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  2. Analysis of algorithms - Wikipedia

    en.wikipedia.org/wiki/Analysis_of_algorithms

    In computer science, the analysis of algorithms is the process of finding the computational complexity of algorithms—the amount of time, storage, or other resources needed to execute them. Usually, this involves determining a function that relates the size of an algorithm's input to the number of steps it takes (its time complexity ) or the ...

  3. Empirical algorithmics - Wikipedia

    en.wikipedia.org/wiki/Empirical_algorithmics

    In computer science, empirical algorithmics (or experimental algorithmics) is the practice of using empirical methods to study the behavior of algorithms.The practice combines algorithm development and experimentation: algorithms are not just designed, but also implemented and tested in a variety of situations.

  4. Computational complexity - Wikipedia

    en.wikipedia.org/wiki/Computational_complexity

    The study of the complexity of explicitly given algorithms is called analysis of algorithms, while the study of the complexity of problems is called computational complexity theory. Both areas are highly related, as the complexity of an algorithm is always an upper bound on the complexity of the problem solved by this algorithm. Moreover, for ...

  5. Average-case complexity - Wikipedia

    en.wikipedia.org/wiki/Average-case_complexity

    Average-case analysis requires a notion of an "average" input to an algorithm, which leads to the problem of devising a probability distribution over inputs. Alternatively, a randomized algorithm can be used. The analysis of such algorithms leads to the related notion of an expected complexity. [2]: 28

  6. Computational complexity theory - Wikipedia

    en.wikipedia.org/wiki/Computational_complexity...

    Closely related fields in theoretical computer science are analysis of algorithms and computability theory. A key distinction between analysis of algorithms and computational complexity theory is that the former is devoted to analyzing the amount of resources needed by a particular algorithm to solve a problem, whereas the latter asks a more ...

  7. Profiling (computer programming) - Wikipedia

    en.wikipedia.org/wiki/Profiling_(computer...

    Profiling results can be used to guide the design and optimization of an individual algorithm; the Krauss matching wildcards algorithm is an example. [5] Profilers are built into some application performance management systems that aggregate profiling data to provide insight into transaction workloads in distributed applications.

  8. Weird AI illustrates why algorithms still need people - AOL

    www.aol.com/weird-ai-illustrates-why-algorithms...

    “If it seems like AI is everywhere, it’s partly because ‘artificial intelligence’ means lots of things, depending on whether you’re reading science fiction or selling a new app or doing ...

  9. Algorithm - Wikipedia

    en.wikipedia.org/wiki/Algorithm

    The analysis, and study of algorithms is a discipline of computer science. Algorithms are often studied abstractly, without referencing any specific programming language or implementation. Algorithm analysis resembles other mathematical disciplines as it focuses on the algorithm's properties, not implementation.