Constraint Logic Programming

这项研究的长期目标是支持编程语言研究中的既定范式，以减少编程工作并缩短开发时间。约束逻辑编程（CLP）是一类新的编程语言，其基本操作是在计算域上求解约束。CLP语言最适合用于通常需要大量专业知识和开发时间的组合问题。典型的例子包括电路的调度和形式化验证。CLP语言目前支持部分枚举（包括分支、绑定和回溯）作为主要范例。第一代这些语言的成功代表是CHIP，它现在广泛应用于工业（例如西门子，Bull和ICL），用于诸如香港港口船舶调度之类的任务。本项目将开发第二代CLP语言，从三个方向扩展对组合问题的支持：1。约束处理：通过提供新的原语操作（如约束蕴涵）和组合原语约束的新方法，将纳入新的推理和修剪技术；2. 执行模型：将研究动态规划和局部搜索，以便将它们纳入CLP语言；3. 计算领域：该项目将研究新的应用领域，如计算几何和解析，其中约束在识别新的计算领域中起着基础作用。

The long-term goal of this research is to support established paradigms in programming language research in order to reduce programming effort and shorten development time. Constraint logic programming (CLP) is a new class of programming languages whose basic operation is constraint solving over a computation domain. CLP languages are best used for combinatorial problems that often require considerable expertise and development time. Typical examples include scheduling and formal verification of circuits. CLP languages presently support partial enumeration (subsuming branch and bound and backtracking) as the main paradigm. A successful representative of the first generation of these languages is CHIP which is now widely used in industry (e.g., at Siemens, Bull and ICL) for tasks like the scheduling of ships in Hong Kong harbor. This project will develop a second-generation CLP language, extending the support for combinatorial problems in three directions: 1. Constraint handling: new reasoning and pruning techniques will be incorporated by providing new primitive operations such as constraint entailment and new ways of combining primitive constraints; 2. Execution models: dynamic programming and local search will be investigated in order to incorporate them into CLP languages; 3. Computation domains: the project will investigate new application areas such as computational geometry and parsing where constraints play a fundamental role in order to identify new computation domains.