  Large-scale, fault-tolerant quantum computations will be enabled by quantum
error-correcting codes (QECC). This work presents the first systematic
technique to test the accuracy and effectiveness of different QECC decoding
schemes by comparing a look-up table decoder to solutions generated using
algorithmic decoders. Specifically, we examine the results of
minimum-weight-perfect-matching and belief-propagation decoders against
exhaustive look-up tables for surface codes up to distance seven and categorise
where errors are accurately corrected in both decoding schemes. While our
results are preliminary, we show that significant quantitative results can be
generated, comparing how actual error channels are successfully or
unsuccessfully decoded. We show that different decoding schemes perform very
differently under the same QECC scheme and error model, and detail how decoders
can be tested and classified with respect to errors that are successfully
decodable. This work paves the way to the data driven tuning of decoder
ensembles and will enable tailored design of hybrid decoding schemes that allow
for real-time decoding, while maintaining the high theoretical thresholds
allowed by specific quantum error correction codes.
