Staged parser combinators for efficient data processing

Jonnalagedda, Manohar; Coppey, Thierry; Stucki, Sandro; Rompf, Tiark; Odersky, Martin

doi:10.1145/2714064.2660241

Cited by 5 publications

(2 citation statements)

References 30 publications

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“…Staged parser combinators were pioneered in Scala using Light-weight Modular Staging (LMS) [Jonnalagedda et al 2014]. This work illustrates how to add staging annotations to remove the abstraction overheads of the combinators.…”

Section: Nandlangmentioning

confidence: 99%

Staged selective parser combinators

Willis

Pickering

2020

Proc. ACM Program. Lang.

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Parser combinators are a middle ground between the fine control of hand-rolled parsers and the high-level almost grammar-like appearance of parsers created via parser generators. They also promote a cleaner, compositional design for parsers. Historically, however, they cannot match the performance of their counterparts. This paper describes how to compile parser combinators into parsers of handwritten quality. This is done by leveraging the static information present in the grammar by representing it as a tree. However, in order to exploit this information, it will be necessary to drop support for monadic computation since this generates dynamic structure. Selective functors can help recover lost functionality in the absence of monads, and the parser tree can be partially evaluated with staging. This is implemented in a library called Parsley.

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Section: Nandlangmentioning

confidence: 99%

Staged selective parser combinators

Willis

Pickering

2020

Proc. ACM Program. Lang.

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“…We adapt the work on staged parser combinators [43,42] to generate C code instead of Scala code. After this initial port (which amounts to switching the code generation backend of the LMS framework), with minimal additional work, we further ensure that parser requests per second (baseline) nginx (0.94 ± 0.01) • 10 6 (our) staged verified (1.00 ± 0.01) • 10 6 Figure 7.…”

Section: Http Parsermentioning

confidence: 99%

LMS-Verify: abstraction without regret for verified systems programming

Amin

Rompf

2017

SIGPLAN Not.

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Performance critical software is almost always developed in C, as programmers do not trust high-level languages to deliver the same reliable performance. This is bad because low-level code in unsafe languages attracts security vulnerabilities and because development is far less productive, with PL advances mostly lost on programmers operating under tight performance constraints. Highlevel languages provide memory safety out of the box, but they are deemed too slow and unpredictable for serious system software. Recent years have seen a surge in staging and generative programming: the key idea is to use high-level languages and their abstraction power as glorified macro systems to compose code fragments in first-order, potentially domain-specific, intermediate languages, from which fast C can be emitted. But what about security? Since the end result is still C code, the safety guarantees of the high-level host language are lost. In this paper, we extend this generative approach to emit ACSL specifications along with C code. We demonstrate that staging achieves "abstraction without regret" for verification: we show how high-level programming models, in particular higher-order composable contracts from dynamic languages, can be used at generation time to compose and generate first-order specifications that can be statically checked by existing tools. We also show how type classes can automatically attach invariants to data types, reducing the need for repetitive manual annotations. We evaluate our system on several case studies that varyingly exercise verification of memory safety, overflow safety, and functional correctness. We feature an HTTP parser that is (1) fast (2) high-level: implemented using staged parser combinators (3) secure: with verified memory safety. This result is significant, as input parsing is a key attack vector, and vulnerabilities related to HTTP parsing have been documented in all widely-used web servers.

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Multi-stage programming in the large with staged classes

Parreaux

Shaikhha

2020

Proceedings of the 19th ACM SIGPLAN International Conference on Generative Programming: Concepts and Experiences

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Staged parser combinators for efficient data processing

Cited by 5 publications

References 30 publications

Staged selective parser combinators

Staged selective parser combinators

LMS-Verify: abstraction without regret for verified systems programming

Multi-stage programming in the large with staged classes

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