Risk Analysis Method Oriented to Software Modification

Abstract

The invention relates to a risk analysis method for software modification. The present invention uses the TF‑IDF algorithm to extract keywords and feed them back to the developers, and analyzes the modification submission information from the perspective of the repaired bug information, and provides risk results and corresponding risk explanations for the modification submission of the developers. A risk analysis is submitted for the submission, which combines the developer's historical submission information and the comment information in the bug for reference in the developer's modification submission, and gives the cause of the defect, forms a description of the risk characteristics, and gives the corresponding Risk explanation. The invention overcomes the defect that the developer's development history and the content in related bug comments were not considered in the past. The invention provides the cause of defects, effectively improves the quality of software maintenance and reduces the risks brought by software maintenance.

Description

technical field [0001] The invention belongs to the field of software maintenance, in particular to a risk analysis method oriented to software modification. Background technique [0002] Due to the complexity of software engineering, software loopholes often appear in the process of software development and maintenance, and these loopholes cause a lot of loss of manpower and material resources. Therefore, software quality issues have become one of the important divisions in the field of software engineering research. Nowadays, many studies focus on the prediction of software quality, and many software analysis and prediction works have proposed methods about software measurement and software models, which are used to accurately analyze and predict software quality. However, the adoption rate of the current analysis and prediction technology is very low, and the analysis and prediction of software quality is still a difficult problem, because there is a lack of corresponding...

AI Technical Summary

Problems solved by technology

However, these technologies do not take into account the development history of developers and the content of related bug comments, making the analysis of submitted information incomplete, and at the same time, they do not provide intuitive risk prediction results and causes of defects, and developers cannot clearly understand To fully understand the reasons for the risks in the current revision submission, you need to determine it yourself based on statistical data. The lack of specific analysis and explanation of the entire software submission makes the process of software maintenance more difficult.

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