Blve:当前的软件版本是否适合发布?

Wei Zheng, Zhao Shi, Xiaojun Chen, Junzheng Chen, Manqing Zhang, Xiang Chen
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引用次数: 0

摘要

近年来,敏捷开发已成为一种流行的软件开发方法,敏捷开发过程中发生了许多版本迭代。确保每个软件版本的质量是非常重要的。然而,在实际开发中,很难了解大型软件开发的每个阶段或版本。这意味着开发人员不知道当前项目对应于哪个版本。同时,在实际开发中,软件发布也有许多必要的需求。当我们确切地知道当前项目对应的版本时,我们就可以知道当前的软件版本是否满足发布要求。因此,我们需要一个好的软件版本划分方法。本文利用机器学习的方法提出了一种新的软件版本划分方法Blve。通过对bug列表中常见的软件版本划分数据进行处理,构建了基于支持向量回归(SVR)训练的准确的软件版本划分模型。然后,对回归结果进行处理,并使用分类指标进行评价。此外,我们提出了一种基于坡度的方法来优化模型,这种优化可以将精度性能指标提高到95%左右。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Blve: Should the Current Software Version Be Suitable for Release?
Recently, agile development has become a popular software development method and many version iterations occur during agile development. It is very important to ensure the quality of each software version. However in actual development, it is difficult to know every stage or version about large-scale software development. That means developers do not know exactly which version the current project corresponds to. Simultaneously, there are many necessary requirements for software release in actual development. When we know exactly the version corresponding to the current project, we can know whether the current software version meets the release requirements. Therefore, we need a good software version division method. This paper presents a novel software version division method Blve by using machine learning method. We construct an accurate division model trained with Support Vector Regression method (SVR) to divide software version by processing the data which is commonly recorded in bug list. Then, we process the results of the regression and use the classification indicators for evaluation. In addition, we propose a slope-based approach to optimize the model, and this optimization can improve the accuracy performance measure to about 95%.
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