Using Temporal Logic and Datalog to Query Databases Evolving in Time (Classic Reprint) - Softcover

Inhaltsangabe

Explore how databases that change over time can be queried with logic that tracks evolution.

This book introduces a formal framework that blends temporal logic with Datalog to handle dynamic databases. It explains how time can be integrated into queries and how different semantics affect results, from traditional fixpoint ideas to inflationary, time-aware approaches.

Readers will see how temporal logic can express queries about events across time and how these queries relate to standard Datalog programs. The text compares domain-dependent and domain-independent queries, introduces safe Datalog with inflationary semantics, and demonstrates how to translate temporal queries into executable rules. Clear examples illustrate the construction of ordering predicates and practical techniques for modeling database evolution.

• Definitions of dynamic semantics and inflationary Datalog for time-aware queries
• Ways to express and compare temporal logic queries with Datalog
• Techniques to encode the order of data insertion and preserve safety
• Concrete examples showing how to compute complex relations over time

Ideal for students and professionals working with databases, logic, and temporal data modeling.

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