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Note that with respect to example of "recurrence analysis of merge sort," it can be considered that both "merge sort" is applied to "recurrence analysis" and "recurrence analysis" is applied to "merge sort." For finding out prerequisite relationship, the order of presentation of concepts X and Y is considered.
A user can select and click on a particular concept from the relational graph, let us say Merge Sort. His view is then shifted to conceptual realm where he sees the objects related to the concept.
The constant factor implicit in the above analysis matches the constant factor 2 for merge sort in several cases, if we require that all I/Os be simple and respect track boundaries, as defined at the end of Section 3.
In this section, we describe variants of merge sort and distribution sort that achieve the bounds in Theorems 3.1-3.3.
The standard merge sort algorithm works as follows: In the "run" formation phase, the N/B tracks are inputted into memory, in groups of one memoryload at a time; each memoryload is sorted into a "run," which is then output to consecutive positions on disk.