CNS Core: Small: Automated testing for data- and compute-intensive distributed systems through feedback-based fuzzing

大规模数据存储和处理的需求使得分布式系统变得至关重要。然而，对现代分布式系统进行编程尤其具有挑战性，因为它需要对跨机器运行的并发代码、不可靠的网络、软件和硬件故障以及复杂的应用程序逻辑进行正确的推理。在实践中，尽管开发人员面临着挑战，但目前还没有好的选择来自动和全面地测试分布式系统。该项目侧重于开发有效测试数百万用户使用的数据和计算密集型分布式应用程序的技术，这些应用程序几乎运行在每个云服务和数据中心上。通过汇集操作系统、分布式系统和系统测试方面的专业知识，该项目将通过以下方式对理论和实践做出贡献：(1)设计和构建高效的测试执行引擎，透明地使大型分布式系统适应低开销和高吞吐量的执行；(2)探索测试覆盖和突变策略，用于处理多节点和容错系统；(3)开发技术，利用分布式系统错误的可能根源来最小化测试用例并重现生产失败。分布式系统现在是社会最基本服务的基础，包括电子商务、银行、金融、医疗和物流服务。这个项目将允许分布式系统开发人员通过开发实用的和高覆盖率的测试方法来构建更可靠的分布式系统。所开发的测试方法将防止服务停机、数据丢失、系统故障以及数十亿美元行业的业务和客户信任损失。此外，开发的测试系统将减少开发人员用于修复分布式系统的工作量和时间，这对开发人员来说是众所周知的挑战。所有项目数据都存储在公共站点和大学存储系统中，以确保安全长期存储至少七年，从获奖结束或公开发布（以较晚者为准）起。生成的数据包括系统实现和源代码、文档、测试集、分析数据集和教育材料。该项目信息将在https://www.cs.purdue.edu/homes/pfonseca/projects/ds-fuzzing.html.This上公布。该奖项反映了美国国家科学基金会的法定使命，并通过基金会的知识价值和更广泛的影响审查标准进行评估，认为值得支持。

The demand for large-scale data storage and processing has made distributed systems crucial. However, programming modern distributed systems is particularly challenging because it requires correct reasoning about concurrent code running across machines, unreliable networks, software and hardware failures, and complex application logic. In practice, despite the challenges faced by developers, there are currently no good options to test distributed systems automatically and comprehensively. This project focuses on developing techniques that effectively test data- and compute-intensive distributed applications used by millions of users, running on virtually every cloud service and data center.By bringing together expertise in operating systems, distributed systems, and systems testing, this project will make contributions to both theory and practice by (1) designing and building efficient test execution engines that transparently make large distributed systems amenable to low-overhead and high-throughput execution, (2) exploring test coverage and mutation policies that are tuned to address multi-node and fault-tolerant systems, and (3) developing techniques that use the likely root cause of distributed system bugs to minimize test cases and reproduce production failures.Distributed systems are now the foundation of society's most essential services, including e-commerce, banking, financial, medical, and logistics services. This project will allow distributed system developers to build more reliable distributed systems by developing practical and high-coverage testing approaches. The testing approaches developed will prevent service downtime, data loss, system malfunctions, and business and customer trust loss across a range of multi-billion dollar industries. Furthermore, the testing systems developed will reduce developer effort and time devoted to fixing distributed systems, which are notoriously challenging for developers.All project data is stored in public sites and university storage systems to ensure safe long-term storage for at least seven years from the award conclusion or public release, whichever comes later. The data produced includes system implementations and source code, documentation, test sets, analysis datasets, and educational material. The project information will be located at https://www.cs.purdue.edu/homes/pfonseca/projects/ds-fuzzing.html.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.