Characterizing History Independent Data Structures

We consider history independent data structures as proposed for study by Naor and Teague [3]. In a history independent data structure, nothing can be learned from the memory representation of the ucture except for what is available from the abstract data structure. We show that for the most part, strong history independent data structures have canonical representations. We provide a natural alternative definition of strong history independence that is less restrictive than [3] and characterize how it restricts allowable representations. We also give a general formula for creating dynamically resizing history independent data structures and give a related impossibility result.

• Type: Journal
• Year: 2005
• Where: ALGORITHMICA
• Authors: Jason D. Hartline, Edwin S. Hong, Alexander E. Mohr, William R. Pentney, Emily Rocke
• Keywords: ALGORITHMICA 2005, History Independent Data, Independent Data Structures, Strong History