IV003 Algorithms and Data Structures II

Faculty of Informatics
Spring 2024
Extent and Intensity
2/2/0. 3 credit(s) (plus extra credits for completion). Type of Completion: zk (examination).
Taught in person.
Teacher(s)
prof. RNDr. Ivana Černá, CSc. (lecturer)
RNDr. Nikola Beneš, Ph.D. (seminar tutor)
RNDr. Martin Jonáš, Ph.D. (seminar tutor)
Mgr. Martin Kurečka (seminar tutor)
RNDr. David Klaška (assistant)
doc. RNDr. Pavel Matula, Ph.D. (assistant)
Guaranteed by
prof. RNDr. Ivana Černá, CSc.
Department of Computer Science – Faculty of Informatics
Contact Person: doc. RNDr. Pavel Matula, Ph.D.
Supplier department: Department of Computer Science – Faculty of Informatics
Timetable
Tue 16:00–17:50 D2
  • Timetable of Seminar Groups:
IV003/A: Wed 12:00–13:50 A217, N. Beneš
IV003/02: Tue 18:00–19:50 A318, M. Kurečka
IV003/03: Thu 16:00–17:50 B410, M. Jonáš
IV003/04: Wed 14:00–15:50 A320, M. Jonáš
IV003/2EN_lecture: Wed 10:00–11:50 A217, I. Černá, Lecture in English
Prerequisites
IB002 Algorithms I || PROGRAM ( 1431:N - MA )
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: 62/99, 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 56 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.
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 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.
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/jaro2023/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 2022, Spring 2023, Spring 2025.

IV003 Algorithms and Data Structures II

Faculty of Informatics
Spring 2025
Extent and Intensity
2/2/0. 3 credit(s) (plus extra credits for completion). Type of Completion: zk (examination).
Taught in person.
Teacher(s)
prof. RNDr. Ivana Černá, CSc. (lecturer)
RNDr. Nikola Beneš, Ph.D. (seminar tutor)
RNDr. Martin Jonáš, Ph.D. (seminar tutor)
Mgr. Martin Kurečka (seminar tutor)
doc. RNDr. Petr Novotný, Ph.D. (seminar tutor)
RNDr. David Klaška (assistant)
Guaranteed by
prof. RNDr. Ivana Černá, CSc.
Department of Computer Science – Faculty of Informatics
Supplier department: Department of Computer Science – Faculty of Informatics
Prerequisites
IB002 Algorithms I || PROGRAM ( 1431:N - MA )
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: 0/99, 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 38 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.
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 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.
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)
The course is taught annually.
The course is taught: every week.
General note: Předmět byl dříve vypisován pod kódem IB108.
Teacher's information
https://is.muni.cz/auth/el/1433/jaro2023/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 2022, Spring 2023, Spring 2024.

IV003 Algorithms and Data Structures II

Faculty of Informatics
Spring 2023
Extent and Intensity
2/2/0. 3 credit(s) (plus extra credits for completion). Type of Completion: zk (examination).
Taught in person.
Teacher(s)
prof. RNDr. Ivana Černá, CSc. (lecturer)
RNDr. Nikola Beneš, Ph.D. (seminar tutor)
RNDr. Martin Jonáš, Ph.D. (seminar tutor)
doc. RNDr. Petr Novotný, Ph.D. (seminar tutor)
RNDr. David Klaška (assistant)
Mgr. Martin Kurečka (assistant)
Bc. Tomáš Macháček (assistant)
RNDr. Jan Mrázek (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 15. 2. to Wed 10. 5. Wed 10:00–11:50 D2
  • Timetable of Seminar Groups:
IV003/A: Thu 16. 2. to Thu 11. 5. Thu 16:00–17:50 A217, N. Beneš
IV003/02: Thu 16. 2. to Thu 11. 5. Thu 14:00–15:50 C525, P. Novotný
IV003/03: Wed 15. 2. to Wed 10. 5. Wed 16:00–17:50 B410, M. Jonáš
IV003/04: Fri 17. 2. to Fri 12. 5. Fri 8:00–9:50 A318, M. Jonáš
IV003/2P: Thu 16. 2. to Thu 11. 5. Thu 12:00–13:50 C525, I. Černá, English lecture
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: 61/99, 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 56 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.
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 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.
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/jaro2023/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 2022, Spring 2024, Spring 2025.

