Detection and Impact Analyses of Feature Interactions

处理大型软件系统的复杂性的一种常见策略是将系统分解为更容易处理的较小的子系统。基于特征的分解是一种功能分解，其中特征是可以独立考虑、开发和发展的功能单元。因为特性提供了不同的功能，所以它们代表了不同的开发任务，这些任务可以增量地添加、由单独的团队并行执行或外包给第三方供应商。功能可能是可选的，甚至是可征收关税的，从而允许通过产品线大规模定制产品。基于特征的分解的缺点是意外的特征交互，其中一个特征的动作与另一个特征的动作相互干扰，导致冲突、新出现的功能行为，并可能人为地传染到其他特征和系统。*本项目研究四个补充分析，以实现对特征交互和特征演变的有效推理：(1)轻量级静态分析，使工程师能够对所有特征执行系统范围的分析，并识别可能导致安全隐患的潜在特征交互；(2)可扩展的动态分析；(3)组合代码级分析，允许在不影响整体系统行为的情况下检查一个特征实现是否可以被另一个替代；以及(4)产品线分析，使工程师能够同时高效地分析和验证多个功能配置，从而为公众提供更多的定制产品选择。拟议工作的预期结果是一组计算机支持的方法和技术，用于分析不同软件开发构件中表达的功能之间潜在的和已实现的交互作用。这些工具将根据它们在检测交互方面的有效性和对大型软件系统的可扩展性进行评估，并将在一定程度上根据我们工业合作伙伴的软件构件进行评估。*

A common strategy for dealing with the complexity of large software systems is to decompose the system into smaller sub-systems that can be tackled more easily. Feature-based decomposition is a type of functional decomposition, in which features are units of functionality that can be considered, developed, and evolved independently. Because features provide distinct functionalities, they represent distinct development tasks that can be added incrementally, performed by separate teams in parallel, or outsourced to third-party vendors. Features may be optional or even tariffable, thereby allowing for mass customization of products through product-lining. The downside of feature-based decomposition is unexpected feature interactions, in which the actions of one feature interfere with those of another, leading to conflicts, emergent functional behaviours, and possibly artificial contagion to other features and systems.****This project investigates four complementary analyses that enable efficient reasoning about feature interactions and feature evolution: (1) Lightweight static analyses that enable engineers to perform a system-wide analysis of all features, and identify potential feature interactions that can lead to safety hazards; (2) scalable dynamic analyses and (3) compositional code-level analyses that allow checking whether one feature implementation can be substituted for another without affecting the overall system behaviour; and (4) product-line analyses that enable engineers to analyze and verify multiple feature configurations simultaneously and efficiently, making it possible offer a larger selection of customized products to the public. The expected outcomes of the proposed work are a collection of computer-supported methods and techniques for analyzing potential and realized interactions among features expressed in different software-development artifacts. The tools will be evaluated with respect to their effectiveness in detecting interactions and their scalability to large software systems, and will be evaluated in part on software artifacts from our industrial partner.******