 2023, Spring 2024, Spring 2025.
  • Enrolment Statistics (Spring 2022, recent)
  • Permalink: https://is.muni.cz/course/fi/spring2022/IV003