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

职业：利用现场数据测试高度可配置且快速发展的普及系统

基本信息

批准号：
0347518
负责人：
Sebastian Elbaum
金额：
$ 40万
依托单位：
University of Nebraska-Lincoln
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2004
资助国家：
美国
起止时间：
2004-03-15 至 2010-02-28
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=0347518&HistoricalAwards=false
关键词：
CAREER Leveraging Field Data Test

项目摘要

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.

内布拉斯加州 - 林肯科医师的Abstract0347518Sebastian Elbaumuniversity：利用现场数据来测试高度可配置和快速发展的Pervasive Systemsoftsoftware测试工程师无法预测的，更不用说锻炼了，更不用说锻炼了，他们的软件面临的潜在场景数量过多。取而代之的是，他们基于对发布后如何使用软件的假设来分配有限的资源。然而，内部活动之间缺乏联系以及该领域中软件的使用方式可能导致假设不准确，从而导致系统寿命的软件质量和可靠性降低。该项目将通过开发少量足迹来捕获现场数据和自适应测试技术来解决这些挑战，以利用这些信息。这两个主要目标是：1）为大量用户和资源合格监控方案设计分析机制，以减少执行开销，以及2）开发自适应测试技术，以连续表征软件行为以识别测试不足，重新测试资源并扩展现有测试套件以克服其限制。经验研究将定期用于技术评估和探索。这项工作的教育组成部分旨在为本科教室带来对现实世界验证问题的早期欣赏，并为学生提供精心设计的软件质量和经验验证的准备。