TESS: automated support for the evolution of persistent types

Abstract

Persistent data often has a long lifetime. During its lifetime, the types that are used to structure the data may undergo evolution to support new requirements or provide more efficient services. This evolution often makes the persistent data inaccessible unless it also evolves with the types. Existing systems that support type and data evolution focus on changes isolated to individual types, thereby limiting what can be easily accomplished during maintenance. We extend this work by presenting a model of compound type changes that can also describe changes simultaneously involving multiple types and their effects on data. We then describe TESS (Type Evolution Software System), a system to automate the evolution of types and their associated data when the types undergo compound type changes.