Data Structures and Algorithms

The course is a substitute for:

Data Structures and Algorithms (X36DSA)

Lecturer:

Tutor:

Supervisor:

Department of Computer Science and Engineering

Synopsis:

Complexity of algorithms. Sorting - taxonomy of methods, Shellsort, Heapsort, Quicksort, Radixsort, searching, hashing, binary search, binary trees, multidimensional trees, geometrical searching. Data type specification and implementation (vector, linked list,, array, table, list, relation, graph). Logical and physical structure of files, sorting sequential files. Recursion and recursive programming. Dynamic programming. Program design methodologies.

Requirements:

Students must undergo the initial test which checks their programming abilities.

Those who fail to pass the test will not be permitted to enroll the subject.

The expected programming skills are:

Understanding short code which uses recursive funcion calls.

Manipulating linked list data structures with help of references (Java) or pointers (C/C++).

http://service.felk.cvut.cz/courses/X36DSA/index_en.html

Syllabus of lectures:

1. Space and time complexity of algorithms

2. Classification of sorting methods. Sorting algorithms with complexity O(n2)

3. Sorting algorithms with complexity O(n.logn)

4. Searching problem. Address searching methods

5. Associative searching methods

6. Multidimensional searching, Multidimensional searching trees

7. Geometrical searching, geometrical algorithms

8. Specification and implementation of data types

9. Implementation of the string, stack, queue, array, table, list, and graph data types

10. File data type, logical and physical structure of files, file sorting

11. Recursive programming, implementation of recursive algorithms

12. Back tracking searching algorithms

13. Dynamic programming

14. Program design paradigms

Syllabus of tutorials:

1. Calculation of minimal, maximal and average complexity of algorithms

2. Select-Sort and Buble-Sort, their space and time complexities

3. Insert-Sort implemented in array and linked structures

4. Quick-Sort, Heap-Sort, Merge-Sort, and Radix-Sort

5. Address search methods, hashing

6. Binary search, binary search trees

7. K-dimensional search trees, interval and segment trees, proximity problem

8. Construction of convex hull of a set of points in 2D

9. Specification of data types

10. Implementation of data types

11. Updating and sorting sequential files

12. Backtracking algorithms

13. Complexity of recursive algorithms

14. Assessment

Study Objective:

Study materials:

1. Cormen,T.H., et al.: Introduction to ALGORITHMS, New York, McGraw-Hill 1990.

2. Manoocher, A.:Abstract Data Types and Algorithms, London, Macmillan Education Ltd.

Note:

Further information:

No time-table has been prepared for this course

The course is a part of the following study plans:

• Computer Technology- structured studies (compulsory course)