EAGER: Systematic and Scalable Testing of Concurrent Software in the Cloud

虽然多核和许多核和GPU处理器提高了计算速度，但为它们编写的并发和并行程序越来越复杂，难以验证，也难以测试。所谓的“并发错误”很难找到，因为需要检查大量的线程交错，以找出可能发生错误的情况。在顺序程序中查找错误的技术不能扩展到并发程序，特别是对于具有数据输入和共享内存的程序，这需要更严格和详尽的测试。该项目将研究一种将符号执行与进度探索相结合的方法，以找到有效的解决方案。通过寻求在云平台上并行执行来追求可伸缩性，这是迈向用于并发软件测试的云服务的一步。人们迫切需要能够对并发程序进行可扩展和高效测试的工具，如果在广泛可用的服务中实现这些工具，将对软件质量和正确性产生很大影响。这笔急切的赠款将探索这种高风险、潜在高回报的方法的可行性。

While multicore and many core and GPU processors increase computing speed, the concurrent and parallel programs written for them are increasingly complex, hard to verify, and difficult to test. So-called "concurrency bugs" are very hard to find, because of the huge number of thread interleavings that need to be examined to find the circumstances in which a bug might occur. Techniques for finding bugs in sequential programs do not scale to concurrent programs, especially for programs with data inputs and shared memory, which require more rigor and exhaustive testing. The project will investigate an approach that combines symbolic execution with a form of schedule exploration to find efficient solutions. Scalability is pursued by seeking to parallelize the execution on a cloud platform, which is a step toward a cloud service for concurrent software testing. There is a dire need for tools capable of doing scalable and efficient testing of concurrent programs, which will have a high impact on software quality and correctness if implemented in a widely available service. This EAGER grant will explore the feasibility of this high-risk, potentially high-reward approach.