Growing solver-aided languages with rosette

262 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

FlashMeta: a framework for inductive program synthesis (2015, methodology): “Three main initiatives in this space are S KETCH [35], R OSETTE [36], and SyGuS [1].”
Neurosymbolic Programming (2021, methodology): “Rosette (Torlak and Bodik, 2013) is a framework embedded into the Racket virtual machine that translates a subset of the Racket language into an SMT constraint using symbolic execution.”
Unsupervised Learning by Program Synthesis (2015, methodology): “The program synthesis community introduced solver-based methods for learning programs [7, 23, 9], and our work builds upon their techniques.”
Program Synthesis (2017, methodology): “Most popular synthesis frameworks include the aforementioned Sketch system [132], the PROSE framework for FlashFill-like programming by examples [113], and the Rosette virtual machine for solver-aided programming [139].”
Neural-Guided Deductive Search for Real-Time Program Synthesis from Examples (2018, unknown): “Most approaches employ either bottom-up enumerative search (Udupa et al., 2013), constraint solving (Torlak & Bodik, 2013), or inductive logic programming (Lin et al., 2014), and thus scale poorly to real-world industrial applications (e.g. data wrangling applications).”