SHF: Small: Software and Hardware Support for Detecting Concurrency, Sequential and Distributed Bugs via Data-Flow Invariants

软件可靠性对于许多应用程序至关重要。多核硬件和并行编程的普及使得并行bug成为一个日益重要和紧迫的问题。并发错误与其他类型的错误一起严重影响了软件的可靠性。尽管人们在软件缺陷的检测方面做了大量的工作，但现有的工作还远远不够理想，许多缺陷，特别是并行或分布式程序中的缺陷，仍然很难被现有的工具捕捉到。该方案通过提出一种新颖的、广泛适用的数据流不变性，可以检测各种类型的软件错误，包括并行错误和其他类型的错误，使软件更加可靠和安全，从而朝着提高软件的正确性，特别是并行和分布式软件的正确性迈出了重要一步。我们坚信，我们提出的研究可以有效地提高我们对这一挑战的理解，提供大量的工具支持，软件开发，并大大提高并行和分布式软件的质量。我们还为学生，特别是计算机科学专业的女学生规划了各种教育和外联活动。

Software reliability is critical for many applications. The pervasiveness of multi-core hardware and parallel programming makes parallel bugs become an increasingly important and urgent issue. Concurrency bugs together with the other types of bugs have significantly impacted software reliability. Although much effort has been put on detecting software bugs, existing work is still far from ideal, and many bugs, especially those in parallel or distributed programs, are still difficult to catch by existing tools. This proposal makes a major step toward improving the correctness of software, especially parallel and distribute software, by proposing a novel and widely applicable invariance, called data-flow invariance, that can be used to detect various types of software bugs, including parallel bugs and other types of bugs, and make software more reliable and secure. We strongly believe that our proposed research can effectively improve our understanding of this challenge, provide substantial tool support to software development, and greatly improve the quality of parallel and distributed software. We have also planned various educational and outreach activities for students, especially women students in computer science.