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| title | TARGET DECK | FILE TAGS | tags | ||
|---|---|---|---|---|---|
| Order of Growth | Obsidian::STEM | algorithm::complexity |
|
Overview
The running time of an algorithm is usually considered as a function of its input size. How input size is measured depends on the problem at hand. For instance, algorithms/sorting/index algorithms have an input size corresponding to the number of elements to sort.
%%ANKI Basic How is the running time of a program traditionally measured? Back: As a function of its input size. Reference: Thomas H. Cormen et al., Introduction to Algorithms, 3rd ed (Cambridge, Mass: MIT Press, 2009).
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%%ANKI Basic How do you determine the input size used to measure an algorithm's running time? Back: This depends entirely on the specific problem/algorithm. Reference: Thomas H. Cormen et al., Introduction to Algorithms, 3rd ed (Cambridge, Mass: MIT Press, 2009).
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%%ANKI Basic What concrete measure is typically used to measure running time? Back: The number of primitive operations executed. Reference: Thomas H. Cormen et al., Introduction to Algorithms, 3rd ed (Cambridge, Mass: MIT Press, 2009).
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%%ANKI Basic What abstract measure is typically used to measure running time? Back: It's order of growth. Reference: Thomas H. Cormen et al., Introduction to Algorithms, 3rd ed (Cambridge, Mass: MIT Press, 2009).
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%%ANKI Basic Why does Cormen et al. state the scope of average-case analysis is limited? Back: What constitutes an "average" input isn't always clear. Reference: Thomas H. Cormen et al., Introduction to Algorithms, 3rd ed (Cambridge, Mass: MIT Press, 2009).
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%%ANKI Basic What about running time are algorithm designers mostly interested in? Back: It's order of growth. Reference: Thomas H. Cormen et al., Introduction to Algorithms, 3rd ed (Cambridge, Mass: MIT Press, 2009).
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%%ANKI Basic How does order of growth relate to running time? Back: Order of growth measures how quickly running time grows with respect to input size. Reference: Thomas H. Cormen et al., Introduction to Algorithms, 3rd ed (Cambridge, Mass: MIT Press, 2009).
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%%ANKI Basic Why are lower-ordered terms ignored when determining order of growth? Back: They become less significant as input size grows. Reference: Thomas H. Cormen et al., Introduction to Algorithms, 3rd ed (Cambridge, Mass: MIT Press, 2009).
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%%ANKI Basic Why are leading coefficients ignored when determining order of growth? Back: They become less significant as input size grows. Reference: Thomas H. Cormen et al., Introduction to Algorithms, 3rd ed (Cambridge, Mass: MIT Press, 2009).
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%%ANKI Basic Polynomials describing order of growth usually have what two parts ignored? Back: Coefficients and lower-ordered terms. Reference: Thomas H. Cormen et al., Introduction to Algorithms, 3rd ed (Cambridge, Mass: MIT Press, 2009).
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References
- Thomas H. Cormen et al., Introduction to Algorithms, 3rd ed (Cambridge, Mass: MIT Press, 2009).