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).
Taught in person.
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: 39/99, 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.

IV003 Algorithms and Data Structures II

Faculty of Informatics
Spring 2021
Extent and Intensity
2/2/0. 3 credit(s) (plus extra credits for completion). Type of Completion: zk (examination).
Taught online.
Teacher(s)
prof. RNDr. Ivana Černá, CSc. (lecturer)
RNDr. Jan Mrázek (seminar tutor)
doc. RNDr. Petr Novotný, Ph.D. (seminar tutor)
RNDr. Samuel Pastva, Ph.D. (seminar tutor)
RNDr. Jaroslav Bendík, Ph.D. (assistant)
RNDr. Nikola Beneš, Ph.D. (assistant)
Mgr. Jan Horáček (assistant)
Mgr. Tomáš Jelínek (assistant)
RNDr. David Klaška (assistant)
doc. RNDr. Barbora Kozlíková, Ph.D. (assistant)
doc. RNDr. Petr Matula, 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
Tue 16:00–17:50 Virtuální místnost
  • Timetable of Seminar Groups:
IV003/01: Tue 18:00–19:50 Virtuální místnost, S. Pastva
IV003/02: Wed 12:00–13:50 Virtuální místnost, J. Mrázek
IV003/03: Wed 16:00–17:50 Virtuální místnost, P. Novotný
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: 4/99, 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 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 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.
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 2022, Spring 2023, Spring 2024, Spring 2025.

IV003 Algorithms and Data Structures II

Faculty of Informatics
Spring 2020
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. Jaroslav Bendík, Ph.D. (seminar tutor)
RNDr. Nikola Beneš, Ph.D. (seminar tutor)
RNDr. Tomáš Effenberger, Ph.D. (seminar tutor)
Mgr. Jan Horáček (seminar tutor)
RNDr. Jan Mrázek (seminar tutor)
RNDr. Samuel Pastva, Ph.D. (seminar tutor)
RNDr. David Klaška (assistant)
doc. RNDr. Pavel Matula, 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
Mon 17. 2. to Fri 15. 5. Wed 8:00–9:50 D2
  • Timetable of Seminar Groups:
IV003/01: Mon 17. 2. to Fri 15. 5. Thu 8:00–9:50 B410, T. Effenberger, J. Horáček
IV003/02: Mon 17. 2. to Fri 15. 5. Wed 14:00–15:50 A217, J. Mrázek
IV003/03: Mon 17. 2. to Fri 15. 5. Wed 12:00–13:50 B410, J. Bendík
IV003/04: Mon 17. 2. to Fri 15. 5. Thu 10:00–11:50 B204, S. Pastva
IV003/05: Mon 17. 2. to Fri 15. 5. Wed 18:00–19:50 A319, S. Pastva
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.
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 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 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.
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/jaro2020/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 2021, Spring 2022, Spring 2023, Spring 2024, Spring 2025.

