activity
20192022
most citedbabble: Learning Better Abstractions with E-Graphs and Anti-Unification

39 citations · 39 across the 3 of their papers we have counts for

collaborators

6 papers

cs.PL202239 cited

babble: Learning Better Abstractions with E-Graphs and Anti-Unification

David Cao, Rose Kunkel, Chandrakana Nandi +3

Library learning compresses a given corpus of programs by extracting common structure from the corpus into reusable library functions. Prior work on library learning suffers from t…

cs.PL2021

Rewrite Rule Inference Using Equality Saturation

Chandrakana Nandi, Max Willsey, Amy Zhu +6

Many compilers, synthesizers, and theorem provers rely on rewrite rules to simplify expressions or prove equivalences. Developing rewrite rules can be difficult: rules may be subtl…

cs.GR2021

Co-Optimization of Design and Fabrication Plans for Carpentry

Haisen Zhao, Max Willsey, Amy Zhu +4

Past work on optimizing fabrication plans given a carpentry design can provide Pareto-optimal plans trading off between material waste, fabrication time, precision, and other consi…

cs.GR2021

Co-Optimization of Design and Fabrication Plans for Carpentry: Supplemental Material

Haisen Zhao, Max Willsey, Amy Zhu +4

Past work on optimizing fabrication plans given a carpentry design can provide Pareto-optimal plans trading off between material waste, fabrication time, precision, and other consi…

cs.PL2020

egg: Fast and Extensible Equality Saturation

Max Willsey, Chandrakana Nandi, Yisu Remy Wang +3

An e-graph efficiently represents a congruence relation over many expressions. Although they were originally developed in the late 1970s for use in automated theorem provers, a mor…

cs.PL2019

Synthesizing Structured CAD Models with Equality Saturation and Inverse Transformations

Chandrakana Nandi, Max Willsey, Adam Anderson +4

Recent program synthesis techniques help users customize CAD models(e.g., for 3D printing) by decompiling low-level triangle meshes to Constructive Solid Geometry (CSG) expressions…