Bridging Boolean and Quantitative Synthesis Using Smoothed Proof Search - Inria - Institut national de recherche en sciences et technologies du numérique Access content directly
Conference Papers Year : 2014

Bridging Boolean and Quantitative Synthesis Using Smoothed Proof Search


We present a new technique for parameter synthesis under boolean and quantitative objectives. The input to the technique is a "sketch" - a program with missing numerical parameters - and a probabilistic assumption about the program's inputs. The goal is to automatically synthesize values for the parameters such that the resulting program satisfies: (1) a boolean specification, which states that the program must meet certain assertions, and (2) a quantitative specification, which assigns a real valued rating to every program and which the synthesizer is expected to optimize. Our method - called smoothed proof search - reduces this task to a sequence of unconstrained smooth optimization problems that are then solved numerically. By iteratively solving these problems, we obtain parameter values that get closer and closer to meeting the boolean specification; at the limit, we obtain values that provably meet the specification. The approximations are computed using a new notion of smoothing for program abstractions, where an abstract transformer is approximated by a function that is continuous according to a metric over abstract states. We present a prototype implementation of our synthesis procedure, and experimental results on two benchmarks from the embedded control domain. The experiments demonstrate the benefits of smoothed proof search over an approach that does not meet the boolean and quantitative synthesis goals simultaneously.
Fichier principal
Vignette du fichier
clochard14popl.pdf (2.04 Mo) Télécharger le fichier
Origin : Files produced by the author(s)

Dates and versions

hal-00920955 , version 1 (19-12-2013)


  • HAL Id : hal-00920955 , version 1


Swarat Chaudhuri, Martin Clochard, Armando Solar-Lezama. Bridging Boolean and Quantitative Synthesis Using Smoothed Proof Search. POPL - 41st ACM SIGPLAN-SIGACT Symposium on Principles of Programming Languages, Jan 2014, San Diego, United States. ⟨hal-00920955⟩
321 View
259 Download


Gmail Facebook X LinkedIn More