Logo Data Structures and Algorithms with Object-Oriented Design Patterns in Java
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Running Time Analysis

The KruskalsAlgorithm method begins by creating an graph to hold the result spanning tree (lines 7-9). Since a spanning tree is a sparse graph the GraphAsLists class is used to represent it. Initially the graph contains tex2html_wrap_inline70519 vertices but no edges. The running time for lines 7-9 is tex2html_wrap_inline70543.

Next all of the edges in the input graph are inserted one-by-one into the priority queue (lines 11-19). Since there are tex2html_wrap_inline70531 edges, the worst-case running time for a single insertion is tex2html_wrap_inline71399. Therefore, the worst-case running time to initialize the priority queue is

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when adjacency lists are used, and

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when adjacency matrices are used to represent the input graph.

The main loop of the method comprises lines 22-35. This loop is done at most tex2html_wrap_inline70531 times. In each iteration of the loop, one edge is removed from the priority queue (lines 24-25). In the worst-case this takes tex2html_wrap_inline71399 time.

Then, two partition find operations are done to determine the elements of the partition that contain the two end-points of the given edge (lines 26-29). Since the partition contains at most tex2html_wrap_inline70519 elements, the running time for the find operations is tex2html_wrap_inline71861. If the two elements of the partition are distinct, then an edge is added to the spanning tree and a join operation is done to unite the two elements of the partition (lines 30-35). The join operation also requires tex2html_wrap_inline71861 time in the worst-case. Therefore, the total running time for the main loop is tex2html_wrap_inline71865.

Thus, the worst-case running time for Kruskal's algorithm is

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when adjacency lists are used, and

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when adjacency matrices are used to represent the input graph.


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Bruno Copyright © 1998 by Bruno R. Preiss, P.Eng. All rights reserved.