SAFIR, analogy-based system for database definition and query reuse.

Abstract

This thesis presents a system which employs analogical reasoning to define and manipulate databases. The objective is to model the behavior of naive users who often adapt database relations and queries from documentation examples to the problem at hand. The user has at her disposal a manual that contains examples of database designs with a variety of database queries in some exemplary milieu called the base domain. The manual explains the example queries in simple terms and gives their implementation in a database query language such as SQL. Our user is not a database expert. She can neither define the database nor can she compose query implementations from scratch. At best she can construct simple queries in the base domain by copying them verbatim from the manual. Our system works in two steps: first it defines a target database by building incrementally analogies represented by pairs of object correspondences, base-target. These analogies are built by mapping objects, relationships, and semantic constructs from the base domain into the target domain. The process is then interactive and incremental (i.e. the user can accept or reject the inferred analogies). The second step of the approach consists to derive target domain query's implementation from its specification by reusing queries developed in the base domain. We rely on a weak form of derivational analogy--traces of a planner operating in the base domain are used to derive a target domain query's implementation in SQL from its specification. The very simple planner used builds in the base domain plans that result in particularly simple, prototypical queries. Queries are specified in a high level subset of natural language.