  Interactive tools make data analysis both more efficient and more accessible
to a broad population. Simple interfaces such as Google Finance as well as
complex visual exploration interfaces such as Tableau are effective because
they are tailored to the desired user tasks. Yet, designing interactive
interfaces requires technical expertise and domain knowledge. Experts are
scarce and expensive, and therefore it is currently infeasible to provide
tailored (or precise) interfaces for every user and every task.
  We envision a data-driven approach to generate tailored interactive
interfaces. We observe that interactive interfaces are designed to express sets
of programs; thus, samples of programs-increasingly collected by data
systems-may help us build interactive interfaces. Based on this idea, Precision
Interfaces is a language-agnostic system that examines an input query log,
identifies how the queries structurally change, and generates interactive web
interfaces to express these changes. The focus of this paper is on applying
this idea towards logs of structured queries. Our experiments show that
Precision Interfaces can support multiple query languages (SQL and SPARQL),
derive Tableau's salient interaction components from OLAP queries, analyze <75k
queries in <12 minutes, and generate interaction designs that improve upon
existing interfaces and are comparable to human-crafted interfaces.