IV003 Algorithms and data structures II

Faculty of Informatics
Spring 2019
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. Tomáš Effenberger, Ph.D. (seminar tutor)
Mgr. Jan Horáček (seminar tutor)
RNDr. Jan Mrázek (seminar tutor)
RNDr. Samuel Pastva, Ph.D. (seminar tutor)
RNDr. Martin Jonáš, Ph.D. (assistant)
RNDr. David Klaška (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
Wed 20. 2. to Wed 15. 5. Wed 12:00–13:50 D2
  • Timetable of Seminar Groups:
IV003/A: Thu 21. 2. to Thu 16. 5. Thu 12:00–13:50 B411, N. Beneš
IV003/01: Thu 21. 2. to Thu 16. 5. Thu 14:00–15:50 B410, T. Effenberger, J. Horáček
IV003/02: Thu 21. 2. to Thu 16. 5. Thu 16:00–17:50 A217, S. Pastva
IV003/03: Thu 21. 2. to Thu 16. 5. Thu 10:00–11:50 A318, S. Pastva
IV003/04: Wed 18:00–19:50 B410, J. Mrázek
Prerequisites
( IB002 Algorithms I || PROGRAM ( 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.
fields of study / plans 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.
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 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.
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 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
Czech
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/jaro2018/IV003/index.qwarp
The course is also listed under the following terms Spring 2014, Spring 2015, Spring 2016, Spring 2017, Spring 2018, Spring 2020, Spring 2021, Spring 2022, Spring 2023, Spring 2024, Spring 2025.

IV003 Algorithms and data structures II

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. Jaroslav Bendík, Ph.D. (seminar tutor)
RNDr. Nikola Beneš, Ph.D. (seminar tutor)
RNDr. Jan Mrázek (seminar tutor)
RNDr. Samuel Pastva, Ph.D. (seminar tutor)
Mgr. Filip Štefaňák (seminar tutor)
RNDr. František Blahoudek, Ph.D. (assistant)
Mgr. Jan Horáček (assistant)
RNDr. Martin Jonáš, Ph.D. (assistant)
RNDr. David Klaška (assistant)
Mgr. Tadeáš Kučera (assistant)
Mgr. Martina Vitovská (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
Mon 12:00–13:50 D2
  • Timetable of Seminar Groups:
IV003/Advanced: Thu 12:00–13:50 A319, N. Beneš
IV003/01: Thu 10:00–11:50 B410, J. Bendík
IV003/02: Tue 12:00–13:50 C511, J. Bendík
IV003/03: Thu 14:00–15:50 B410, S. Pastva
IV003/04: Tue 14:00–15:50 A217, J. Mrázek
IV003/05: Mon 18:00–19:50 A218, F. Štefaňák
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.
fields of study / plans 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.
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 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.
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 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
Czech
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/jaro2018/IV003/index.qwarp
The course is also listed under the following terms Spring 2014, Spring 2015, Spring 2016, Spring 2017, Spring 2019, Spring 2020, Spring 2021, Spring 2022, Spring 2023, Spring 2024, Spring 2025.

IV003 Algorithms and data structures II

Faculty of Informatics
Spring 2017
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. Jaroslav Bendík, Ph.D. (seminar tutor)
RNDr. Nikola Beneš, Ph.D. (seminar tutor)
RNDr. Samuel Pastva, Ph.D. (seminar tutor)
RNDr. František Blahoudek, Ph.D. (assistant)
RNDr. Martin Jonáš, Ph.D. (assistant)
RNDr. David Klaška (assistant)
Bc. Tomáš Lamser (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
Tue 16:00–17:50 D2
  • Timetable of Seminar Groups:
IV003/OS01: Wed 8:00–9:50 D2, N. Beneš
IV003/T01: Tue 7. 3. to Mon 22. 5. Tue 13:00–15:25 118, D. Klaška, Nepřihlašuje se. Určeno pro studenty se zdravotním postižením.
IV003/01: Wed 16:00–16:50 B411, N. Beneš
IV003/02: Wed 17:00–17:50 B411, N. Beneš
IV003/03: Wed 12:00–12:50 C416, J. Bendík
IV003/04: Wed 13:00–13:50 C416, J. Bendík
IV003/05: Thu 9:00–9:50 B411, S. Pastva
IV003/06: Thu 8:00–8:50 B411, S. Pastva
IV003/07: Thu 11:00–11:50 C511, J. Bendík
IV003/08: Thu 10:00–10:50 C511, J. Bendík
IV003/09: Thu 15:00–15:50 C511, S. Pastva
IV003/10: Thu 14:00–14:50 C511, S. Pastva
Prerequisites (in Czech)
( IB002 Algorithms I || PROGRAM ( 1431:N - MA )) && ! IB108 Algorithms II
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 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.
Syllabus
  • 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.
Literature
  • 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. URL 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 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
Czech
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/jaro2012/IB108/index.qwarp
The course is also listed under the following terms Spring 2014, Spring 2015, Spring 2016, Spring 2018, Spring 2019, Spring 2020, Spring 2021, Spring 2022, Spring 2023, Spring 2024, Spring 2025.

