Software module clustering method for probability selection

A software module, probabilistic selection technology, applied in software maintenance/management, computer parts, character and pattern recognition, etc., can solve problems such as large amount of calculation and small scale

Active Publication Date: 2018-03-06
西安新量标科技有限公司
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AI Technical Summary

Problems solved by technology

[0006] Problems to be solved by the present invention: In order to overcome the shortcomings of the large amount of calculation in the existing methods, a probabilistic selection software module clustering method is proposed, which provides a relatively simple and good clustering effect for the large-scale software system module clustering problem method to cluster large-scale complex software systems into smaller, more manageable subsystems

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  • Software module clustering method for probability selection
  • Software module clustering method for probability selection
  • Software module clustering method for probability selection

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Embodiment Construction

[0050] Take a software system as an example, such as figure 2 Shown is the method call relationship diagram of the software system, specifically illustrating the specific implementation of the software module clustering method disclosed in the present invention.

[0051] (1) For example figure 2 The shown method calls the relation graph coding, there are 10 methods in this software system, and these methods can be expressed as F={f by set F 1 ,f 2 ,..., f j ,..., f 10}, j is any integer value between 1 and 10, f j (1≤j≤10) represents the jth method in the software system, and is coded by a 10×10 two-dimensional matrix B,

[0052] (2) Assuming that the software system needs to be clustered to form m (m1 ,c 2 ,... c i ,... c m}, i is any integer value between 1 and m, c i (1≤i≤m) means the ith module of the software system after module clustering. The module clustering scheme of the software system can be expressed as a 10-dimensional vector Cluster, and the cluste...

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Abstract

The invention aims at the problem of software module clustering in software system reconstruction and discloses a software module clustering method for probability selection. The software module clustering method comprises the steps that a module dependency relation drawing of a software system is extracted and obtained from a software system source program, then nodes are subjected to local merging operation based on probability selection by taking sparse points in the drawing as starting points so that initial module clusters of the software system can be obtained, then the cluster to whicheach node belongs is dynamically adjusted according to the correlation number of the nodes and all the modules based on the probability, and the clustering result of software modules is obtained. Thesoftware module clustering method provides a simple engineering method with high convergence rate and good clustering effect for the clustering problem of the software modules, and is used for reconstructing a software system structure and improving the understandability of the software system.

Description

technical field [0001] The invention belongs to the technical field of software system reconfiguration, specifically relates to the module clustering problem in software system reconfiguration, provides a software module clustering method based on probability selection, and mainly solves how to optimize system code in software system code reconfiguration Structure, to achieve the purpose of eliminating system redundancy, increasing the comprehensibility of the software system, and reducing the maintenance cost of the software system. Background technique [0002] Software maintenance is a very important stage in the software life cycle, and its maintenance cost is often high. With the increase and change of business requirements, the modular structure of the software system often deviates from the original design structure with the change of the software system. The software system needs to be constantly refactored, and it becomes more and more difficult to understand and ma...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F8/72G06K9/62
Inventor 孙家泽令蓓蕾
Owner 西安新量标科技有限公司
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