Type of course: | Compulsory |
Language of instruction: | English |
Erasmus Language of instruction: | English |
Name of lecturer: | Ovidiu Domsa |
Seminar tutor: | Adriana Bîrluțiu |
Form of education | Full-time |
Form of instruction: | Class |
Number of teaching hours per semester: | 56 |
Number of teaching hours per week: | 4 |
Semester: | Autumn |
Form of receiving a credit for a course: | Grade |
Number of ECTS credits allocated | 5 |
• General principles for algorithm development. • Complexity of algorithms. Asymptotic analysis of worst case scenario. • Numerical algorithms. Optimization of numerical algorithms. Primality. Bell numbers. Stirling numbers. Catalan numbers. Numbers with special properties. • Sorting: HeapSort, QuickSort, RadixSort, Median-Algorithms, Lower Bounds. • Analysis of sorting and searching algorithms complexity. • Parallel sorting: enumeration sort, odd-even transposition sort. • Parallel sorting: bitonic sort, quicksort on a hypercube. • Binary search trees. • AVL trees. Red-black trees. B-trees. • Hash tables. Collision resolution. Hash functions. • Graph algorithms: Transitive Closure, Shortest Path Problems, Minimum Spanning Trees. • Branch&Bound algorithms. Exemples of problems solved with the Branch&Bound method. • NP-complete algorithms. • Analysis, evaluation, and feed-back.
• acquisition of basic and specific knowledge about the concept of fundamental algorithms; • the ability to identify the applicability of the studied algorithms in real problems; • understanding the need of using advanced methods to create efficient algorithms when addressing problems from an specific domain; • Acquiring advanced knowledge of algorithms complexity and apply efficient methods to solve different practical problems.