  With the growing number of qubits of quantum information processing devices,
the task of fully characterizing these processors becomes increasingly
unfeasible. From a practical perspective, one wants to find possible errors in
the functioning of the device as quickly as possible, or otherwise establish
its correct functioning with high confidence. In response to these challenges,
we propose a pattern-based approach inspired by classical memory testing
algorithms to evaluate the functionality of a quantum memory, based on
plausible failure mechanisms. We demonstrate the method's capability to extract
pattern dependencies of important qubit characteristics, such as $T_1$ and
$T_2$ times, and to identify and analyze interactions between adjacent qubits.
Additionally, our approach enables the detection of different types of
crosstalk effects and of signatures indicating non-Markovian dynamics in
individual qubits.
