2026-09-19T00:37:19Zhttps://dspace.mit.edu/server/oai/requestoai:dspace.mit.edu:1721.1/1433742022-06-16T03:08:25Zcom_1721.1_7582com_1721.1_7581col_1721.1_131022
Chlipala, Adam
Pit-Claudel, Clément
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
2022-06-15T13:16:16Z
2022-06-15T13:16:16Z
2022-02
2022-03-04T20:47:52.443Z
https://hdl.handle.net/1721.1/143374
https://orcid.org/0000-0002-1900-3901
Purely functional programs verified using interactive theorem provers typically need to be translated to run: either by extracting them to a similar language (like Coq to OCaml) or by proving them equivalent to deeply embedded implementations (like C programs). Traditionally, the first approach is automated but produces unverified programs with average performance, and the second approach is manual but produces verified, high-performance programs.
This thesis shows how to recast program extraction as a proof-search problem to automatically derive correct-by-construction, high-performance code from shallowly embedded functional programs. It introduces a unifying framework, relational compilation, to capture and extend recent developments in program extraction, with a focus on modularity and sound extensibility. To demonstrate the value of this approach, it then presents Rupicola, a relational compiler-construction toolkit designed to extract fast, verified, idiomatic low-level code from annotated functional models.
The originality of this approach lies in its combination of foundational proofs, extensibility, and performance, backed by an unconventional take on compiler extensions: unlike traditional compilers, Rupicola generates good code not because of clever built-in optimizations, but because it allows expert users to plug in domain- and sometimes program-specific extensions that allow them to generate exactly the low-level code that they want. This thesis demonstrates the benefits of this approach through case studies and performance benchmarks that highlight how easy Rupicola makes it to create domain-specific compilers that generate code with performance comparable to that of handwritten C programs.
Ph.D.
Massachusetts Institute of Technology
In Copyright - Educational Use Permitted
Copyright MIT
http://rightsstatements.org/page/InC-EDU/1.0/
Relational compilation: Functional-to-imperative code generation for performance-critical applications
Thesis
application/pdf
Doctoral
Doctor of Philosophy
Publication
unknown
unknown
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<Abstract>Purely functional programs verified using interactive theorem provers typically need to be translated to run: either by extracting them to a similar language (like Coq to OCaml) or by proving them equivalent to deeply embedded implementations (like C programs). Traditionally, the first approach is automated but produces unverified programs with average performance, and the second approach is manual but produces verified, high-performance programs.
This thesis shows how to recast program extraction as a proof-search problem to automatically derive correct-by-construction, high-performance code from shallowly embedded functional programs. It introduces a unifying framework, relational compilation, to capture and extend recent developments in program extraction, with a focus on modularity and sound extensibility. To demonstrate the value of this approach, it then presents Rupicola, a relational compiler-construction toolkit designed to extract fast, verified, idiomatic low-level code from annotated functional models.
The originality of this approach lies in its combination of foundational proofs, extensibility, and performance, backed by an unconventional take on compiler extensions: unlike traditional compilers, Rupicola generates good code not because of clever built-in optimizations, but because it allows expert users to plug in domain- and sometimes program-specific extensions that allow them to generate exactly the low-level code that they want. This thesis demonstrates the benefits of this approach through case studies and performance benchmarks that highlight how easy Rupicola makes it to create domain-specific compilers that generate code with performance comparable to that of handwritten C programs.</Abstract>
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