Fine grained data management to achieve evolution resilience in a software development environment

Abstract

A software development environment (SDE) exhibits evolution resilience if changes to the SDE do not adversely affect its functionality nor performance, and also do not introduce delays in returning the SDE to an operational state after a change. Evolution resilience is especially difficult to achieve when manipulating fine grained data, which must be tightly bound to the language in which the SDE is implemented to achieve adequate performance. We examine a spectrum of approaches to tool integration that range from high SDE-development-time efficiency to high SDE-execution-time efficiency. We then present a meta-environment, a specific SDE tailored to the development of target SDE's, that supports easy movement of individual tools along this spectrum.