There's a textbook problem that talks about making a binary search dynamic, then analyzing for its amortize cost. However I'm not exactly sure what is the organization scheme of this data structure.
Binary search of a sorted array takes logarithmic search time, but the time to insert a new element is linear in the size of the array. We can improve the time for insertion by keeping several sorted arrays. Specifically, suppose that we wish to support SEARCH and INSERT on a set of $n$ elements. Let $k = lg(n + 1)$, and let the binary representation of $n$ be $\langle n_{k‒1}, n_{k‒2}, \ldots , n_0 \rangle$. We have $k$ sorted arrays $A_0, A_1, \ldots , A_{k‒1}$, where for $i = 0, 1, \ldots , k − 1$, the length of array $A_i$ is $2i$ . Each array is either full or empty, depending on whether $n_i = 1$ or $n_i = 0$, respectively. The total number of elements held in all $k$ arrays is therefore $n$. Although each individual array is sorted, elements in different arrays bear no particular relationship to each other
(Excerpt From: Thomas H. Cormen et al., “Introduction to Algorithms: Third Edition.”)
What does this mean when we have a data structure with several sorted arrays that bear no such relationship? Does it mean that they all must be sorted relative to themselves, but not to the rest? If that's the case, when you try to perform an insert or delete, conceptually, how would you know which array to insert it to or to delete from, and how would it be reshaped?