On list update with locality of reference

We present a comprehensive study of the list update problem with locality of reference.
More specifically, we present a combined theoretical and experimental study in which
the theoretically proven and experimentally observed performance guarantees of algorithms
match  or nearly match.

In the first part of the paper we introduce a new model of locality of reference
that closely captures the concept of runs, representing sequences of requests to the same item.
Using this model we develop refined theoretical analyses of popular list update algorithms.
The second part of the paper is devoted to an extensive experimental study in which we have
tested the algorithms on traces from benchmark libraries. It shows that the theoretical and
experimental bounds differ by just a few percent.

Our new theoretical bounds are substantially lower than those provided by standard competitive analysis.
Another result is that the well-known Move-To-Front strategy exhibits the best performance. Its
refined competitive ratio tends to 1 as the degree of locality in a request sequence increases.
This confirms that Move-To-Front is the method of choice in practice.