Key-independent optimality
Key-independent optimality is a property of some binary search tree data structures in computer science proposed by John Iacono.[1] Suppose that key-value pairs are stored in a data structure, and that the keys have no relation to their paired values. A data structure has key-independent optimality if, when randomly assigning the keys, the expected performance of the data structure is within a constant factor of the optimal data structure. Key-independent optimality is related to dynamic optimality.
Definitions
There are many binary search tree algorithms that can look up a sequence of keys , where each is a number between and . For each sequence , let be the fastest binary search tree algorithm that looks up the elements in in order. Let be one of the possible permutation of the sequence , chosen at random, where is the th entry of . Let . Iacono defined, for a sequence , that .
A data structure has key-independent optimality if it can lookup the elements in in time .
Relationship with other bounds
Key-independent optimality has been proved to be asymptotically equivalent to the working set theorem. Splay trees are known to have key-independent optimality.
References
- "John Iacono. Key independent optimality. Algorithmica, 42(1):3-10, 2005" (PDF). Archived from the original (PDF) on 2010-06-13.