Information Technology Reference
In-Depth Information
15.7 SUMMARY
First, we will look at trends in software development to augur the implications for
the software testing profession. Then, we will look at trends in applications to prog-
nosticate the implications for software testing research.
There are two trends in software development that are of interest to software
testing professionals. The fi rst trend is “get the code out quickly, we can fi x it later.”
With the number of patches and fi xpacks increasing almost exponentially (from once
a month to three times a day!), the authors fi nd the software vendors' response to this
avalanche of software defects to be most interesting and most telling about their tech-
nology priorities. Instead of a reemphasis on quality (fewer bugs
fewer fi xes and
fi xpacks
better quality software), they have chosen to invest development dollars
into faster alerts that a fi x needs to be applied. Entrepreneurs who fully understand
and embrace the lessons learned from the quick-release development technology
model will have a real chance to offer cost-effective software with signifi cantly bet-
ter quality (fewer patches and fi xpacks) to a market hungry for good-quality soft-
ware. If they succeed, then the software testing profession will really take wings.
The software development challenges to extend the current applications into
the wireless environment have been enormous. The plethora of viable devices run-
ning a wide range of successful applications attests to the software development
profession's creativeness and persistence.
The next quantum leap in software development after wireless applications is
autonomic computing. We believe that successfully testing autonomic systems will
require a testing paradigm shift to validate the feature of autonomic systems not
present in other software, namely the ability to “self-diagnose.”
There are a number of articles in the Artifi cial Intelligence research arena that
propose how software “learning” might occur. No overtly successful efforts have
been reported to date. Showing a bit of optimism in the hardware and software devel-
opers' genius, we expect that “learning” computers will come into existence. At this
time, we can only wonder at the testing challenges posed by software that “learns.”
KEY CONCEPTS
“Get the code out quick-
ly, we can fix it later”
Software development
technology model
Software development
business model
Testing for and in hostile
environments
Software that is “self-
healing”
Software that “learns”
Wireless environment
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