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An extended constraint deductive database: Theory and implementation

机译:扩展约束演绎数据库:理论与实现

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The scheme of Hereditary Harrop formulas with constraints, HH(C), has been proposed as a basis for constraint logic programming languages. In the same way that Datalog emerges from logic programming as a deductive database language, such formulas can support a very expressive framework for constraint deductive databases, allowing hypothetical queries and universal quantifications. As negation is needed in the database field, HH(C) is extended with negation to get HH_(C). This work presents the theoretical foundations of HH_(C) and an implementation that shows the viability and expressive power of the proposal. Moreover, the language is designed in a flexible way in order to support different constraint domains. The implementation includes several domain instances, and it also supports aggregates as usual in database languages. The formal semantics of the language is defined by a proof-theoretic calculus, and for the operational mechanism we use a stratified fixpoint semantics, which is proved to be sound and complete w.r.t. the former. Hypothetical queries and aggregates require a more involved stratification than the common one used in Datalog. The resulting fixpoint semantics constitutes a suitable foundation for the system implementation.
机译:已经提出了具有约束的遗传哈罗普公式的方案HH(C),作为约束逻辑编程语言的基础。就像Datalog作为一种演绎数据库语言从逻辑编程中出现一样,这些公式可以支持约束演绎数据库的非常有表达力的框架,从而允许进行假想查询和通用量化。由于在数据库字段中需要否定,因此对HH(C)进行否定扩展以获取HH_(C)。这项工作介绍了HH_(C)的理论基础,并展示了该提案的可行性和表达能力。此外,该语言以灵活的方式设计,以支持不同的约束域。该实现包括多个域实例,并且它也照常支持数据库语言中的聚合。语言的形式语义由证明理论演算定义,对于操作机制,我们使用分层的定点语义,事实证明它是合理且完整的。前者。假设的查询和汇总需要比Datalog中使用的常见查询更复杂的分层。由此产生的定点语义构成了系统实现的合适基础。

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