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https://doi.org/10.1145/345348...
Article . 2021 . Peer-reviewed
License: CC BY
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SyRust: automatic testing of Rust libraries with semantic-aware program synthesis

Authors: Yoshiki Takashima; Ruben Martins; Limin Jia 0001; Corina S. Pasareanu;

SyRust: automatic testing of Rust libraries with semantic-aware program synthesis

Abstract

Rust’s type system ensures the safety of Rust programs; however, programmers can side-step some of the strict typing rules by using the unsafe keyword. A common use of unsafe Rust is by libraries. Bugs in these libraries undermine the safety of the entire Rust program. Therefore, it is crucial to thoroughly test library APIs to rule out bugs. Unfortunately, such testing relies on programmers to manually construct test cases, which is an inefficient and ineffective process. The goal of this paper is to develop a methodology for automatically generating Rust programs to effectively test Rust library APIs. The main challenge is to synthesize well-typed Rust programs to account for proper chaining of API calls and Rust’s ownership type system and polymorphic types. We develop a program synthesis technique for Rust library API testing, which relies on a novel logical encoding of typing constraints from Rust’s ownership type system. We implement SyRust, a testing framework for Rust libraries that automatically synthesizes semantically valid test cases. Our experiments on 30 popular open-source Rust libraries found 4 new bugs.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
24
Top 10%
Top 10%
Top 10%
hybrid