Course details

Algorithms (in English)

IALe Acad. year 2022/2023 Summer semester 5 credits

Current academic year

Overview of fundamental data structures and their exploitation. Principles of dynamic memory allocation. Specification of abstract data types (ADT). Specification and implementation of ADT's: lists, stack and its exploitation, queue, searching table. Algorithms upon the binary trees. Searching: sequential, in the ordered and in not ordered array, searching with the guard (sentinel), binary search, search tree, balanced trees (AVL). Searching in hash-tables. Sorting (ordering), principles, sorting without the moving of items, sorting with multiple keys. Most common methods of sorting: Select-sort, Bubble-sort, Heap-sort, Insert-sort a jeho varianty, Shell-sort, recursive and non-recursive notation of the Quick sort, Merge-sort, List-merge-sort, Radix-sort.

Guarantor

Honzík Jan M., prof. Ing., CSc. (DIFS)

Language of instruction

English

Completion

Credit+Examination (written)

Time span

  • 39 hrs lectures
  • 13 hrs projects

Assessment points

  • 51 pts final exam (written part)
  • 14 pts mid-term test (written part)
  • 35 pts projects

Department

Department of Information Systems (UIFS)

Lecturer

Burgetová Ivana, Ing., Ph.D. (DIFS)
Honzík Jan M., prof. Ing., CSc. (DIFS)
Hranický Radek, Ing., Ph.D. (DIFS)
Škarvada Libor, RNDr. (DIFS)

Instructor

Burgetová Ivana, Ing., Ph.D. (DIFS)

Subject specific learning outcomes and competences

  • Student will acquaint with the methods of proving of correctness of programs and with construction of proved programms and learn their significance. 
  • Student will learn the fundamentals of algorithm coplexity and their intention. 
  • He/she acquaints with basic abstract data types and to commands its implementation and exploitation. 
  • Student will learn the principles of dynamic memory allocation. 
  • He/she learns and commands recursive and non recursive notation of basic algorithms. 
  • Student overrules the implementation and analysis of most used algorithms for searching and sorting.


  • Student learns terminology in Czech ane English language
  • Student learns to participate on the small project as a member of small team
  • Student learns to present and defend the results of the small project

Learning objectives

To acquaint with the principles of methods of proving of correctness of programs and with basic concepts of construction of proved programms. To learn the fundamentals of algorithm coplexity. To learn the principles of dynamic memory allocation. To acquaint with basic abstract data types and to command its implementation and exploitation. To learn and command recursive and non recursive notation of basic algorithms. To overrule the implementation and analysis of most used algorithms for searching and sorting.

Recommended prerequisites

Prerequisite knowledge and skills

  • Basic knowledge of the programming in programming language C.
  • Knowledge of secondary school level mathematics.

Study literature

  • Cormen, T.H., Leiserson, Ch.E., Rivest, R.L.: Introduction to Algorithms, Cambridge: MIT Press, 2009
  • Knuth, D.: The Art of Computer programming, Vol.1,2,3. Addison Wesley, 1968
  • Wirth, N.: Alorithms+Data Structures=Programs, Prentice Hall, 1976
  • Horowitz, Sahni: Fundamentals of Data Structures in C, University Press, 2010
  • Aho A.V., Hoppcroft J.E., Ullman J.D.: Data Structures and Algorithms, Addison Wesley, 1983.
  • Kruse, R.L.: Data Structures and Program Design. Prentice- Hall,Inc. 1984
  • Baase, S.: Computer Algorithms - Introduction to Design and Analysis. Addison Wesley, 1998

Syllabus of lectures

  1. Overview of data structures, introduction to methods for evaluating the time complexity of algorithms.
  2. Abstract data type and its specification.
  3. Specification, implementation and exploitation of ADT list.
  4. Specification, implementation and exploitation of ADT stack, queue. Numeration of expressions with the use of stack.
  5. ADT search table.
  6. Binary tree, algorithms upon the binary tree.
  7. Searching, sequential, in the array, binary search.
  8. Binary search trees, AVL tree.
  9. Hashing-tables.
  10. Ordering (sorting), principles, without movement, multiple key.
  11. Most common methods of sorting of arrays.

Syllabus - others, projects and individual work of students

  • Two home assignments

Progress assessment

  • Two evaluated  home assignments - 25 points
  • Mid-term written examination - 14 point
  • Final written examination - 51 points
  • Elaboration of short tasks in lectures - 10 points

Exam prerequisites

  • to earn min. 15 points within the semester

  • Plagiarism and not allowed cooperation will cause that involved students are not classified and disciplinary action can be initiated.

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