Summary of Study |
Summary of Branches |
All Subject Groups |
All Subjects |
List of Roles |
Explanatory Notes
Instructions
Web page:
https://cw.fel.cvut.cz/wiki/courses/BE5B33ALG
Anotation:
In the course, the algorithms development is constructed with minimum dependency to programming language; nevertheless the lectures and seminars are based on Python. Basic data types a data structures, basic algorithms, recursive functions, abstract data types, stack, queues, trees, searching, sorting, special application algorithms, Dynamic programming. Students are able to design and construct non-trivial algorithms and to evaluate their affectivity.
Study targets:
Semester project consists from empirical evaluation of searching and sorting algorithms, comparison of iterative and recursive algorithms and debugging of graphical output of selected algorithms of linear algebra and mathematical analysis. Three phases of supervision associated to constituted subtask of project with closing demonstration and defense
Course outlines:
1. | | Order of growth of functions, asymptotic complexity of an algorithm |
2. | | Recursion, recurrence, Master theorem |
3. | | Trees, binary trees, backracking |
4. | | Queue, graph, Depth-first and Breadth-first search in a tree and in a general graph |
5. | | Searching in arrays, binary search trees |
6. | | AVL trees and B-trees |
7. | | Sorting, Insert Sort, SelectionSort, Bubble Sort, QuickSort |
8. | | Sorting, Merge Sort, Halda, Heap Sort |
9. | | Sorting, Radix sort, Counting Sort, Bucket Sort |
10. | | Hashing, open and chained tables, double hashing |
11. | | Hashing, coalesced hashing, universal hashing |
12. | | Dynamic programming, optimal solution structure, memoization, optimal BST |
13. | | Dynamic programming, longest common subsequence, optimal matrich chain multiplication, knapsack problem |
14. | | Sorting multidimensional data, realistic sorting algorithms performance |
Exercises outline:
1. | | Introductory test, repeating of the ways of program construction in development environment, examples of functions and procedures, parameters, simple classes, assignment of semester task |
2. | | One-dimensional array processing |
3. | | Sorting and searching in 1D array algorithms |
4. | | Multidimensional array processing algorithms |
5. | | Text and string algorithms |
6. | | Experimentation with space and complexity of algorithms |
7. | | Sequential files |
8. | | Implementation of abstract data types |
9. | | Recursion and iteration |
10. | | Linked lists, linearly-linked list |
11. | | Tree construction, tree search |
12. | | Test, consultation to semester task |
13. | | Algorithms of linear algebra and geometry, mathematical analysis |
14. | | Credit |
Literature:
[1] | | T. H. Cormen, C. E. Leiserson, R. L. Rivest, C. Stein: Introduction to Algorithms, 3rd ed., MIT Press, 2009, |
[2] | | S. Dasgupta, C.H. Papadimitriou, and U.V. Vazirani: Algorithms, Mcgraw-Hill Higher Education, 2006, |
[3] | | Robert Sedgewick: Algoritms in v C, parts 1-4, Addison-Wesley Professional; 3rd edition (1997) |
Requirements:
Programming 1
Keywords:
Asymptotic complexity, recursive algorithms, binary trees, searching, hashing, sorting, dynamic programming.
Subject is included into these academic programs:
Page updated 2.12.2024 09:51:55, semester: Z/2024-5, L/2023-4, Z/2025-6, L/2024-5, Send comments about the content to the Administrators of the Academic Programs |
Proposal and Realization: I. Halaška (K336), J. Novák (K336) |