Adventure of a Lifetime: Extract Method Refactoring for Rust

We present a design and implementation of the automated "Extract Method" refactoring for Rust programs. Even though Extract Method is one of the most well-studied and widely used in practice automated refactorings, featured in all major IDEs for all popular programming languages, implement...

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Vydáno v:Proceedings of ACM on programming languages Ročník 7; číslo OOPSLA2; s. 658 - 685
Hlavní autoři: Thy, Sewen, Costea, Andreea, Gopinathan, Kiran, Sergey, Ilya
Médium: Journal Article
Jazyk:angličtina
Vydáno: New York, NY, USA ACM 16.10.2023
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ISSN:2475-1421, 2475-1421
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Shrnutí:We present a design and implementation of the automated "Extract Method" refactoring for Rust programs. Even though Extract Method is one of the most well-studied and widely used in practice automated refactorings, featured in all major IDEs for all popular programming languages, implementing it soundly for Rust is surprisingly non-trivial due to the restrictions of the Rust's ownership and lifetime-based type system. In this work, we provide a systematic decomposition of the Extract Method refactoring for Rust programs into a series of program transformations, each concerned with satisfying a particular aspect of Rust type safety, eventually producing a well-typed Rust program. Our key discovery is the formulation of Extract Method as a composition of naive function hoisting and a series of automated program repair procedures that progressively make the resulting program "more well-typed" by relying on the corresponding repair oracles. Those oracles include a novel static intra-procedural ownership analysis that infers correct sharing annotations for the extracted function's parameters, and the lifetime checker of rustc, Rust's reference compiler. We implemented our approach in a tool called REM---an automated Extract Method refactoring built on top of IntelliJ IDEA plugin for Rust. Our extensive evaluation on a corpus of changes in five popular Rust projects shows that REM (a) can extract a larger class of feature-rich code fragments into semantically correct functions than other existing refactoring tools, (b) can reproduce method extractions performed manually by human developers in the past, and (c) is efficient enough to be used in interactive development.
ISSN:2475-1421
2475-1421
DOI:10.1145/3622821