Software development activity clustering analysis method based on event logs

A technology of software development and cluster analysis, which is applied in the field of process mining and software engineering, can solve problems such as being difficult to understand, event logs not giving full play to their value, and insufficient attention to event log data, so as to improve training efficiency and reduce vector space The effect of dimension

Active Publication Date: 2019-04-19
YUNNAN NORMAL UNIV
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Problems solved by technology

However, due to the lack of attention to event log data, the complexity and difficulty of understanding the o

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  • Software development activity clustering analysis method based on event logs
  • Software development activity clustering analysis method based on event logs
  • Software development activity clustering analysis method based on event logs

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Embodiment 1

[0062] Embodiment 1: as figure 1 As shown, an event log-based software development activity cluster analysis method, this embodiment takes the development log file of the open source software ArgoUML as an example, and performs software development activity cluster analysis on it. The software has been downloaded more than 100,000 times, and its log files have recorded a total of 17,795 event information from 1998 to 2015 in detail, which is quite representative. The specific process includes: extracting event log feature words (Step 1), vectorizing event logs (Step 2), clustering event logs (Step 3), and completing the association between software development process events and software development activities according to the clustering results (Step 4 ).

[0063] The concrete steps of described software development activity cluster analysis method are as follows (concrete program realizes and adopts Python language):

[0064] Step1. Event log feature word extraction.

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Abstract

The invention relates to a software development activity clustering analysis method based on event logs, and belongs to the technical field of software engineering and process mining. The method comprises the following steps of Firstly, adopting a natural language processing technology for carrying out text analysis and feature word extraction on event log data of a software development process version control system, achieving software development activity event daily vectorization on the basis of word2vec, and then based on a K-means clustering algorithm, clustering vectorized software development activity events . And clustering the vectorized software development activity events by using a means clustering algorithm, obtaining an optimal clustering cluster number by using a contour coefficient method, and finally obtaining software development activities and an incidence relation between the events and the activities. According to the method, the comprehensiveness of the software development event log can be enhanced, information contained in the event log data is revealed, software development activities can be found conveniently, software development behaviors can be guided and standardized, and technical support is provided for software development.

Description

technical field [0001] The invention relates to an event log-based software development activity cluster analysis method, belonging to the technical fields of software engineering and process mining. Background technique [0002] In the process of software development, a series of software development activities and event log data will be generated. These growing event log data record the specific details of the implementation of software development activities, which are helpful for avoiding software development project risks, improving software development project maturity and control. Software product quality is of great significance. However, due to insufficient attention to event log data, the complexity and difficulty of understanding the original event log data, the event log in the software development process has not given full play to its value. Using the method of process mining to mine and analyze software development activities will help reveal the information ...

Claims

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Application Information

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IPC IPC(8): G06F8/30G06F16/35G06F17/27
CPCG06F8/30G06F40/289
Inventor 唐明靖文斌王俊陈建兵邹伟
Owner YUNNAN NORMAL UNIV
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