Next-generation Constraint Solvers for Software Engineering and Security

约束求解器，即自动求解数学约束的程序，在工程和科学领域有着广泛的应用。求解器可以被比作瑞士军刀，用于规划机器人的运动、配置汽车或自动发现软件中的错误等应用。工程师使用数学约束对他们的问题建模，然后使用求解器自动解决问题。就在十年前，像文字处理器和操作系统这样的商业软件的可伸缩的自动bug发现被认为实际上是不可行的。由于求解器性能的显著提高（包括我在内的许多研究人员），自动bug查找不仅变得可行，而且在微软等公司也是强制性的。虽然迄今为止的成果很重要，但随着工程师们解决软件合成等更难的应用，对功能更强大、表达能力更强的求解器的需求仍在持续增长。因此，我提出了一个长期的研究计划，以开发新的求解器技术，这些技术比现在的求解器更快，更有表现力，旨在开发软件可靠性和安全性的软件工程工具。

Constraint solvers, programs that automatically solve mathematical constraints, are used in myriad applications in engineering and science. Solvers can be likened to swiss-army knives, used in applications such as planning a robot's movement, configuring a car or automatically finding bugs in software. Engineers model their problem using mathematical constraints, and then use solvers to automatically solve them. As little as a decade ago, scalable automatic bug-finding of commercial software like word processors and operating systems was considered practically infeasible. Thanks to impressive gains in solver performance (due to many researchers including myself), not only has automatic bug-finding become feasible but is mandatory in companies like Microsoft. While the gains to-date are important, the demand for ever-more powerful and expressive solvers continues to grow unabated as engineers tackle even harder applications such as software synthesis. Hence, I propose a long-term research program to develop new solver techniques that are orders of magnitude faster and more expressive than today's, aimed at software engineering tools for software reliability and security.