what people do manually with the
automated version of the same,” said
Kacek, “…once it works.” Bell added:
“While the management team understood the advantages of test automation and we all have an engineering
background, we had to keep asking:
how to get buy-in?” “Our driver was to
find creative ways for our customers to
make decisions, what we call ‘speed to
value’” Kacek asserted.
some steps
Cerny described a few of the steps they
took at SmartSignal to build their automated test system:
˲ ˲Build to virtual machines and
virtualization to isolate device dependence;
˲ ˲ Start simply using comma delimited scripts and hierarchical tree data
views;
˲ ˲ Build up a name directory of functions;
˲ ˲ Separate global (run in any environment) from local variables;
˲ ˲Keep object recognition out of
scripts, use both static and dynamic
binding; and
˲ ˲ Initially automate within the development team to prove the concept
before moving to production.
test knowledge is
system knowledge
These steps are typical engineering
design actions anyone might take in
automating testing or, indeed, in automating any process or any system. But
in this case there was a difference.
“Asset configuration is a big issue
in the power industry.” Cerny said in
his presentation at Quest. “Imagine
setting up a power station: what equip-
ment should go where? Which pumps
are used and connected to which other
equipment? Where are sensors to be
placed? What is the ‘best’ configura-
tion of equipment that will most likely
reduce the overall failure rate of the
plant?”
The analytics test system is designed
to prove the analytical system itself
works. To do this, the test system must
be set up (automatically, of course) to
the appropriate target system configu-
ration. The normal test function is
meant to show that the analytical sys-
tem will work as built for that particu-
lar target system. But what if we turn
the knowledge of
how to set up the test
system is also the
knowledge of how
to set up the target
production system.
this around? What if we use our testing
capability to find out what configuration would show the lowest likely failure
rate Doing this allows field engineers
and power plant designers to model
different configurations of systems for
least likelihood of failure before they
actually build and install them.
The knowledge in the test system
is the same as the knowledge in the
target system. The knowledge of how
to set up the test system is also the
knowledge of how to set up the target
production system. Automating this
knowledge allows simulation of a system before it is built.
a Really Good idea
This is what Jason Kalich and the panel
at Quest were looking for. Automating
the test system at SmartSignal ended
up being not simply about speeding
things up a bit, making the testers’
lives easier, or saving a few dollars. It
was not just about cranking through a
few more tests in limited time or reducing test setup, analysis, and reporting
time. It became something different—
it became a configuration simulator
and that’s a new product.
If we automate knowledge in the
right way, even internal software process knowledge, it can be used in
many different ways and it can even be
used to create new functionality and
new products that our customers will
pay for.
Now that’s a good idea.
Reference
1. Humphrey, W. Managing the Software Process.
Prentice Hall, New York, 1989, 54.
Phillip G. Armour ( armour@corvusintl.com) is a senior
consultant at Corvus International Inc., Deer Park, IL.
Copyright held by author.
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