Testing Challenges: Legacy Systems, Modernization and the Path to AI
Reading time: 3 minutes
As a Quality professional, it is a daunting task to keep up with the changes in technology. The need to know new programming languages, be aware of the latest-and-greatest testing tools, and know how to deliver applications faster in our daily practice are just some of the challenges we face. In addition, many organizations are focusing on AI and Machine Learning as a way to modernize their business.
One way we can prepare for the future of our Quality practice and the rapid tech advancements is to have meaningful conversations about technology trends.
Joining us on the panel was Bond Brand Loyalty QA Manager and Strategist, Humera Iqbal, Morneau Shepell QA Manager, Lois Keating and API Automation Quality Engineer, Poorva Chaturvedi. Our moderator Puneet Randhawa, QA Manager from CaseWare, engaged the panel in a thought-provoking discussion on the current industry trends and the anticipated future of the field of testing.
Top three testing challenges
Each member of the panel shared their experiences and perspectives on testing large complex integrated systems, to implementing automation for continuous testing. The pressure to learn new skills and hone our testing techniques is always there.
Legacy systems aren’t going away
Legacy systems, such as warehouses or banking databases, may be considered outdated, but are essential to keep things running smoothly. Businesses that use large enterprise systems are very cautious about changing to a lighter version, because they are satisfied with what their current software does. The vast majority of their end users just want to get the job done—They don’t need all the bells and whistles that a new and innovative solution could bring.
Some of the difficulties we face when testing legacy systems are understanding the complexity of the application and the possibility that when defects are found and fixed, it could have impact in unplanned ways. The inability to find a faulty calculation in an accounting system could affect the accuracy of a corporation’s tax submission.
Testing at the speed of Agile is unavoidable
Modernization is the process of change and the effects that change can bring. We’ve all been a part of the Agile movement for quite a while now. When companies want to test at the speed of Agile, and bring their systems into more modern processes, testing needs to be smart. Automation is necessary for continuous integration and delivery to be successful. We know that even if it scares us, we need to learn how to contribute to automation strategies.
AI can change the way we test
How does AI affect the way we test? Does it mean our testing techniques need to change?
What we are testing, how we test, and when we test, is significantly different for AI projects. The panelists shared that the volume of data available, the task of obtaining real data from production, and having access to data that has value are significant factors for positive testing outcomes. Not only are we testing AI-based systems, we must also explore ways to use AI to provide more value to the user tests that we execute.
To learn more about the impact of AI, check out How to actually use AI for your business.
We must adapt
As testers and quality advocates, we continue to expand our skills, adapt our testing strategies for legacy products, support modernization and agile delivery, and understand how AI can change the way we test. We are arming ourselves with a better understanding of increasingly complex technologies.
Women Who Test Toronto
As the head of the Toronto Chapter of Women Who Test, I’m working to grow our community. We have 155 members, and meet regularly for panel talks, Q&A and networking events. Join us to break down barriers for women in the software industry, and get to know other Women Who Test at the next event.