IV003 Algorithms and data structures II

Faculty of Informatics
Spring 2016
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. Jaroslav Bendík, Ph.D. (seminar tutor)
RNDr. Nikola Beneš, Ph.D. (seminar tutor)
Mgr. Bc. Tomáš Janík (seminar tutor)
RNDr. Jan Mrázek (seminar tutor)
Mgr. Filip Štefaňák (seminar tutor)
RNDr. Peter Bezděk, Ph.D. (assistant)
RNDr. Petra Budíková, Ph.D. (assistant)
RNDr. Martin Jonáš, Ph.D. (assistant)
RNDr. David Klaška (assistant)
RNDr. Henrich Lauko, 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
Mon 16:00–17:50 D2
  • Timetable of Seminar Groups:
IV003/OS01: Tue 12:00–13:50 D2, N. Beneš, Demonstrační cvičení
IV003/T01: Wed 24. 2. to Fri 20. 5. Wed 11:40–14:05 106, T. Janík, Nepřihlašuje se. Určeno pro studenty se zdravotním postižením.
IV003/T02: Tue 23. 2. to Fri 20. 5. Tue 10:20–11:55 106, Thu 25. 2. to Fri 20. 5. Thu 14:40–16:15 105, T. Janík, Nepřihlašuje se. Určeno pro studenty se zdravotním postižením.
IV003/01: Thu 14:00–14:50 B411, N. Beneš
IV003/02: Thu 15:00–15:50 B411, N. Beneš
IV003/03: Wed 12:00–12:50 C525, N. Beneš
IV003/04: Wed 13:00–13:50 C525, N. Beneš
IV003/05: Tue 14:00–14:50 C525, J. Mrázek
IV003/06: Tue 15:00–15:50 C525, J. Mrázek
IV003/07: Thu 12:00–12:50 B410, J. Bendík
IV003/08: Thu 13:00–13:50 B410, J. Bendík
IV003/09: Wed 10:00–10:50 C525, F. Štefaňák
IV003/10: Wed 11:00–11:50 C525, F. Štefaňák
Prerequisites (in Czech)
( IB002 Algorithms I || PROGRAM ( 1431:N - MA )) && ! IB108 Algorithms II
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 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.
Syllabus
  • 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.
Literature
  • 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. URL 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 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
Czech
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/jaro2016/IV003/index.qwarp
The course is also listed under the following terms Spring 2014, Spring 2015, Spring 2017, Spring 2018, Spring 2019, Spring 2020, Spring 2021, Spring 2022, Spring 2023, Spring 2024, Spring 2025.

