  The Australian Square Kilometre Array Pathfinder (ASKAP) presents a number of
challenges in the area of source finding and cataloguing. The data rates and
image sizes are very large, and require automated processing in a
high-performance computing environment. This requires development of new tools,
that are able to operate in such an environment and can reliably handle large
datasets. These tools must also be able to accommodate the different types of
observations ASKAP will make: continuum imaging, spectral-line imaging,
transient imaging. The ASKAP project has developed a source-finder known as
Selavy, built upon the Duchamp source-finder (Whiting 2012). Selavy
incorporates a number of new features, which we describe here.
  Since distributed processing of large images and cubes will be essential, we
describe the algorithms used to distribute the data, find an appropriate
threshold and search to that threshold and form the final source catalogue. We
describe the algorithm used to define a varying threshold that responds to the
local, rather than global, noise conditions, and provide examples of its use.
And we discuss the approach used to apply two-dimensional fits to detected
sources, enabling more accurate parameterisation. These new features are
compared for timing performance, where we show that their impact on the
pipeline processing will be small, providing room for enhanced algorithms.
  We also discuss the development process for ASKAP source finding software. By
the time of ASKAP operations, the ASKAP science community, through the Survey
Science Projects, will have contributed important elements of the source
finding pipeline, and the mechanisms in which this will be done are presented.
