Answering Historical What-if Queries with Provenance, Reenactment, and Symbolic Execution

What-if queries predict how the results of an analysis would change based on hypothetical changes to a database. While a what-if query determines the effect of a hypothetical change on a query’s result, it is often unclear how such a change could have been achieved limiting the practical applicability of such queries. We propose an alternative model for what-if queries where the user proposes a hypothetical change to past update operations. Answering such a query amounts to determining the effect of a hypothetical change to past operations on the current database state (or a query’s result). We argue that such historical what-if queries are often easier to formulate for a user and lead to more actionable insights. In this paper, we take a first stab at answering historical what-if queries. We use reenactment, a declarative replay technique for transactional histories, to evaluate the effect of a modified history on the current database state. Furthermore, we statically analyze the provenance dependencies of a history to limit reenactment to transactions and data affected by a hypothetical change.