Course details

Algorithms

IAL Acad. year 2017/2018 Winter 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, set, array, searching table, graph, binary tree. 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. Ordering (sorting), principles, sorting without the moving of items, sorting with multiple keys. Most common methods of sorting:Select-sort, Bubble-sort, Heap-sort, Insert-sort and variants, Shell-sort, recursive and non-recursive notation of the Quick sort, Merge-sort,List-merge-sort, Radix-sort. Recursion and backtrack algorithms. Searching the patterns in the text. Proving of correctness of programs, construction of proved programs.

5 ECTS credits represent approximately 125-150 hours of study workload:

  • 39 hours of lectures
  • 26 hours for two home assignments
  • 35 hours of project work
  • 20 hours of continual study
  • 30 hours of study for midterm and final examination

 

Guarantor

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

Language of instruction

Czech, 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)

Subject specific learning outcomes and competences

  • Student will acquaint with the methods of proving of correctness of programs and with construction of proved programs and learn their significance. 
  • Student will learn the fundamentals of algorithm complexity 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 and will be use them on the model system. 
  • 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 and 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

Student will learn the principles of methods of proving of correctness of programs (Wirth) and with basic concepts of construction of proved programs (Dijkstra) and will be able to use gained knowledge in design of programmes.. Student will learn the fundamentals of algorithm complexity and will be able to use gained knowledge in design of programmes. Student  learns the principles of dynamic memory allocation and he will exercise them on the model system. Student  acquaints with basic abstract data types and to command its implementation and exploitation.  Student  learns and commands recursive and non recursive notation of basic algorithms and will be able to use gained knowledge in design of programmes.. Student overrules the implementation and analysis of most of used algorithms for searching and sorting.

Recommended prerequisites

Prerequisite knowledge and skills

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

Study literature

  • Honzík, J., Hruška, T., Máčel, M.: Vybrané kapitoly z programovacích technik, Ed.stř.VUT Brno,1991.

Fundamental literature

  • Knuth, D.: The Art of Computer programming, Vol.1,2,3. Addison Wesley, 1968
  • Wirth, N.: Alorithms+Data Structures=Programs, Prentice Hall, 1976
  • Horovitz, Sahni: Fundamentals of Data Structures.
  • Amsbury, W: Data Structures: From Arrays to Priority Queues.
  • Cormen, T.H., Leiserson, Ch.E., Rivest, R.L.: Introduction to Algorithms.
  • Aho A.V., Hoppcroft J.E., Ullman J.D.: Data Structures and Algorithms.
  • Kruse, R.L.: Data Structures and Program Design. Prentice- Hall,Inc. 1984
  • Baase, S.: Computer Algorithms - Introduction to Design and Analysis. Addison Wesley, 1998
  • Sedgewick,R.:Algoritmy v C. (Základy. Datové struktury. Třídění. Vyhledávání.) Addison Wesley 1998. Softpress 2003.

Syllabus of lectures

  1. Overview of data structures. Abstract data type and its specification.
  2. Specification, implementation and exploitation of ADT list.
  3. Specification, implementation and exploitation of ADT stack, queue. Numeration of expressions with the use of stack.
  4. ADT array, set, graph, binary tree.
  5. Algorithms upon the binary tree.
  6. Searching, sequential, in the array, binary search.
  7. Binary search trees, AVL tree.
  8. Hashing-tables.
  9. Ordering (sorting), principles, without movement, multiple key.
  10. Most common methods of sorting of arrays - beginning.
  11. Most common methods of sorting of arrays - continuation, sorting of files.
  12. Recursion, backtracking algorithms.
  13. Proving the programs, construction of proved programs.

Progress assessment

  • to earn min. 20 points within the semester

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

Controlled instruction

  • Evaluated home assignments - 20 points
  • Mid-term written examination - 14 point
  • Evaluated project with the defense - 15 points
  • Final written examination - 51 points; The minimal number of points which can be obtained from the final written examination is 20. Otherwise, no points will be assigned to a student.

Course inclusion in study plans

  • Programme IT-BC-3, field BIT, 2nd year of study, Compulsory
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