CAREER: Leveraging Field Data to Test Highly-Configurable and Rapidly-Evolving Pervasive Systems

摘要：sebastian ElbaumUniversity of nebraska - lincoln职业：利用现场数据来测试高度可配置和快速发展的普遍系统软件测试工程师无法预测，更不用说练习了，他们的软件面临的大量潜在场景。相反，他们根据软件发布后如何使用的假设来分配有限的资源。然而，缺乏内部活动和软件如何在现场使用之间的联系会导致不准确的假设，从而导致软件质量和系统生命周期内可靠性的下降。该项目将通过开发具有较小足迹的分析技术来捕获现场数据，以及可以利用该信息的自适应测试技术来解决这些挑战。两个主要目标是：1)为大型用户池和资源认知监控方案设计分析机制，以减少执行开销；2)开发自适应测试技术，持续表征软件行为，以识别测试不足，重新调整测试资源，并扩展现有测试套件以克服其局限性。将定期采用实证研究方法进行技术评价和探索。这项工作的教育部分旨在将对现实世界验证问题的早期理解带入本科课堂，并使学生对软件质量和经验验证精通。

ABSTRACT0347518Sebastian ElbaumUniversity of Nebraska-LincolnCAREER: Leveraging Field Data to Test Highly-Configurable and Rapidly Evolving Pervasive SystemsSoftware test engineers cannot predict, much less exercise, the overwhelming number of potential scenarios faced by their software. Instead, they allocate their limited resources based on assumptions about how the software will be employed after release. Yet, the lack of connection between in-house activities and how the software is employed in the field can lead to inaccurate assumptions, resulting in decreased software quality and reliability over the system's lifetime. This project will address those challenges by developing profiling techniques with a small footprint to capture field data and adaptive testing techniques that can leverage that information. The two primary objectives are: 1) to design profiling mechanisms for large pools of users andresource-cognizant monitoring schemes to reduce execution overhead, and 2) to develop adaptive testing techniques that continuously characterize software behavior to identify testing inadequacies, realign testingresources, and extend existing test suites to overcome their limitations. Empirical studies will be regularly employed for technique evaluation and exploration. The educational component of this work aims at bringing an earlier appreciation of the real-world validation problems to the undergraduate classroom and prepare students well-versed in software quality and empirical validation.