Fri 12 Jan 2018 16:40 - 17:05 at Bunker Hill - Synthesis Chair(s): Nadia Polikarpova

We present a new approach to example-guided program synthesis based on counterexample-guided abstraction refinement. Our method uses the abstract semantics of the underlying DSL to find a program $P$ whose abstract behavior satisfies the examples. However, since program $P$ may be spurious with respect to the concrete semantics, our approach iteratively refines the abstraction until we either find a program that satisfies the examples or prove that no such DSL program exists. Because many programs have the same input-output behavior in terms of their abstract semantics, this synthesis methodology significantly reduces the search space compared to existing techniques that use purely concrete semantics.

While synthesis using abstraction refinement (SYNGAR) could be implemented in different settings, we propose a refinement-based synthesis algorithm that uses abstract finite tree automata (AFTA). Our technique uses a coarse initial program abstraction to construct an initial AFTA, which is iteratively refined by constructing a proof of incorrectness of any spurious program. In addition to ruling out the spurious program accepted by the previous AFTA, proofs of incorrectness are also useful for ruling out many other spurious programs.

We implement these ideas in a framework called Blaze, which can be instantiated in different domains by providing a suitable DSL and its corresponding concrete and abstract semantics. We have used the Blaze framework to build synthesizers for string and matrix transformations, and we compare Blaze with existing techniques. Our results for the string domain show that Blaze compares favorably with FlashFill, a domain-specific synthesizer that is now deployed in Microsoft PowerShell. In the context of matrix manipulations, we compare Blaze against Prose, a state-of-the-art general-purpose VSA-based synthesizer, and show that Blaze results in a 90x speed-up over Prose. In both application domains, Blaze also consistently improves upon the performance of two other existing techniques by at least an order of magnitude.

Fri 12 Jan

Displayed time zone: Tijuana, Baja California change

15:50 - 17:05
SynthesisResearch Papers at Bunker Hill
Chair(s): Nadia Polikarpova University of California, San Diego
15:50
25m
Talk
Strategy Synthesis for Linear Arithmetic Games
Research Papers
Azadeh Farzan University of Toronto, Zachary Kincaid Princeton University
16:15
25m
Talk
Bonsai: Synthesis-Based Reasoning for Type Systems
Research Papers
Kartik Chandra Stanford University, Rastislav Bodík University of Washington
16:40
25m
Talk
Program Synthesis using Abstraction Refinement
Research Papers
Xinyu Wang UT Austin, Işıl Dillig UT Austin, Rishabh Singh Microsoft Research