A benefit of this method is that its conceptual model is simple and familiar. That is, a person knows what they have just done and can thus predict if an item will be on the history list. We will use this value as a benchmark to contrast other methods. While this type of list does not show the exact sequence of URLs visited by the user, it still presents a clear conceptual model, and we expect that the user can easily understand how the list contents are ordered. The striking differences between these three recency orders are illustrated by the plots in Figure 13 .
Frequency has other problems, as already mentioned.
Users may find it more difficult to predict which pages would appear on a frequency-ordered list beyond the two or three that they visit the most. As well, frequency ordering suffers instability when few items are on the history list, and excessive inertia when the list is long. Still, frequency could be applied to a few key URLs, possibly used as an auxiliary method in conjunction with another history mechanism that gives better overall performance. In addition, users may have more difficulty understanding how this method works, as they need to know what a 'direct access URL' is to grasp the way the history list is organized. In conclusion, our analysis of conditioning methods shows that several methods improve upon the effectiveness of current stack-based history mechanisms.