Examples of using Analysis of algorithms in English and their translations into Greek
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Section 5: Analysis of Algorithms.
Analysis of algorithms: time complexity.
Design and Analysis of Algorithms.
Analysis of algorithms(proof of correctness and complexity).
Robert Tarjan For fundamental achievements in the design and analysis of algorithms and data structures.
Design and analysis of algorithms and data structures.
With Robert E Tarjan,for fundamental achievements in the design and analysis of algorithms and data structures.
Design and analysis of algorithms, combinatorial optimization.
Mechanisms of behavior and activities, a detailed analysis of algorithms of viruses.
Complexity analysis of algorithms on the Parallel Random Access Machine(PRAM).
As in programming languages,such restrictions may simplify the description and analysis of algorithms, and improve their readability.
Analysis of algorithms is a branch of computer science that studies the performance of algorithms(computer programs solving a certain problem).
A constant factor,is usually disregarded in the analysis of algorithms under the standard uniform cost model.
Combinatorics is typically utilized in computer technology to obtain solutions and estimate the analysis of algorithms.
For example, logarithms appear in the analysis of algorithms that solve a problem by dividing it into two similar smaller problems and patching their solutions.
Students take a combination of core courses focused on design and analysis of algorithms; computer architectures;?
It covers the design and analysis of algorithms, computer architecture, operating systems, structure of programming languages, and advanced techniques in programming.
Combinatorics is used frequently in computer science to obtain formulas and estimates in the analysis of algorithms.
They will be able to use these methods in subsequent courses in the design and analysis of algorithms, computability theory, software engineering, and computer systems.
Combinatorics is employed frequently in computer science to have formulas and estimates in the analysis of algorithms.
In the field of runtime analysis of algorithms, it is common to specify a computational model in terms of primitive operations allowed which have unit cost, or simply unit-cost operations.
It includes disciplines that relate to the processing of information by computer systems, the analysis of algorithms and the development of programming languages.
Required areas of study include data structures, analysis of algorithms, low-level programming, computer architecture and language translation, ethics and law for the computing professional, and software design and development.
His research interests included mathematical programming, linear programming and network flows,design and analysis of algorithms, and data structures.
However, with the growth of applications to analysis of algorithms in computer science, as well as classical probability, additive and probabilistic number theory, the area recently grew to become an independent field of combinatorics.
The following three sets areselected exercises(and their solutions) on generating functions from the third chapter of the book"An introduction to the analysis of algorithms" by Philippe Flajolet and Robert Sedgewick.
Donald Knuth(PhD 1963), the"father" of the analysis of algorithms, wrote The Art of Computer Programming and created the TeX computer typesetting system, which is commonly used in the scientific community.
These foundations are extended by specialized courses giving graduates a good overview of areas of computer science such as complexity and computability,design and analysis of algorithms, and artificial intelligence.
He is the author of the multi-volume work The Art of Computer Programming.[8]Knuth has been called the"father of the analysis of algorithms".[9] He contributed to the development of the rigorous analysis of the computational complexity of algorithms and systematized formal mathematical techniques for it.
Our computer science curriculum is designed to educate students in the basic areas of computer science including general problem-solving techniques, architecture, concepts of programming languages, operating systems andtheoretical concepts dealing with computational models and the design and analysis of algorithms…[-].