SHF: Small: Automated Detection and Repair of Errors in Event-Driven Applications

事件驱动软件在现代社会中扮演着极其重要的角色，在各种领域，包括基于浏览器的Web软件，服务器端应用程序和运行在移动的设备上的应用程序。在这样的应用程序中，控制流由用户或外部系统触发的事件驱动。编写事件驱动的软件是出了名的容易出错，当程序员犯错误时，各种类型的错误就会显现出来，而这些错误是出了名的难以调试。事件驱动的网络软件的质量仍然是一个重大挑战，编程错误破坏了对在线提供商品或服务的公司和机构的信心，并可能使它们面临法律和财务风险。该项目的智力优势是开发实用的算法和工具，用于检测和自动修复事件驱动软件中的错误。该项目的更广泛的意义和重要性来自于基于网络的软件质量的改进，这些软件由用于查找和修复错误的实用工具实现。该项目的技术重点是在静态和动态程序分析算法中提供事件驱动控制流的良好解决方案的开发，在实用工具中实现它们，并在现实世界的软件中对其进行评估。正在研究的具体研究课题包括：能够防止数据沿着沿着不可行的控制流路径流动的精确过程间数据流分析算法、用于使用promise的JavaScript代码的静态分析算法、现在在JavaScript社区中广泛采用的异步计算的机制、以及用于自动修复web应用中的事件竞争错误的技术，通过根据指定的修复策略限制浏览器中的事件处理程序调度。这些技术将有助于开发更可靠的事件驱动软件，使程序员能够更快地检测和修复错误。该项目正在将开发的工具作为开源发布，并通过确保感兴趣的研究人员能够为代码库做出贡献，围绕这些工具建立一个用户社区。NSF高级网络基础设施办公室的软件集群对此特别感兴趣，该办公室为该奖项提供共同资助。

Event-driven software plays an exceedingly important role in modern society, in a variety of domains that include browser-based software for the web, server-side applications, and apps running on mobile devices. In such applications, control flow is driven by events that are triggered by users or by external systems. Writing event-driven software is notoriously error-prone, and when programmers make mistakes, various types of errors manifest themselves that are notoriously difficult to debug. The quality of event-driven web-based software remains a significant challenge, and programming errors undermine confidence in companies and institutions that offer goods or services on-line, and may put them at risk legally and financially. The intellectual merits of this project are the development of practical algorithms and tools for detecting and automatically repairing errors in event-driven software. The project's broader significance and importance follows from improvements in the quality of web-based software that are enabled by practical tools for finding and fixing errors. The technical focus of this project is on the development of well-founded solutions for accommodating event-driven control flow in static and dynamic program analysis algorithms, implementing them in practical tools, and evaluating them on real-world software. Specific research topics under study include the development of: precise interprocedural data flow analysis algorithms that are capable of preventing data flow along infeasible control-flow paths, static analysis algorithms for JavaScript code that makes use of promises, a mechanism for asynchronous computation that is now widely adopted in the JavaScript community, and techniques for automatically repairing event race errors in web applications, by restricting event handler scheduling in the browser according to a specified repair policy. Together, these techniques will facilitate the development of more reliable event-driven software, by enabling programmers to detect and repair errors more quickly.The project is releasing the developed tools as open source and is building a user community around the tools by ensuring that interested researchers are able to contribute to the codebase. This aspect is of special interest to the software cluster in NSF's Office of Advanced Cyberinfrastructure, which provides co-funding for this award.