Functional Logic Programming with Distributed Constraint Solving System

分布式约束求解系统的函数逻辑编程

基本信息

批准号：
10480053
负责人：
IDA Tetsuo
金额：
$ 6.4万
依托单位：
University of Tsukuba
依托单位国家：
日本
项目类别：
Grant-in-Aid for Scientific Research (B)
财政年份：
1998
资助国家：
日本
起止时间：
1998 至 1999
项目状态：
已结题

项目摘要

Our contributions are (i) development of computation models for functional logic programming languages with distributed constraint solving systems and (ii) realization of a programming environment based on the computation models.(i) Design of computation modelsWe started the research project with the design of a computation model called Lazy Narrowing Calculus (LNC). LNC forms the basis of our investigation into all our computation models for functional and logic programming. To deal with constraint solving in functional logic programming languages, we extended LNC to the conditional case. The resulting calculus is called Lazy Conditional Narrowing Calculus (LCNC). Moreover, we removed the non-determinism inherent in LCNC. This simplifies the implementation of the calculus on computers and improves the computational efficiency.Furthermore we designed higher-order calculi, i.e. Applicative LNC, which simulates higher-order computation by using (first-order) applicative terms for representing terms, and Higher-Order Lazy Narrowing Calculus (LNff), which can handle lambda terms. We proved that all the above-mentioned calculi have completeness.(ii) Implementation of the programming systemWe implemented a functional logic programming system in a distributed environment. The system is called Constraint Functional Logic Programming system (CFLP). CFLP consists of three components : an interpreter, a scheduler, and a constraint solving system. We implemented CFLP as a distributed software system using the programming language Mathematica. The computation mechanism of CFLP is based on the narrowing calculi. The interpreter of the functional logic programming language in CFLP system solves given equations by accessing constraint solvers in a distributed environment. The narrowing calculi find solutions over the domain of term algebra. The other domain-specific constants and operations are handled by the constraint solvers which provide the domain-specific solving methods.

我们的贡献是（i）使用分布式约束解决系统的功能逻辑编程语言开发计算模型，以及（ii）基于计算模型的编程环境的实现。（i）计算设计Modelswe的设计启动了研究项目，设计了一个名为Lazy Narricking Calculus（LNC）的计算模型。 LNC构成了我们对所有计算模型进行功能和逻辑编程的调查的基础。为了处理功能逻辑编程语言中的约束求解，我们将LNC扩展到了条件情况。所得的演算称为懒惰条件狭窄的微积分（LCNC）。此外，我们删除了LCNC固有的非确定性。这简化了计算机上的演算的实现，并提高了计算效率。我们设计了更高阶的计算，即应用LNC，该计算方法通过使用（一阶）适用术语来模拟高阶计算，以表示可以代表较高的狭窄calculus（lnff），该术语可以处理LAMBDA术语。我们证明了所有上述计算都有完整性。（ii）编程Systemwe的实现在分布式环境中实现了功能逻辑编程系统。该系统称为约束功能逻辑编程系统（CFLP）。 CFLP由三个组件组成：解释器，调度程序和约束解决系统。我们使用编程语言Mathematica实现了CFLP作为分布式软件系统。 CFLP的计算机制基于狭窄的计算。 CFLP系统中功能逻辑编程语言的解释器通过在分布式环境中访问约束求解器来解决给定方程。狭窄的微积分在术语代数的域上找到解决方案。其他特定于域的常数和操作由提供特定于域特异性求解方法的约束求解器来处理。