Detecting and Preventing Program Inconsistencies under Database Schema Evolution

Nowadays, data-intensive applications tend to access their underlying database in an increasingly dynamic way. The queries that they send to the database server are usually built at runtime, through String concatenation, or Object-Relational-Mapping (ORM) frameworks. This level of dynamicity significantly complicates the task of adapting application programs to database schema changes. Failing to correctly adapt programs to an evolving database schema results in program inconsistencies, which in turn may cause program failures. In this paper, we present a tool-supported approach, that allows developers to (1) analyze how the source code and database schema co-evolved in the past and (2) simulate a database schema change and automatically determine the set of source code locations that would be impacted by this change. Developers are then provided with recommendations about what they should modify at those source code locations in order to avoid inconsistencies. The approach has been designed to deal with Java systems that use dynamic data access frameworks such as JDBC, Hibernate and JPA. We motivate and evaluate the proposed approach, based on three real-life systems of different size and nature.