Managing Constraints as Data

数据库已经成为数据驱动的数字时代的基石。世界上的事件和观察产生了大量的数据，这些数据被安全地存储在数据库中，并通过数据库查询有效地分析。分析结果进一步支持广泛软件系统的决策制定，例如工资和财务管理、控制系统和运筹学。这些决策必须尊重安全性和正确性约束。约束的例子随处可见：工资截止日期、最大容量、服务器可用性等。虽然数据库技术在数据存储和分析方面表现出色，但目前它无法为约束的管理和验证提供相同水平的有效性。目前，为了填补这一空白，需要程序员手动开发特定于应用程序的程序。但这种努力代价高昂，而且极易出错。由于人为错误和有缺陷的软件而导致的约束违反在行业和政府的不同部门中经常被观察到。这个拟议的研究计划旨在通过扩展数据库的作用来包括约束管理来纠正这种情况。

Database has been a cornerstone in the data-driven digital age. Events and observations in the world generate large volumes of data which are safely stored in databases and efficiently analyzed by database queries. The results of the analysis further support decision making of a wide range of software systems, e.g. payroll and financial management, control systems, and operational research. These decisions must respect safety and correctness constraints. Examples of constraints are everywhere: payroll deadlines, maximal power capacity, server availability etc.. While the database technology excels at data storage and analytics, presently it fails to provide the same level of effectiveness for the management and verification of constraints. Currently, to fill this gap, application specific programs need to be manually developed by programmers. But such efforts are costly and highly error-prone. Constraint violations as the results of human errors and buggy software are frequently observed in different sectors of the industry and governments. This proposed research program is aimed to rectify the situation by extending the role of the database to include the management of constraints.