Abstract Regulations are pervasive in information systems. They manifest themselves as design rules, integrity constraints, deadlines, conventions, information disclosure requirements, policies, procedures, contracts, taxes, quotas and other statutes. Managing regulations is difficult. Regulations are complex, change frequently and rest on models of the real world that involve unusual vocabulary if not unusual concepts. Consequently, checking compliance with regulations is tedious and error‐prone. Logic programming appears to provide a good framework for developing regulation management systems. Besides permitting arbitrary regulations to be modelled, it offers rapidity and ease of development, readability, incremental modifiability, extensibility and portability. These features are not provided by existing DP programming tools, database managers or conventional expert‐system shells. This paper investigates the application of logic programming in a significant regulation management application: Workers' Compensation Insurance premium auditing. The insurance premium computation rules for the State of California were encoded as a large Prolog program. This application illustrates specific strengths and weaknesses of logic programming and Prolog in dealing with large‐scale real‐world regulations.

This paper investigates the use of a cellular tree computer, the FFP machine, for parallel processing of relational databases. This machine directly executes Formal Functional Programming (FFP) code. A method to embed SQL statements in FFP programs is described. Schemes for parallel implementation of simple retrieval statements are presented for different I/O architectures. Then techniques for parallel implementation of more complex retrieval statements are given. Because the FFP machine can accommodate the almost unbounded parallelism of FFP programs, execution time analysis shows potential for highly efficient execution of relational database queries on this machine. Modifications of the FFP machine to speed up input/output operations are discussed.

This paper examines the use of the Geometric Arithmetic Parallel Processor (GAPP) IC systolic array chip as the major processing element in the design and construction of a high-speed, parallel, relational database machine. This chip is of particular interest because it is one of the first commercially available systolic array chips. A brief review of the architectural features of the GAPP is presented. Parallel algorithms for handling basic relational database operations-simple queries, joins, and sorts-are presented. Building blocks of cascaded systolic arrays are developed to implement these algorithms. A database machine architecture to incorporate these building blocks is described and compared to existing designs.