  Risk-limiting audits (RLAs) can use information about which ballot cards
contain which contests (card-style data, CSD) to ensure that each contest
receives adequate scrutiny, without examining more cards than necessary. RLAs
using CSD in this way can be substantially more efficient than RLAs that sample
indiscriminately from all cast cards. We describe an open-source Python
implementation of RLAs using CSD for the Hart InterCivic Verity voting system
and the Dominion Democracy Suite(R) voting system. The software is demonstrated
using all 181 contests in the 2020 general election and all 214 contests in the
2022 general election in Orange County, CA, USA, the fifth-largest election
jurisdiction in the U.S., with over 1.8 million active voters. (Orange County
uses the Hart Verity system.) To audit the 181 contests in 2020 to a risk limit
of 5% without using CSD would have required a complete hand tally of all
3,094,308 cast ballot cards. With CSD, the estimated sample size is about
20,100 cards, 0.65% of the cards cast--including one tied contest that required
a complete hand count. To audit the 214 contests in 2022 to a risk limit of 5%
without using CSD would have required a complete hand tally of all 1,989,416
cast cards. With CSD, the estimated sample size is about 62,250 ballots, 3.1%
of cards cast--including three contests with margins below 0.1% and 9 with
margins below 0.5%.
