Semantic code search via equational reasoning

Premtoon, Varot; Koppel, James; Solar-Lezama, Armando

doi:10.1145/3385412.3386001

Cited by 44 publications

(25 citation statements)

References 55 publications

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“…Originally developed for and still used in the heart of theorem provers [De Moura and Bjùrner 2008;Detlefs et al 2005;], e-graphs have also been used to power a program optimization technique called equality saturation [Joshi et al 2002;Nandi et al 2020;Panchekha et al 2015;Premtoon et al 2020;Stepp et al 2011;Tate et al 2009;Wang et al 2020].…”

Section: E-graphsmentioning

confidence: 99%

“…It uses a global profitability heuristic for extraction which is implemented using a pseudo-boolean solver. Recently, [Premtoon et al 2020] uses PEGs for code search. egg can support PEGs as a user-defined language, and thus their technique could be ported.…”

Section: Related Workmentioning

confidence: 99%

“…At a high level, e-graphs Nieuwenhuis and Oliveras 2005] extend union-find [Tarjan 1975] to compactly represent equivalence classes of expressions while maintaining a key invariant: the equivalence relation is closed under congruence. 1 Over the past decade, several projects have repurposed e-graphs to implement state-of-the-art, rewrite-driven compiler optimizations and program synthesizers using a technique known as equality saturation [Joshi et al 2002;Nandi et al 2020;Panchekha et al 2015;Premtoon et al 2020;Stepp et al 2011;Tate et al 2009;Wang et al 2020]. Given an input program , equality saturation constructs an e-graph that represents a large set of programs equivalent to , and then extracts the łbestž program from .…”

Section: Introductionmentioning

confidence: 99%

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egg: Fast and extensible equality saturation

Willsey

Nandi

Wang

et al. 2021

Proc. ACM Program. Lang.

104

121

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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 more recent technique known as equality saturation repurposes e-graphs to implement state-of-the-art, rewrite-driven compiler optimizations and program synthesizers. However, e-graphs remain unspecialized for this newer use case. Equality saturation workloads exhibit distinct characteristics and often require ad-hoc e-graph extensions to incorporate transformations beyond purely syntactic rewrites. This work contributes two techniques that make e-graphs fast and extensible, specializing them to equality saturation. A new amortized invariant restoration technique called rebuilding takes advantage of equality saturation's distinct workload, providing asymptotic speedups over current techniques in practice. A general mechanism called e-class analyses integrates domain-specific analyses into the e-graph, reducing the need for ad hoc manipulation. We implemented these techniques in a new open-source library called egg. Our case studies on three previously published applications of equality saturation highlight how egg's performance and flexibility enable state-of-the-art results across diverse domains.

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Section: E-graphsmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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egg: Fast and extensible equality saturation

Willsey

Nandi

Wang

et al. 2021

Proc. ACM Program. Lang.

104

121

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show abstract

“…This particular type of graphs has been used in the past in many automated theorem provers [13]. Over the past decades, many projects have repurposed e-graphs to achieve excellent results in compiler optimization tasks based on source code rewriting through an algorithm called equality saturation ( [53,25,42,36,44,50,57]). Many of these approaches, though, suffer from the two-language problem.…”

Section: Chapter 2 An Advanced Framework For Expression Rewriting In ...mentioning

confidence: 99%

Automated Code Optimization with E-Graphs

Cheli¹

2021

Preprint

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“…For example, Gu et al [18] and Cambronero et al [19] use neural networks to produce code and natural language embeddings that can be used to search a large corpus of methods given a natural language description of the desired functionality. Premtoon et al's Yogo [31] system represents a code fragment using its corresponding dataflow graph, as well as rewrites of the graph based on a set of rules, and perform queries as searches over the graphs. David and Yahav [32] also use a rewriting-based strategy to enable code search, but their system is focused on searching for function usage in a corpus of executables.…”

Section: Related Workmentioning

confidence: 99%

Synthesizing replacement classes

Samak

Kim

Rinard

2019

Proc. ACM Program. Lang.

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We present a new technique for automatically synthesizing replacement classes. The technique starts with an original class O and a potential replacement class R, then uses R to synthesize a new class that implements the same interface and provides the same functionality as O. Critically, our technique works with a synthesized inter-class equivalence predicate between the states of O and R. It uses this predicate to ensure that original and synthesized methods leave corresponding O and R objects in equivalent states. The predicate therefore enables the technique to synthesize individual replacement methods in isolation while still obtaining a replacement class that leaves the original and replacement objects in equivalent states after arbitrarily long method invocation sequences. We have implemented the technique as part of a tool, named M , and evaluated it using open-source Java classes. The results highlight the e ectiveness of M in synthesizing replacement classes. CCS Concepts: • Software and its engineering → Programming by example; Object oriented frameworks.

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Semantic code search via equational reasoning

Cited by 44 publications

References 55 publications

egg: Fast and extensible equality saturation

egg: Fast and extensible equality saturation

Automated Code Optimization with E-Graphs

Synthesizing replacement classes

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