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Computing as a whole suffers from a crisis of reproducibility. Programs executed in one context are aston- ishingly hard to reproduce in another context, resulting in wasted effort by people and general distrust of results produced by computer. The root of the problem lies in the fact that every program has implicit dependencies on data and execution environment which are rarely understood by the end user. To address this problem, we present PRUNE, the Preserving Run Environment. In PRUNE, every task to be executed is wrapped in a functional interface and coupled with a strictly defined environment. The task is then executed by PRUNE rather than the user to ensure reproducibility. As a scientific workflow evolves in PRUNE, a growing but immutable tree of derived data is created. The provenance of every item in the system can be precisely described, facilitating sharing and modification between collaborating researchers, along with efficient management of limited storage space. We present the user interface and the initial prototype of PRUNE, and demonstrate its application in matching records and comparing surnames in U.S. Censuses