  AWAIRE is one of two extant methods for conducting risk-limiting audits of
instant-runoff voting (IRV) elections. In principle AWAIRE can audit IRV
contests with any number of candidates, but the original implementation
incurred memory and computation costs that grew superexponentially with the
number of candidates. This paper improves the algorithmic implementation of
AWAIRE in three ways that make it practical to audit IRV contests with 55
candidates, compared to the previous 6 candidates. First, rather than trying
from the start to rule out all candidate elimination orders that produce a
different winner, the algorithm starts by considering only the final round,
testing statistically whether each candidate could have won that round. For
those candidates who cannot be ruled out at that stage, it expands to consider
earlier and earlier rounds until either it provides strong evidence that the
reported winner really won or a full hand count is conducted, revealing who
really won. Second, it tests a richer collection of conditions, some of which
can rule out many elimination orders at once. Third, it exploits relationships
among those conditions, allowing it to abandon testing those that are unlikely
to help. We provide real-world examples with up to 36 candidates and synthetic
examples with up to 55 candidates, showing how audit sample size depends on the
margins and on the tuning parameters. An open-source Python implementation is
publicly available.
