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Home » Blogs » Automation Killed QA – It’s Time to Deal With It

Automation Killed QA – It’s Time to Deal With It

By: Ron DeCanio on January 27, 2017 Leave a Comment

Quality assurance (QA) had a good run.

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From the time it was considered an afterthought by organizations and software vendors alike to the era of massive outsourcing contracts, followed by significant vendor investments in related tooling, and, finally, its recognition as a critical success factor among high-performing organizations, quality has evolved to become even more important than functionality to end users.

Customer experience, today, is defined by speed and quality above all else. Namely, can I access the information and products that I want in the blink of an eye and get expected feedback based on input? As a result, customer experience has also shifted: It’s all about application experience, not the friendliness of a checkout cashier or sales/service rep.

With this massive shift toward customer experience platforms (think omni-channel) and increasingly lofty expectations, the operative question becomes, How are we enabling velocity in our testing practices to ensure the highest quality while keeping up?

We’ve tried everything from outsourcing to insourcing, investing in tooling, investing in people and even building testing architecture teams to oversee the automation, quality and consistency of testing results. Roughly seven years ago, my top priority for testing teams was to automate 30 percent of our tests. Today, if you are not 100 percent automated, or close to it, you are severely lagging in output.

But what’s next? What if I’ve automated all of my tests and my manual testers have been replaced with automation engineers, but I’m still having quality issues and being perceived as a bottleneck?

The answer is simple. Automate everything.

Makes sense, right? Isn’t everyone telling you that? But what are we defining as “everything” from a testing perspective? Therein lies the problem; we are thinking about testing as its own factory within the larger software development life cycle.

While we believe we are changing this perception by going agile and moving most QA functions into scrum teams, the reality is we still look at testing as a standalone function. Centralized or decentralized, this is the case, and we need to think differently.

Automating for quality begins with defining requirements. How am I ensuring that I’m covering all cases? How do I ensure I’m translating the business requirements properly? These questions, the time it takes to answer them and the risk of human miscalculation all impact quality and velocity.

We must start our automation for quality at the beginning, during establishment of business requirements.

Let me introduce you to next-generation QA. Intelligent “continuous testing” platforms are replacing humans for testing, automating tests, creating data and building test cases. These platforms are able to translate model-based business requirements into complete automation—test cases, test data and test script automation.

Orchestration across your software development life cycle creates your environments, lays down your test data, deploys your software, runs your test scripts and reports results. No more human error, no costly resources and guaranteed test coverage that ensures quality.

Integrating your existing automation around continuous integration, portfolio management reporting, and execution reporting to this framework now gives you the ability to report and automate your ideas all the way through to outcomes.

Early adopters are already doing this. QA as a functional organization is gone. If you aren’t already automating to this end, you are severely behind.

Questions?  Comments?  Perspective?  Have at it in the comments below.

— Ron DeCanio

Filed Under: Blogs, Continuous Delivery Tagged With: Automated testing, automation, CD, code quality, continuous delivery, continuous testing, culture, devops, devops adoption, devops culture, devops process, enterprise devops, quality, Quality Assurance, test data, test data management

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