Abstract
Betweenness centrality helps researcher to master the changes of the system from the overall perspective in software network. The existing betweenness centrality algorithm has high time complexity but low accuracy. Therefore, Layer First Searching (LFS) algorithm is proposed that is low in time complexity and high in accuracy. LFS algorithm searches the nodes with the shortest to the designated node, then travels all paths and calculates the nodes on the paths, at last get the times of each node being traveled which is betweenness centrality. The time complexity of LFS algorithm is O(V2).
Highlights
It is over fifteen years since Norman Fenton outlined the need for a scientific basis of software measurement
The definition of betweenness centrality is the times of a node being traveled in all the shortest paths of the software network and it reflects the influence of the node in the whole network
Since both Dijkstra and Layer First Searching (LFS) are related to the number of non-isolated nodes in the software network, the relation between these two kinds of algorithm is shown through the number of non-isolated nodes by the following figures
Summary
It is over fifteen years since Norman Fenton outlined the need for a scientific basis of software measurement. Such a theory is a prerequisite for any useful quantitative approach to software engineering, little attention has been received from both practitioners and researchers. As a typical parameter and an important global statistics, betweenness centrality can meet the needs of researchers to know the inter-reaction of software network from the overall perspective. The existing betweenness centrality algorithms are either based on the shortest path or merely approximate algorithm [1–3], and both have its own shortcomings. The traditional shortest path algorithm has high time complexity and costs too much time to be available in large network, which makes it impossible to put the algorithms into practice. Compare these two algorithms to show the advantages of LFS algorithm
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