Transparent persistence promises to integrate programming languages and databases by allowing procedural programs to access persistent data with the same ease as non-persistent data. When the data is stored in a relational database, however, transparent persistence does not naturally leverage the performance benefits of relational query optimization. We present a program analysis that combines the benefits of both approaches by extracting database queries from programs with transparent access to persistent data. The analysis uses a sound abstract interpretation of the original program to approximate the data traversal paths in the program and the conditions under which the paths are used. The resulting paths are then converted into a query, and the program is simplified by removing redundant tests. We study an imperative kernel language with read-only access to persistent data and identify the conditions under which the transformations can be applied. This analysis approach promises to combine the software engineering benefits of transparent data persistence with the performance benefits of database query optimization.
To recover some of the benefits of these optimizations REF proposes the use of abstract interpretation to statically extract SQL queries from the code.
Extracting queries by static analysis of transparent persistence
POPL '07
Computer Science