Introduction: While operations rank and select on static bitvectors can be
supported in constant time, lower bounds show that this is impossible when
supporting updates; practical implementations offer O(log n) time for the
operations, which is close to optimal. This is a shame in scenarios where
updates are possible but uncommon. 

Methods: We develop a representation of bitvectors that we call adaptive
dynamic bitvector, which can use (1+e)n bits of space for any constant e and,
if there are queries per update, supports all the operations in O(log(n/q))
amortized time. 

Results: Our experimental results support the theoretical findings, displaying
speedups of orders of magnitude compared to standard dynamic implementations.
We offer a public implementation of our data structure.