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Massachusetts Institute of Technology

Parametric Inversion of Programs

Abstract

dc:description.abstract

Programmers and mathematicians often find themselves in situations where they must solve an inverse problem for a particular function. Solving an inverse problem generally means determining the input that produced a given output. However, this is ambiguous for most functions since the function may have multiple inputs that produce an output. Parametric inversion takes a new approach to solving inverse problems by proposing a method to make a non-injective (many-to-one) function invertible through a parameter. This parameter is used to distinguish between elements in the input space of a function that produced a given output. The existing parametric inversion theory primarily describes inverting mathematical functions. This work extends the theory to encompass inversion of programs. Specifically, we introduce a language, IR, and address problems related to inversion of a simple code block, control flow, and re-use of variables. This includes a practical implementation in Julia that is able to correctly invert a suite of sample programs.

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
2021

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Morejon, David
Advisors dc:contributor.advisor
  • Tavares, Zenna
  • Solar-Lezama, Armando

Rights

dc:rights
Statement dc:rights
  • In Copyright - Educational Use Permitted
  • Copyright MIT

Identifiers

dc:identifier.*
Handle dc:identifier.uri
https://hdl.handle.net/1721.1/138965
OAI identifier oai:identifier
oai:dspace.mit.edu:1721.1/138965

Chain of custody

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

Morejon, David. Parametric Inversion of Programs. Massachusetts Institute of Technology, 2021. https://hdl.handle.net/1721.1/138965