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Massachusetts Institute of Technology

Extracting and optimizing low-level bytecode from high-level verified Coq

Abstract

dc:description.abstract

This document is an MEng thesis presenting MCQC, a compiler for extracting verified systems programs to low-level assembly, with no Runtime or Garbage Collection requirements and an emphasis on performance. MCQC targets the Gallina functional language used in the Coq proof assistant. MCQC translates pure and recursive functions into C++17, while compiling monadic effectful functions to imperative C++ system calls. With a series of memory and performance optimizations, MCQC combines verifiability with memory and runtime performance. By handling effectful and pure functions MCQC can generate executable code directly from Gallina and link it with trusted code, reducing the effort of implementing and executing verified systems.

Degree

thesis:*
Name thesis:degree_name
Master
Department dc:contributor.department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Grantor dc:publisher
Massachusetts Institute of Technology
Year dc:date.issued
2019

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Ioannidis, Eleftherios Ioannis.
Advisor dc:contributor.advisor
  • Frans Kaashoek and Nickolai Zeldovich.

Subjects

dc:subject × 1

Rights

dc:rights
Statement dc:rights
  • MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission.
Language dc:language.iso
eng

Identifiers

dc:identifier.*
Handle dc:identifier.uri
https://hdl.handle.net/1721.1/121675
OAI identifier oai:identifier
oai:dspace.mit.edu:1721.1/121675

Chain of custody

source
Harvested from
MIT
Base URL
dspace.mit.edu/oai/request
Last updated
2026-07-22
Source record
OAI-PMH GetRecord
citation

Ioannidis, Eleftherios Ioannis.. Extracting and optimizing low-level bytecode from high-level verified Coq. Massachusetts Institute of Technology, 2019. https://hdl.handle.net/1721.1/121675