Compiling Distributed System Models into Implementations

将分布式系统模型编译为实现

• 批准号: RGPIN-2020-05203
• 负责人: Beschastnikh, Ivan
• 金额: $ 2.55万
• 依托单位: University of British Columbia
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2022
• 资助国家: 加拿大
• 起止时间: 2022-01-01 至 2023-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=749780
• 关键词: Compiling; Distributed; System; Models; into

Cloud computing has revolutionized computing. Enterprises, large and small, are taking advantage of the flexibility and capacity of massive data centers for their infrastructure. However, systems that run in the cloud are notoriously complex to engineer because these systems are designed to scale by executing across many machines. For example, given two events at different hosts, it is not obvious whether one of the events is causally dependent on the other, even if each event has a timestamp. Bugs in cloud-based systems can be subtle and catastrophic. For example, in 2017 a bug in Amazon's S3 storage system caused $150 million of dollars in damage for the companies that rely on Amazon AWS cloud services. Such incidents are increasingly common. Engineers who build cloud-based systems today rely on testing to gain assurance. Unfortunately, attaining reasonable distributed behavior coverage with testing is an established challenge while writing tests is tedious, error-prone, and fundamentally incomplete. State-of-the-art techniques for achieving distributed system correctness are rarely used in practice because they do not work on actual large-scale systems or because they require substantial effort and expertise. There is a growing interest in modeling languages for distributed systems, which can be checked exhaustively or proved to satisfy certain properties. However, today, the developer must manually translate a formal model of their system into an implementation. This process requires intensive effort and may introduce bugs into the implementation. This is one reason why developers rarely model their systems, electing instead to build first and debug later. In the proposed research program I will design and implement techniques to compile formal models of distributed systems, written in a high-level modeling language, into runnable implementations. As part of my research I will create a toolchain that will flip the dominant software engineering process used for cloud-based systems: developers will be able to first create formal models that they can verify, and then later compile these models into code. By deriving a runnable and equivalent implementation for free, developers will be more incentivized to create and curate formal models of their systems. The long-term goal of this research is to incentivize developers to use formal methods earlier in the design/implementation effort to decrease the number of bugs that make it into production systems. This research will generate new scientific knowledge about the modeling of distributed systems and compilation of distributed logic. As part of this research my team will also work to integrate this new knowledge into robust open source tools. These tools can then be used by industry practitioners to develop reliable and maintainable distributed systems more rapidly.

云计算彻底改变了计算。大小的企业正在利用其基础设施的大量数据中心的灵活性和能力。但是，在云中运行的系统对于工程师来说是复杂的，因为这些系统的设计旨在通过在许多机器上执行来扩展。例如，给定两个主机上的两个事件，即使每个事件都有时间戳，其中一个事件是否在因果关系上依赖于另一个事件。基于云的系统中的错误可能是微妙的灾难性的。例如，在2017年，亚马逊S3存储系统中的一个错误对依靠亚马逊AWS Cloud Services的公司造成了1.5亿美元的损失。这样的事件越来越普遍。当今建立基于云的系统的工程师依靠测试来获得保证。不幸的是，通过测试获得合理的分布式行为覆盖范围是一个既定的挑战，而写作测试则乏味，容易出错并且根本不完整。实践中很少使用用于实现分布式系统正确性的最新技术，因为它们不适用于实际的大规模系统，或者因为它们需要大量的努力和专业知识。对分布式系统的建模语言的兴趣越来越大，可以详尽地检查或证明可以满足某些属性。但是，如今，开发人员必须将其系统的正式模型手动转化为实施。这个过程需要大量的努力，并可能将错误引入实施中。这就是为什么开发人员很少对系统建模，选择先建造并在以后进行调试的原因之一。在拟议的研究计划中，我将设计和实施技术，以将用高级建模语言编写的分布式系统的正式模型编译为可运行的实现。作为我的研究的一部分，我将创建一个工具链，该工具链将翻转用于基于云的系统的主要软件工程过程：开发人员将能够首先创建可以验证的正式模型，然后将这些模型编译为代码。通过免费获得可运行和同等的实现，开发人员将更加激励他们创建和策划其系统的正式模型。这项研究的长期目标是激励开发人员在设计/实施工作中使用正式方法，以减少将其进入生产系统的错误数量。这项研究将产生有关分布式系统建模和分布式逻辑汇编的新科学知识。作为这项研究的一部分，我的团队还将努力将这些新知识纳入强大的开源工具中。然后，行业从业人员可以使用这些工具来更快地开发可靠和可维护的分布式系统。