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  2. Comparison of programming languages (list comprehension)

    en.wikipedia.org/wiki/Comparison_of_programming...

    List comprehension is a syntactic construct available in some programming languages for creating a list based on existing lists. It follows the form of the mathematical set-builder notation (set comprehension) as distinct from the use of map and filter functions.

  3. Time complexity - Wikipedia

    en.wikipedia.org/wiki/Time_complexity

    For example, a procedure that adds up all elements of a list requires time proportional to the length of the list, if the adding time is constant, or, at least, bounded by a constant. Linear time is the best possible time complexity in situations where the algorithm has to sequentially read its entire input.

  4. List comprehension - Wikipedia

    en.wikipedia.org/wiki/List_comprehension

    Here, the list [0..] represents , x^2>3 represents the predicate, and 2*x represents the output expression.. List comprehensions give results in a defined order (unlike the members of sets); and list comprehensions may generate the members of a list in order, rather than produce the entirety of the list thus allowing, for example, the previous Haskell definition of the members of an infinite list.

  5. Strand sort - Wikipedia

    en.wikipedia.org/wiki/Strand_sort

    Strand sort is a recursive sorting algorithm that sorts items of a list into increasing order. It has O(n 2) worst-case time complexity, which occurs when the input list is reverse sorted. [1] It has a best-case time complexity of O(n), which occurs when the input is already sorted. [citation needed]

  6. Computational complexity - Wikipedia

    en.wikipedia.org/wiki/Computational_complexity

    Therefore, the time complexity, generally called bit complexity in this context, may be much larger than the arithmetic complexity. For example, the arithmetic complexity of the computation of the determinant of a n × n integer matrix is O ( n 3 ) {\displaystyle O(n^{3})} for the usual algorithms ( Gaussian elimination ).

  7. Element distinctness problem - Wikipedia

    en.wikipedia.org/wiki/Element_distinctness_problem

    In computational complexity theory, the element distinctness problem or element uniqueness problem is the problem of determining whether all the elements of a list are distinct. It is a well studied problem in many different models of computation.

  8. Skip list - Wikipedia

    en.wikipedia.org/wiki/Skip_list

    To index the skip list and find the i'th value, traverse the skip list while counting down the widths of each traversed link. Descend a level whenever the upcoming width would be too large. For example, to find the node in the fifth position (Node 5), traverse a link of width 1 at the top level.

  9. Algorithmic efficiency - Wikipedia

    en.wikipedia.org/wiki/Algorithmic_efficiency

    Timsort sorts the list in time linearithmic (proportional to a quantity times its logarithm) in the list's length ((⁡)), but has a space requirement linear in the length of the list (()). If large lists must be sorted at high speed for a given application, timsort is a better choice; however, if minimizing the memory footprint of the sorting ...