Regression testing of datasets

数据集的回归测试

• 批准号: 521895-2018
• 负责人: Miranskyy, Andriy
• 金额: $ 1.82万
• 依托单位: Ryerson University
• 依托单位国家: 加拿大
• 项目类别: Engage Grants Program
• 财政年份: 2018
• 资助国家: 加拿大
• 起止时间: 2018-01-01 至 2019-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=659860
• 关键词: Regression; testing; datasets

Environics Analytics builds custom analytic solutions for their clients. These solutions require creation of specialized datasets**which should be refreshed on a regular basis. During the refresh, defects may get introduced in each dataset. The Quality**Assurance team manually tests the datasets to detect and eliminate the defects, but this process is time and resource consuming.**Our goal is to detect datasets defects automatically, to streamline data refresh schedules and reduce the cost of detecting and**fixing the defects. To reach this goal, we will develop a novel regression test framework for datasets, automating the dataset**testing process. This regression framework will be integrated into Environics Analytics software development lifecycle.**This research results will improve internal processes and bolster Environics Analytics market competitiveness, ensuring that this**Canadian company continues to be a leader in the rapidly growing industry of data analytics.

Environics Analytics为他们的客户构建定制的分析解决方案。这些解决方案需要创建专门的数据集**，这些数据集应该定期刷新。在刷新期间，可能会在每个数据集中引入缺陷。质量保证团队手动测试数据集以检测和消除缺陷，但此过程耗时耗力。我们的目标是自动检测数据集缺陷，简化数据刷新时间表，降低检测和修复缺陷的成本。为了达到这个目标，我们将为数据集开发一个新的回归测试框架，自动化数据集测试过程。此回归框架将集成到Environics Analytics软件开发生命周期中。**这一研究成果将改善内部流程，增强Environics Analytics的市场竞争力，确保这家**加拿大公司继续成为快速增长的数据分析行业的领导者。