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Massachusetts Institute of Technology

Randomized Data Structures: New Perspectives and Hidden Surprises

Abstract

dc:description.abstract

This thesis revisits some of the oldest and most basic questions in the theory of randomized data structures—questions such as: How efficient is a linear probing hash table? How fast can you maintain a sorted array of numbers? How big does a pointer have to be? With the help of new techniques, along with a willingness to look beyond conventional wisdom, we are able to achieve much stronger bounds for each of these questions than were previously thought to be possible. Our results also come with a powerful set of tools that span a wide range of problems and settings. Perhaps the most surprising of these tools is a new paradigm for designing efficient dynamic data structures, in which, by ‘tying our hands behind our back’ (i.e., by artificially restricting ourselves to a special class of privacy-preserving data structures), we are able to circumvent decades-old barriers in time/space efficiency. This technique appears three (completely separate) times in the thesis. Combined, our results overturn a 60-year-old myth on linear-probing hash tables; refute a 30-year-old conjecture and solve a 40-year-old open problem on dynamic sorting; resolve a 20-year-old open problem on dynamic load balancing; settle some of the most basic and fundamental questions from the theory of space-efficient data structures; and answer a 20-year-old question on memory allocation that was left as the central open problem in the first paper on history independence.

Degree

thesis:*
Name thesis:degree_name
Doctoral
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
2023

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Kuszmaul, William
Advisor dc:contributor.advisor
  • Leiserson, Charles E.

Rights

dc:rights
Statement dc:rights
  • In Copyright - Educational Use Permitted
  • Copyright retained by author(s)

Identifiers

dc:identifier.*
Handle dc:identifier.uri
https://hdl.handle.net/1721.1/155068
OAI identifier oai:identifier
oai:dspace.mit.edu:1721.1/155068

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

Kuszmaul, William. Randomized Data Structures: New Perspectives and Hidden Surprises. Massachusetts Institute of Technology, 2023. https://hdl.handle.net/1721.1/155068