Introduction to algorithms
Oblivious data structures: applications to cryptography
STOC '97 Proceedings of the twenty-ninth annual ACM symposium on Theory of computing
Efficiency of a Good But Not Linear Set Union Algorithm
Journal of the ACM (JACM)
Anti-presistence: history independent data structures
STOC '01 Proceedings of the thirty-third annual ACM symposium on Theory of computing
On uniquely represented data strauctures
SFCS '77 Proceedings of the 18th Annual Symposium on Foundations of Computer Science
Dynamizing static algorithms, with applications to dynamic trees and history independence
SODA '04 Proceedings of the fifteenth annual ACM-SIAM symposium on Discrete algorithms
Lower and upper bounds on obtaining history independence
Information and Computation
Programming Languages For Interactive Computing
Electronic Notes in Theoretical Computer Science (ENTCS)
Lower and upper bounds on obtaining history independence
Information and Computation
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We consider history independent data structures as proposed for study by Teague and Naor [3]. In a history independent data structure, nothing can be learned from the representation of the data structure 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 also provide a natural less restrictive definition of strong history independence 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.