Title:

Algorithms

Code:IAL
Ac.Year:2005/2006
Term:Winter
Curriculums:
ProgrammeBranchYearDuty
IT-BC-3BIT2ndCompulsory
Language:Czech, English
Credits:5
Completion:accreditation+exam (written)
Type of
instruction:
Hour/semLecturesSem. ExercisesLab. exercisesComp. exercisesOther
Hours:3900013
 ExaminationTestsExercisesLaboratoriesOther
Points:50150035
Guarantee:Honzík Jan M., prof. Ing., CSc., DIFS
Lecturer:Honzík Jan M., prof. Ing., CSc., DIFS
Instructor:Křena Bohuslav, Ing., Ph.D., DITS
Lukáš Roman, Ing., Ph.D., DIFS
Faculty:Faculty of Information Technology BUT
Department:Department of Information Systems FIT BUT
Prerequisites: 
Introduction to Programming Systems (IZP), DIFS
Follow-ups:
Java Programming Language (IJA), DITS
Principles of Programming Languages (IPP), DIFS
The C++ Programming Language (ICP), DITS
VHDL Seminar (IVH), DCSY
Substitute for:
Algorithms and Data Structures (ADS), DIFS
 
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.
Description:
  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.
Knowledge and skills required for the course:
  
  • Basic knowledge of the programming in procedural programming language
  • Knowledge of secondary school level matematics
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.
Generic learning outcomes and competences:
  
  • 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
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:
 
  • Two home assignments
  • Project with a mini-defence for a team of students.
Fundamental literature:
 
  • Honzík, J., Hruška, T., Máčel, M.: Vybrané kapitoly z programovacích technik, Ed.stř.VUT Brno,1991.
  • 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 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
Study literature:
 
  • Honzík, J., Hruška, T., Máčel, M.: Vybrané kapitoly z programovacích technik, Ed.stř.VUT Brno,1991.
  • 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
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
Exam prerequisites:
  
  •  to earn min. 20 points within the semester