SHF: Small: Empirical Studies, Principles and Techniques for Software Systems with Complex Configuration Spaces

SHF：小型：具有复杂配置空间的软件系统的实证研究、原理和技术

• 批准号: 1116740
• 负责人: Jeffrey Foster
• 金额: $ 50万
• 依托单位: University of Maryland, College Park
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-07-15 至 2016-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1116740&HistoricalAwards=false
• 关键词: SHF; Small; Empirical; Studies; Principles

Today's software systems are increasingly built from flexible combinations of components that can be configured in a multitude of different ways. For example, the popular Firefox web browser has more than a thousand configuration options. While a high degree of configurability has many benefits, it also makes testing and reasoning about configurable software a major challenge. The goals of this proposed work are 1) to develop new techniques to efficiently discover the structure of software systems' configuration spaces, and 2) to exploit that information to improve common software engineering tasks, specifically testing and program understanding. In particular, this work will allow software developers to quickly and accurately answer questions such as, What are the "right" configurations to test a system under? How can we avoid testing a system under "unnecessary" configurations? How does software configuration change as systems evolve? We expect that, as much of the software used today is configurable, the advances made in this project in understanding and testing configurable systems will have widespread benefits in the reliability and trustworthiness of critical software.The proposed technical approach will pursue four main directions. First, the PIs will develop a representation of "effective" configuration spaces---the configurations needed to achieve a specific goal---that is both usable by software engineering tools and understandable to developers. Second, the PIs will develop novel techniques that compute the effective configuration space of a system. Third, the PIs will explore a number of software engineering applications that will make use of effective configuration space information, including configuration-aware test case selection, configuration-aware regression testing, and several program understanding tasks for configurable systems. Finally, the PIs will conduct a wide range of fundamental empirical studies that will test the research hypotheses and evaluate the proposed approach on large scale subject systems. Among others outcomes, these studies will examine the effective configurations of a range of systems; investigate how those configurations evolve over time; and determine how failures relate to system configurations. The results will impact both practice and education.

当今的软件系统越来越多地由可以通过多种不同方式进行配置的组件的灵活组合构建而成。 例如，流行的火狐网络浏览器有一千多个配置选项。 虽然高度可配置性有很多好处，但它也使可配置软件的测试和推理成为一项重大挑战。 这项工作的目标是 1) 开发新技术来有效地发现软件系统配置空间的结构，2) 利用该信息来改进常见的软件工程任务，特别是测试和程序理解。 特别是，这项工作将使软件开发人员能够快速准确地回答诸如以下问题：测试系统的“正确”配置是什么？ 我们如何避免在“不必要的”配置下测试系统？ 软件配置如何随着系统的发展而变化？我们预计，由于当今使用的大部分软件都是可配置的，因此该项目在理解和测试可配置系统方面取得的进步将对关键软件的可靠性和可信度产生广泛的好处。所提出的技术方法将追求四个主要方向。首先，PI 将开发“有效”配置空间的表示（实现特定目标所需的配置），该表示既可由软件工程工具使用，又可供开发人员理解。 其次，PI 将开发计算系统有效配置空间的新技术。第三，PI 将探索许多利用有效配置空间信息的软件工程应用程序，包括配置感知测试用例选择、配置感知回归测试以及可配置系统的几个程序理解任务。 最后，PI 将进行广泛的基础实证研究，以测试研究假设并评估大规模学科系统所提出的方法。除其他成果外，这些研究将检验一系列系统的有效配置；研究这些配置如何随时间演变；并确定故障与系统配置的关系。结果将影响实践和教育。