SPt:从软件文档中提取相关区域进行探索性测试的文本挖掘过程

Cloves Lima, Ivan Santos, F. Barros, A. Mota
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引用次数: 0

摘要

软件产品必须显示出高质量水平,才能在竞争激烈的市场中取得成功。通常,产品的可靠性是通过测试活动来保证的。然而,软件测试有时会被公司忽视,因为它的成本很高——尤其是在手工执行的时候。在这种情况下,本工作研究了软件测试自动化的智能方法,重点放在软件产品审查过程上。我们提出了一个基于使用文本挖掘技术检查软件文档(特别是发布说明)的测试计划创建的新过程。实现的原型,SWAT计划工具(SPt),自动地从发行说明中提取软件的相关区域,以供探索性测试团队检查。SPt使用我们的合作伙伴摩托罗拉移动公司的真实数据进行了测试。实验将当前的手工过程与使用SPt的自动化过程进行了比较,访问了两种方法所花费的时间和确定的相关区域。获得的结果是非常令人鼓舞的。
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SPt: A Text Mining Process to Extract Relevant Areas from SW Documents to Exploratory Tests
Software products must show high-quality levels to succeed in a competitive market. Usually, products reliability is assured by testing activities. However, SW testing is sometimes neglected by Companies due to its high costs - particularly when manually executed. In this light, this work investigates intelligent methods for SW testing automation, focusing on the software products review process. We propose a new process for test plan creation based on the inspection of SW documents (in particular, Release Notes) using text mining techniques. The implemented prototype, the SWAT Plan tool (SPt), automatically extracts from Release Notes relevant areas of the SW to be examined by exploratory tests teams. SPt was tested using real-world data from Motorola Mobility, our partner Company. The experiments compared the current manual process with the automated process using SPt, accessing time spent and relevant areas identified in both methods. The obtained results were very encouraging.
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