Constraint Logic Programming

这项研究的长期目标是支持已建立的 编程语言研究中的范式，以减少 编程工作量和缩短开发时间。 约束逻辑程序设计（CLP）是一类新的程序设计 语言，其基本操作是在 计算域 CLP语言最适合用于组合 这些问题往往需要大量的专业知识和发展 时间 典型的例子包括调度和形式验证 电路. CLP语言目前支持部分枚举 （包括分支和边界以及回溯）作为主要范例。 一 这些语言第一代的成功代表 是现在广泛用于工业的CHIP（例如，关于Siemens，Bull 和ICL）的任务，如调度船舶在香港港口。 该项目将开发第二代CLP语言，扩展 支持三个方向的组合问题： 1. 约束处理：新的推理和修剪技术将 通过提供新的原语操作来合并， 约束蕴涵与基元组合的新方法 限制; 2. 执行模型：动态编程和局部搜索将是 进行调查，以便将其纳入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，其中约束起基本作用，以便 识别新计算域。

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.