IV003 Algorithms and data structures II

Faculty of Informatics
Spring 2015
Extent and Intensity
2/1. 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. Mária Svoreňová, Ph.D. (seminar tutor)
Mgr. Filip Štefaňák (seminar tutor)
Mgr. Petr Bauch, Ph.D. (assistant)
RNDr. Peter Bezděk, Ph.D. (assistant)
doc. RNDr. Jan Bouda, Ph.D. (assistant)
RNDr. Petra Budíková, Ph.D. (assistant)
Mgr. Jan Fikejs (assistant)
Mgr. Bc. Tomáš Janík (assistant)
RNDr. Martin Jonáš, Ph.D. (assistant)
RNDr. David Klaška (assistant)
Mgr. Karel Kubíček (assistant)
RNDr. Henrich Lauko, Ph.D. (assistant)
doc. Mgr. Jan Obdržálek, PhD. (assistant)
RNDr. Samuel Pastva, Ph.D. (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
Wed 14:00–15:50 D2
  • Timetable of Seminar Groups:
IV003/T01: Mon 16. 2. to Fri 15. 5. Mon 9:40–11:15 117, T. Janík, Nepřihlašuje se. Určeno pro studenty se zdravotním postižením.
IV003/T02: Wed 18. 2. to Fri 15. 5. Wed 14:00–15:35 105 and Tue 24. 2. to Fri 15. 5. each odd Tuesday 8:00–12:55 106, T. Janík, Nepřihlašuje se. Určeno pro studenty se zdravotním postižením.
IV003/01: each even Thursday 16:00–17:50 A318, N. Beneš
IV003/02: each odd Thursday 16:00–17:50 A318, N. Beneš
IV003/03: each even Thursday 12:00–13:50 A319, N. Beneš
IV003/04: each odd Thursday 12:00–13:50 A319, N. Beneš
IV003/05: each even Wednesday 18:00–19:50 C525, M. Svoreňová
IV003/06: each odd Wednesday 18:00–19:50 C525, M. Svoreňová
IV003/07: each even Thursday 10:00–11:50 C511, F. Štefaňák
IV003/08: each odd Thursday 10:00–11:50 C511, F. Štefaňák
Prerequisites (in Czech)
IB002 Algorithms I && ! IB108 Algorithms II
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 200 student(s).
Current registration and enrolment status: enrolled: 0/200, only registered: 0/200, only registered with preference (fields directly associated with the programme): 0/200
fields of study / plans 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.
Syllabus
  • 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.
Literature
  • 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. URL 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 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
Czech
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/jaro2012/IB108/index.qwarp
The course is also listed under the following terms Spring 2014, Spring 2016, Spring 2017, Spring 2018, Spring 2019, Spring 2020, Spring 2021, Spring 2022, Spring 2023, Spring 2024, Spring 2025.

IV003 Algorithms and data structures II

Faculty of Informatics
Spring 2014
Extent and Intensity
2/1. 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)
Mgr. Miroslav Klimoš (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. Bc. Tomáš Janík (assistant)
RNDr. David Klaška (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
Wed 10:00–11:50 D2
  • Timetable of Seminar Groups:
IV003/T01: Tue 18. 2. to Sat 31. 5. Tue 10:00–11:35 Učebna S10 (56), Thu 20. 2. to Sat 31. 5. Thu 12:00–13:35 Učebna S10 (56), T. Janík, Nepřihlašuje se. Určeno pro studenty se zdravotním postižením.
IV003/01: each even Thursday 8:00–9:50 B410, N. Beneš
IV003/02: each odd Thursday 8:00–9:50 B410, N. Beneš
IV003/03: each even Wednesday 14:00–15:50 G126, M. Klimoš
IV003/04: each odd Wednesday 14:00–15:50 G126, M. Klimoš
IV003/05: each even Wednesday 16:00–17:50 G126, M. Klimoš
IV003/06: each odd Wednesday 16:00–17:50 G126, M. Klimoš
IV003/07: each even Thursday 18:00–19:50 G126, N. Beneš
IV003/08: each odd Thursday 18:00–19:50 G126, N. Beneš
Prerequisites (in Czech)
IB002 Algorithms I && ! IB108 Algorithms II
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 200 student(s).
Current registration and enrolment status: enrolled: 0/200, only registered: 0/200, only registered with preference (fields directly associated with the programme): 0/200
fields of study / plans 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.
Syllabus
  • 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.
Literature
  • 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. URL 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 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
Czech
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/jaro2012/IB108/index.qwarp
The course is also listed under the following terms Spring 2015, Spring 2016, Spring 2017, Spring 2018, Spring 2019, Spring 2020, Spring 2021, Spring 2022, Spring 2023, Spring 2024, Spring 2025.
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