  In the era of the SKA precursors, telescopes are producing deeper, larger
images of the sky on increasingly small time-scales. The greater size and
volume of images place an increased demand on the software that we use to
create catalogues, and so our source finding algorithms need to evolve
accordingly. In this paper we discuss some of the logistical and technical
challenges that result from the increased size and volume of images that are to
be analysed, and demonstrate how the Aegean source finding package has evolved
to address these challenges. In particular we address the issues of source
finding on spatially correlated data, and on images in which the background,
noise, and point spread function, vary across the sky. We also introduce the
concept of forced or priorized fitting.
