How will the Test Automation strategy see a change in 2019?
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| Test Automation Strategy |
The global digital landscape has
undergone a change in its dynamics. On one side, there is the advent of cutting
edge technologies enhancing the quality, capacity and functionality of
software. On the other side, there is an increased demand for software to be
delivered off the shelves quickly. Furthermore, there is an additional scare of
cyber security enveloping the entire digital landscape. Overall, businesses are
caught up between delivering quick software products or services to the market
and ensuring the ones delivered are qualitatively superior and secure. Can the
two requirements be compatible and achievable? Yes, if a rigorous software
testing methodology is followed in the mould of Agile-DevOps.
How can a test automation strategy be
of help?
The growing complexity of software
involving advanced technologies like AI and machine learning, IoT, virtual
reality, big data, and cloud etc. has led to a paradigm shift in testing. It is
no longer about manual testing alone but combining the same with automation
testing. However, building a test automation strategy is not simple, for it
requires taking into consideration a lot of factors. These can relate to the
robustness of scripts, the compatibility of scripts across devices and
platforms, or their ability to virtualize among others. Moreover, as the DevOps
paradigm has become the new normal in software testing, engaging software test
automation services has become important to ensure Continuous Integration and
Delivery (CI/CD).
Let us find out how the year 2019
will turn out to be as far as delivering test automation solutions is
concerned.
Trends in test automation solutions
for the year 2019
# Increased use of AI in test
automation and analysis: Enterprises often get bogged down in
identifying the sources of bugs in software codes. They fail to determine if
the bugs have ingressed due to system or coding issues. Test automation experts are hard pressed to find the sources of
glitches leading to a delay in meeting the delivery schedules. This is where
Artificial Intelligence (AI) and Machine Learning (ML) can play their part. For
example, AI/ML can run through billions of lines of coding and analyze as to
which pattern is out of the ordinary. They can even predict the areas where
glitches are likely to sneak-in by mining and analysing the historical data. AI
can provide robust data analytics vis-a-vis the opinions of test automation experts based
on experience. The year will see the use of QA automation testing tools that
incorporate elements of AI/ML to analyze tests such as regression, performance,
functional, usability etc. The year shall see the exact number of tests to be
executed for validating a module.
# Script maintenance will get easy? The
biggest challenge for test automation experts is to create and maintain a test
script beyond its usage date, browser, and operating system. Test scripts can
fail if the application under test is changed without updating the scripts.
This is where AI helps by updating the scripts whenever it detects any change
in the application or its functionality. The year will see new test automation solutions undergoing
self correction as and when there is a change in the user interface.
Moreover, everytime a testing
exercise is conducted, the automation tool captures a humongous quantity of
data comprising HTML data, images, and browser info among others. The data is
then fed into the algorithm and incorporated by the tool as the normal
application behaviour. Once there are deviations from the normal behaviour, the
tool can correctly flag them thereby helping testers/builders to eliminate the
glitch(es). Thus, AI/ML based tools can heal themselves and save testers from
the drudgery of conducting complex regression tests.
#Is Selenium passe? Do other
automation tools come into play?: In the last few years, Selenium has
acquired the de facto status of being the most popular automation testing tool.
However, test teams can adopt tools that are right for the testing job such as
Cypress.io, TestCafe etc and the ones that meet the team’s styles and needs.
Since the year will see more of AI based automation, there is a dire need to
use AI based open source test tools other than Selenium.
Conclusion
With continuous testing becoming an
integral part of software testing, the automated
testing strategy needs to undergo a change to meet the testing
objectives of the day. The year 2019 will see an increased use of AI and ML in
analysing and executing complex test cases. The ultimate result will be a
better software that delivers customer delight.
This Article is originally published at Toolbox, How
will your Test Automation strategy change this year?
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