SHF: Large:Collaborative Research: PASS: Perpetually Available Software Systems

尽管在测试、静态分析、规范和验证方面做出了巨大的努力，但所有现实世界的软件--桌面应用程序、服务器和运输系统--都存在缺陷和功能缺失，给美国经济造成了数十亿美元的损失，并威胁到我们的福祉。 该项目提出了一个变革性的范式转移到“永久可用的软件系统”（PASS），这将使软件更可用和强大的直接解决部署的软件中的错误。 PASS创新将（1）通过保持真实世界的软件运行更长时间来改善用户体验;（2）确保良好的性能;（3）帮助开发人员修复错误，同时允许在运行的软件上安全地部署补丁，以避免停机。该项目将在开源软件库中挖掘错误报告，以导出错误类和测试套件。它将通过与存储库中的错误报告和补丁进行比较来评估系统的有效性。 创新将包括（1）针对常见错误的检测和补救元素，（2）补救和在线更新的语义基础，以及（3）整合元素以利用组件之间的协同作用。 该项目将探索和分析新的安全，概率安全和扩展语义补救/更新。该项目将开发C/C++和Java运行时，因为它们是使用最广泛的语言，并提出独特的挑战。方法将包括结合动态、静态和补救/更新分析和结果。 该项目将培训研究生、本科生和博士后学生，并参与对代表性不足群体的外联活动。这些工具将向公众开放，以增加国家研究基础设施。

Despite heroic efforts in testing, static analysis, specification, and verification, all real-world software -- desktop applications, servers, and transportation systems---deploys with defects and missing functionality, costing the US economy billions and threatening our well-being. This project proposes a transformative paradigm shift to "perpetually available software systems" (PASS) that will make software more available and robust by directly addressing errors in deployed software. PASS innovations will (1) improve user experience by keeping real-world software running longer; (2) ensure good performance; (3) assist developers in fixing errors while allowing patches to be safely deployed on running software, to avoid downtime. The project will mine error reports in open source software repositories to derive error classes and test suites. It will evaluate system effectiveness by comparing with bug reports and patches in repositories. Innovations will include (1) detection and remediation elements that target common errors, (2) semantic foundations for remediation and on-line updating, and (3) integration of elements to exploit synergy among the components. The project will explore and analyze novel safe, probabilistically-safe, and extended-semantics remediations/updates. The project will develop both C/C++ and Java runtimes, because they are the most widely used languages and pose unique challenges. Methods will include combining dynamic, static, and remediation/update analysis and results. The project will train graduate, undergraduate, and post doctoral students, and participate in outreach to under-represented groups. The tools will be made publicly available, adding to the national research infrastructure.