Test case prioritization

该提案是IBM CAS Canada和Ryerson大学的数据科学实验室合作的成果，旨在构建软件工具辅助的测试用例优先排序模型。软件分析指导从业者在整个软件开发过程中做出决策。在这种情况下，预测模型可以帮助管理人员有效地组织他们的资源，并通过以智能和有意义的方式分析现有项目数据的模式来识别问题。管理数据收集、分析和校准以及与软件组织中的现有系统进行通信以提供有价值的信息的一体化工具是必要的。多年来，我们已经开发了这样一个工具，称为Dione。Dione是用于软件交付平台的软件交付智能和预测性分析工具。它有一个智能决策优化引擎(挖掘、过滤、预测)。它集成了完整决策支持周期的数据提取、报告和预测模块，并以平台无关的方式提供最低配置解决方案。在这个项目中，我们的目标是将Dione部署到IBM Rational Team Concert(RTC)中，以解决有关测试用例优先级的实际挑战。测试用例优先排序技术将测试用例排定为要执行的顺序，以尝试提高它们在满足某些性能目标方面的有效性。可以实现各种目标；其中一个目标涉及故障检测率--测试过程中检测到故障的速度。在测试过程中提高故障检测率可以对被测系统提供更快的反馈，并让软件工程师比其他情况下更早开始纠正故障。如果建议的解决方案成功应用，不仅会影响RTC的产品质量，而且会成为RTC用户的最佳实践。换句话说，这将为加拿大的一个特定软件行业触发级联效益。

This proposal is a collaborative effort between IBM CAS Canada and the Data Science Laboratory at Ryerson University to build a software tool-aided test case prioritization model. Software analytics guide practitioners in decision making throughout the software development process. In this context, prediction models can help managers efficiently organize their resources and identify problems by analyzing patterns on existing project data in an intelligent and meaningful manner. It is necessary to have all-in-one tools that manage data collection, analysis, and calibration as well as communicate with existing systems in software organizations to provide valuable information. Over the years we have developed such a tool, called Dione. Dione is a software delivery intelligence and predictive analytics tool for a software delivery platform. It has an intelligent decision optimization engine (mining, filtering, prediction). It integrates data extraction, reporting, and prediction modules for a complete decision support cycle and offers a minimum configuration solution in a platform agnostic manner. In this project we aim to deploy Dione to IBM Rational Team Concert (RTC) to address practical challenges regarding Test Case prioritization. Test case prioritization techniques schedule test cases for execution in an order that attempts to increase their effectiveness in meeting some performance goal. Various goals are possible; one involves rate of fault detection - a measure of how quickly faults are detected within the testing process. An improved rate of fault detection during testing can provide faster feedback on the system under test, and let software engineers begin correcting faults earlier than might otherwise be possible. In the case of successful application of the proposed solution, it will not only impact the product quality of RTC but also be a best practice for the users of it. In other words, this will trigger cascaded benefits for a particular software industry in Canada.