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Else, recursively merge the first ⌊k/2⌋ lists and the final ⌈k/2⌉ lists, then binary merge these. When the input lists to this algorithm are ordered by length, shortest first, it requires fewer than n ⌈log k ⌉ comparisons, i.e., less than half the number used by the heap-based algorithm; in practice, it may be about as fast or slow ...
If the running time (number of comparisons) of merge sort for a list of length n is T(n), then the recurrence relation T(n) = 2T(n/2) + n follows from the definition of the algorithm (apply the algorithm to two lists of half the size of the original list, and add the n steps taken to merge the resulting two lists). [5]
It then merges each of the resulting lists of two into lists of four, then merges those lists of four, and so on; until at last two lists are merged into the final sorted list. [24] Of the algorithms described here, this is the first that scales well to very large lists, because its worst-case running time is O( n log n ).
Example: two runs [1, 2, 3, 6, 10] and [4, 5, 7, 9, 12, 14, 17] must be merged. Note that both runs are already sorted individually. The smallest element of the second run is 4 and it would have to be added at the fourth position of the first run in order to preserve its order (assuming that the first position of a run is 1).
The classic merge outputs the data item with the lowest key at each step; given some sorted lists, it produces a sorted list containing all the elements in any of the input lists, and it does so in time proportional to the sum of the lengths of the input lists. Denote by A[1..p] and B[1..q] two arrays sorted in increasing order.
The input to the + sorting problem consists of two finite collections of numbers and , of the same length. The problem's output is the collection of all pairs of a number from and a number from , arranged into sorted order by the sum of each pair. [1]
In mathematics, an ordered pair, denoted (a, b), is a pair of objects in which their order is significant. The ordered pair (a, b) is different from the ordered pair (b, a), unless a = b. In contrast, the unordered pair, denoted {a, b}, always equals the unordered pair {b, a}. Ordered pairs are also called 2-tuples, or sequences (sometimes ...
The extraneous intermediate list structure can be eliminated with the continuation-passing style technique, foldr f z xs == foldl (\ k x-> k. f x) id xs z; similarly, foldl f z xs == foldr (\ x k-> k. flip f x) id xs z ( flip is only needed in languages like Haskell with its flipped order of arguments to the combining function of foldl unlike e ...