Faculty of Information Technology, BUT

Course details

Algorithms

IAL Acad. year 2004/2005 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 a jeho varianty, 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.

Guarantor

Language of instruction

Czech, English

Completion

Credit+Examination (written)

Time span

39 hrs lectures, 13 hrs projects

Assessment points

50 exam, 15 half-term test, 35 projects

Department

Lecturer

Instructor

Subject specific learning outcomes and competences

Subject specific knowledge and abilities:
  • Student acquaints with the methods of proving of correctness of programs and is capable to prove correctness of simple algorithms.
  • He/she learns the fundamentals of algorithm coplexity and is capable to derive the complexity of simple algorithms.
  • He/she acquaints with basic abstract data types and  commands its implementation and exploitation.
  • He/she learns the principles of dynamic memory allocation.
  • He/she learns and command recursive and non recursive notation of basic algorithms .
  • He/She overrules the implementation and analysis of most used algorithms for searching and sorting.
  • Student overrule basic English termilology in the subject.

     

Generic learning outcomes and competences

  • Student will learn how to solve simple problems by te means of the project team-work.
  • He/she learns to present and defend  the results at the public auditorium.

Learning objectives

Basic attribute of ECTS:

To acquaint with the methods of proving of correctness of programs. To learn the fundamentals of algorithm coplexity. To acquaint with basic abstract data types namely: lists, stack, queue, array, graph, binary tree, search table. To command their implementation and exploitation. To learn the principles of dynamic memory allocation. 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.

Study 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

Fundamental literature

  • Knuth, D.: The Art of Computer programming, Vol.1,2,3. Addison Wesley, 2001
  • Wirth, N.: Alorithms+Data Structures=Programs, Prentice Hall, 1997
  • Horovitz, Sahni: Fundamentals of Data Structures. Prentice- Hall,Inc.2001,
  • Amsbury, W: Data Structures: From Arrays to Priority, Prentice Hall, 2001
  • Cormen, T. H. ,Leiserson, Ch.E., Rivest,R.L.: Introduction to Algorithms. 1998
  • Aho A.V., Hoppcroft J.E., Ullman J.D.: Data Structures and Algorithms. 1999.
  • Kruse, R.L.Data Structures and Program Design. Prentice- Hall,Inc. 1994
  • Baase, S.: Computer Algorithms - Introduction to Design and Analysis. Addison Wesley, 1998

Syllabus of lectures

  • Overview of data structures. Abstract data type and its specification.
  • Specification, implementation and exploitation of ADT list.
  • Specification, implementation and exploitation of ADT stack, queue. Numeration of expressions with the use of stack.
  • ADT array, set, graph, binary tree.
  • Algorithms upon the binary tree.
  • Searching, sequential, in the array, binary search.
  • Binary search trees, AVL tree.
  • Hashing-tables.
  • Ordering (sorting), principles, without movement, multiple key.
  • Most common methods of sorting of arrays, sorting of files.
  • Recursion, backtracking algorithms.
  • Proving the programs, costruction of proved programmes.

Syllabus - others, projects and individual work of students

  • Home assignments for individual students.
  • Project with a mini-defence for team of max. 5 students.

Progress assessment

  • Evaluated home assignments - 20 points
  • Mid-term written examination - 15 point
  • Evaluated project with the defense - 15 points
  • Final written examination - 50 points
  • To be alowed to sit for written examination student is to earn at least 15 points during the semester.
  • Passing bounary for ECTS assessment - 50 points
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