Towards a Universal Data Provenance Framework Using Dynamic Instrumentation

Abstract

The advantage of collecting data provenance information has driven research on how to extend or modify applications and systems in order to provide it, or the creation of architectures that are built from the ground up with provenance capabilities. In this paper we propose a universal data provenance framework, using dynamic instrumentation, which gathers data provenance information for real-world applications without any code modifications. Our framework simplifies the task of finding the right points to instrument, which can be cumbersome in large and complex systems. We have built a proof-of-concept implementation of the framework on top of DTrace. Moreover, we evaluated its functionality by using it for three different scenarios: file-system operations, database transactions and web browser HTTP requests. Based on our experiences we believe that it is possible to provide data provenance, transparently, to any layer of the software stack