Code abstract integration method based on quality assurance framework

A code summary, quality assurance technology, applied in the field of software quality assurance, can solve problems such as documents that have not been investigated, and achieve the effect of improving effectiveness

Pending Publication Date: 2021-08-20
CHONGQING UNIV
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Problems solved by technology

However, no previous work has investigated whether quality assurance methods for document generation tasks can be applied to improve code summarization

Method used

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  • Code abstract integration method based on quality assurance framework
  • Code abstract integration method based on quality assurance framework
  • Code abstract integration method based on quality assurance framework

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[0049] The present invention will be further described below.

[0050] The present invention describes a code summary integrated method based on a quality assurance frame. The core idea of ​​the invention is to automatically predict the quality of the summary generated by the most advanced code summary method by a given code fragment and a plurality of code summary methods, and select a predicted effect as a result of the final generated. The invention is integrated by the mass fraction of the calculation code summary and the code summary method integrates two stages. First, consist of a coordinated component and a retrieval-based component for calculating the mass fraction of the summary; secondly, the alternative code summary method is configured for method integration.

[0051] Specifically, first, give a Code i , Use the current most advanced code summary method for code i Generate multiple candidates Second, build CODE based on coordinated components i Map tables between differ

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Abstract

The invention relates to a code abstract integration method based on a quality assurance framework. The method comprises the following steps: generating I candidate codes by utilizing an existing code abstract method; on the basis of a collaborative filtering component, for each candidate code abstract, respectively calculating two mass scores Precisioni and Recalli, and on the basis of a retrieved component, calculating a mass score REScorei; the harmonic average F1scorei of the candidate code abstracts is calculated by means of the mass fraction Precisioni and the mass fraction Recalli of each candidate code abstract, and the harmonic average F1scorei of the candidate code abstracts is calculated by means of the mass fraction Precise and the mass fraction Recalli of each candidate code abstract; and selecting one candidate code abstract with the best quality as a final output result sum by comparing the harmonic average of the candidate code abstracts and comparing the REScore values of the candidate code abstracts. According to the method, the advantages of different models can be effectively integrated, so that the effectiveness of the code abstract is improved.

Description

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Claims

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Application Information

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Owner CHONGQING UNIV
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