PLDI’17 paper accepted!

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Our paper called “Component-based Synthesis of Table Consolidation
and Transformation Tasks from Examples” will appear in PLDI’17! Here is the abstract:

This paper presents an example-driven synthesis technique
for automating a large class of data preparation tasks that
arise in data science. Given a set of input tables and an output
table, our approach synthesizes a table transformation
program that performs the desired task. Our approach is not
restricted to a fixed set of DSL constructs and can synthesize
programs from an arbitrary set of components, including
higher-order combinators. At a high-level, our approach
performs type-directed enumerative search over partial programs
but incorporates two key innovations that allow it to
scale: First, our technique can utilize any first-order specifi-
cation of the components and uses SMT-based deduction to
reject partial programs. Second, our algorithm uses partial
evaluation to increase the power of deduction and drive enumerative
search. We have evaluated our synthesis algorithm
on dozens of data preparation tasks obtained from on-line
forums, and we show that our approach can automatically
solve a large class of problems encountered by R users.

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