利用机器学习算法提高项目的敏捷性

IF 3 4区 计算机科学 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS
Janani Varun, R A Karthika
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引用次数: 0

摘要

所有开发出来的软件产品都需要测试,以确保产品的质量和准确性。在敏捷时代,如果测试人员能够优化所花费的精力并预测即将到来的模块的缺陷,那么他们的生活就会变得更加轻松。本文讨论的功能是使用随机森林算法预测缺陷。预测分析利用过去的信息来创建对未来事件结果的预测。产品团队总是难以按计划交付产品。由于我们正处于敏捷时代,需求不断变化,团队无法确定即将发布的产品。预测有助于团队在即将发布的版本中专注于复杂和易出错的模块。在历史数据的帮助下,所设计的预测分析模型能以 88% 的准确率预测缺陷。通过预测,测试人员可以将重点放在模型预测的缺陷数量较多的模块上,并对交付进行左移。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Improving agility in projects using machine learning algorithm

Improving agility in projects using machine learning algorithm

All the software products developed will need testing to ensure the quality and accuracy of the product. It makes the life of testers much easier when they can optimize on the effort spent and predict defects for the upcoming modules in the Agile era. The functionality being discussed in this paper is to predict the defects using Random Forest Algorithm. Predictive analytics draws on information from the past to create forecasts about the outcomes of future events. Product team always have the difficulty in delivering the product as per schedule. As we are in the agile era, the requirement keeps changing and team is unsure on upcoming releases. Prediction helps the team to focus on the complex and error prone modules in upcoming releases. The Predictive analytics model designed, can predict defects with an accuracy rate of 88% with the help of historical data. By predicting, testers can focus on the module where there are a greater number of defects predicted by the model and left shift the delivery.

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来源期刊
Multimedia Tools and Applications
Multimedia Tools and Applications 工程技术-工程:电子与电气
CiteScore
7.20
自引率
16.70%
发文量
2439
审稿时长
9.2 months
期刊介绍: Multimedia Tools and Applications publishes original research articles on multimedia development and system support tools as well as case studies of multimedia applications. It also features experimental and survey articles. The journal is intended for academics, practitioners, scientists and engineers who are involved in multimedia system research, design and applications. All papers are peer reviewed. Specific areas of interest include: - Multimedia Tools: - Multimedia Applications: - Prototype multimedia systems and platforms
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