A Practical Introduction to Data Structures and Algorithm Analysis

Sec. 7.7 Binsort and Radix Sort 259over the time required to find the k largest elements using one of the other sortingmethods described earlier. One situation where we are able to take advantage of thisconcept is in the implementation of Kruskal’s minimum-cost spanning tree (MST)algorithm of Section 11.5.2. That algorithm requires that edges be visited in ascendingorder (so, use a min-heap), but this process stops as soon as the MST iscomplete. Thus, only a relatively small fraction of the edges need be sorted.7.7 Binsort and Radix SortImagine that for the past year, as you paid your various bills, you then simply piledall the paperwork onto the top of a table somewhere. Now the year has ended andits time to sort all of these papers by what the bill was for (phone, electricity, rent,etc.) and date. A pretty natural approach is to make some space on the floor, and asyou go through the pile of papers, put the phone bills into one pile, the electric billsinto another pile, and so on. Once this initial assignment of bills to piles is done (inone pass), you can sort each pile by date relatively quickly because they are eachfairly small. This is the basic idea behind a Binsort.Section 3.9 presented the following code fragment to sort a permutation of thenumbers 0 through n − 1:for (i=0; i