CCRI: Medium: Collaborative Research: Open-Source, State-of-the-Art Symbolic Model-Checking Framework

CCRI：媒介：协作研究：开源、最先进的符号模型检查框架

• 批准号: 2016597
• 负责人: Natarajan Shankar
• 金额: $ 56.86万
• 依托单位: SRI International
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-10-01 至 2024-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2016597&HistoricalAwards=false
• 关键词: CCRI; Medium; Collaborative; Research; Open

Safety-critical and security-critical systems are entering our lives at an increasingly rapid pace. These are the systems that help fly our planes, drive our cars, deliver our packages, ensure our electricity, or even automate our homes. Especially when humans cannot perform a task in person, e.g., due to a dangerous working environment, we depend on such systems. Before any safety-critical system launches into the human environment, we need to be sure it is really safe. Model checking is a popular and appealing way to rigorously check for safety: given a system, or an accurate model of the system, and a safety requirement, model checking is a "push button" technique to produce either a proof that the system always operates safely, or a counterexample detailing a system execution that violates the safety requirement. Many aspects of model checking are active research areas, including more efficient ways of reasoning about the system's behavior space, and faster search algorithms for the proofs and counterexamples.As model checking becomes more integrated into the standard design and verification process for safety-critical systems, the platforms for model checking research have become more limited. Previous options have become closed-source or industry tools; current research platforms don't have support for expressive specification languages needed for verifying real systems. This project will fill the current gap in model checking research platforms: building a freely-available, open-source, scalable model checking infrastructure that accepts expressive models and efficiently interfaces with the currently-maintained state-of-the-art back-end algorithms to provide an extensible research and verification tool. This project will create a community resource with a well-documented intermediate representation to enable extensibility, and a web portal, facilitating new modeling languages and back-end algorithmic advances. To add new modeling languages or algorithms, researchers need only to develop a translator to/from the new intermediate language, and will then be able to integrate each advance with the full state-of-the-art in model checking. This community infrastructure will be ideal for catapulting formal verification efforts in many cutting-edge application areas, including security, networking, and operating system verification. This project will particularly target outreach to the embedded systems (CPS) community as the proposed new framework will make hardware verification problems from this community more accessible.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

安全关键和安全关键系统正以越来越快的速度进入我们的生活。这些系统帮助我们驾驶飞机，驾驶汽车，运送包裹，确保电力供应，甚至实现家庭自动化。特别是当人类无法亲自执行任务时，例如，由于工作环境危险，我们依赖这些系统。在任何安全关键系统进入人类环境之前，我们需要确保它是真正安全的。模型检查是一种流行且有吸引力的严格检查安全性的方法：给定一个系统或系统的准确模型以及安全要求，模型检查是一种“按钮”技术，可以证明系统始终安全运行，或者生成一个反例，详细说明违反安全要求的系统执行。模型检测的许多方面都是活跃的研究领域，包括更有效的方法来推理系统的行为空间，以及更快的搜索算法的证明和反例。随着模型检测越来越多地集成到标准设计和验证过程的安全关键系统，模型检测的研究平台变得越来越有限。以前的选项已经成为封闭源代码或行业工具;当前的研究平台不支持验证真实的系统所需的表达性规范语言。该项目将填补当前模型检查研究平台的空白：构建一个免费可用的，开源的，可扩展的模型检查基础设施，接受表达模型，并与当前维护的最先进的后端算法有效地接口，以提供可扩展的研究和验证工具。该项目将创建一个社区资源，其中包含一个文档齐全的中间表示，以实现可扩展性，以及一个门户网站，促进新的建模语言和后端算法的进步。要添加新的建模语言或算法，研究人员只需要开发一个转换器到新的中间语言/从新的中间语言，然后将能够将每个进步与模型检查的最新技术相结合。这个社区基础设施将是在许多尖端应用领域（包括安全、网络和操作系统验证）中进行正式验证工作的理想选择。该项目将特别针对嵌入式系统（CPS）社区的推广，因为拟议的新框架将使该社区的硬件验证问题更容易获得。该奖项反映了NSF的法定使命，并被认为值得通过使用基金会的智力价值和更广泛的影响审查标准进行评估来支持。