KestRel: Relational Verification using E-Graphs for Program Alignment

Many interesting program properties involve the execution of multiple programs, including observational equivalence, noninterference, co-termination, monotonicity, and idempotency. One strategy for verifying such relational properties is to construct and reason about an intermediate program whose correctness implies that the individual programs exhibit those properties. A key challenge in building an intermediate program is finding a good alignment of the original programs. An alignment puts subparts of the original programs into correspondence so that their similarities can be exploited in order to simplify verification. We propose an approach to intermediate program construction that uses e-graphs, equality saturation, and algebraic realignment rules to efficiently represent and build programs amenable to automated verification. A key ingredient of our solution is a novel data-driven extraction technique that uses execution traces of candidate intermediate programs to identify solutions that are semantically well-aligned. We have implemented a relational verification engine based on our proposed approach, called KestRel, and use it to evaluate our approach over a suite of benchmarks taken from the relational verification literature.

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Publication Details

Journal
Proceedings of the ACM on Programming Languages
Published
2025-04-09
DOI
https://doi.org/10.1145/3720474
Citations
1
Primary Topic
Software Testing and Debugging Techniques
Type
article
Field-Weighted Citation Impact
2.31
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article

KestRel: Relational Verification using E-Graphs for Program Alignment

Robert Dickerson, Prasita Mukherjee, Benjamin Delaware
1 citations
Proceedings of the ACM on Programming Languages
Software Testing and Debugging Techniques
2.31
article

KestRel: Relational Verification using E-Graphs for Program Alignment

Robert Dickerson, Prasita Mukherjee, Benjamin Delaware
article en
1 citations

Abstract

Many interesting program properties involve the execution of multiple programs, including observational equivalence, noninterference, co-termination, monotonicity, and idempotency. One strategy for verifying such relational properties is to construct and reason about an intermediate program whose correctness implies that the individual programs exhibit those properties. A key challenge in building an intermediate program is finding a good alignment of the original programs. An alignment puts subparts of the original programs into correspondence so that their similarities can be exploited in order to simplify verification. We propose an approach to intermediate program construction that uses e-graphs, equality saturation, and algebraic realignment rules to efficiently represent and build programs amenable to automated verification. A key ingredient of our solution is a novel data-driven extraction technique that uses execution traces of candidate intermediate programs to identify solutions that are semantically well-aligned. We have implemented a relational verification engine based on our proposed approach, called KestRel, and use it to evaluate our approach over a suite of benchmarks taken from the relational verification literature.

Proceedings of the ACM on Programming LanguagesVol. 9(OOPSLA1)
Purdue University West Lafayette (US)
Openalex Percentile: Top 15%
Software Testing and Debugging Techniques
2.31
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