A Quantitative Measurement Method of Code Quality Evaluation Indicators based on Data Mining

2022 9th International Conference on Dependable Systems and Their Applications (DSA) Pub Date : 2022-08-01 DOI:10.1109/DSA56465.2022.00094

Yikang Shao, Wu Liu, J. Ai, Chunhui Yang

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引用次数: 1

Abstract

Software Code Quality Measurement is a systematic subject with a long history and rich theory. Since the 1960s, a large number of academic research on software code quality measurement methods have been generated. Many scholars have proposed software code quality measurement indicators and measurement methods, and given the measurement trend of evaluation indicators, and proposed a model to measure software quality. However, there are still some blanks in the quantitative evaluation of software code quality evaluation index. The software code quality measurement system is not complete enough to cover all aspects of software code quality from multiple perspectives. In addition, most studies have measured software code quality based on code inspection or code review, which has some limitations. This paper puts forward a software code quality evaluation system based on software network. On this basis, this paper proposes a quantitative measurement method of code quality evaluation indicators based on data mining. It provides a new idea for software quality evaluation or code quality evaluation.

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基于数据挖掘的代码质量评价指标定量度量方法

软件代码质量度量是一门历史悠久、理论丰富的系统学科。自20世纪60年代以来，产生了大量关于软件代码质量度量方法的学术研究。许多学者提出了软件代码质量度量指标和度量方法，并给出了评价指标的度量趋势，提出了软件质量度量模型。但是，在软件代码质量评价指标的定量评价方面还存在一些空白。软件代码质量度量体系不够完整，无法从多个角度涵盖软件代码质量的所有方面。此外，大多数研究都是基于代码检查或代码评审来度量软件代码质量，这有一定的局限性。提出了一种基于软件网络的软件代码质量评价体系。在此基础上，提出了一种基于数据挖掘的代码质量评价指标的定量度量方法。它为软件质量评价或代码质量评价提供了一种新的思路。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

2022 9th International Conference on Dependable Systems and Their Applications (DSA)

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