Accelerating Quality for Digital Enterprises

2017 Automated Testing Trends – What We Should Be Looking Out For

We recently wrapped up 2016 as the year of digital quality. We talked about how digital transformation is going bring even more drastic shifts in how we do software delivery. And how your organization needs to brace up to bring agile models to work in order to release higher quality software faster through automated testing.

A key trend that will sweep over to bring economies of scale, speed and intelligence will be automated testing followed by AI. We’ve seen a massive movement from manual to automation in the last couple of years, as manual could not handle this scale of change. Manual testing matrices are too big to approximate manually, take a long time, and are very complex to handle for applications like Uber, Snapchat, and Twitter that are scaling at the speed of light.

Manual testing might not be able to meet the demand of a plethora of web browsers, devices, operating systems, screen resolutions, and responsive designs. And to deliver quality at the speed of digital, there will be a need to bring in the right automated testing initiatives.

But automation is vast and there are several nuances to it. Which nuances will be more pronounced in 2017? Here are a few premonitions based on our overall customer engagements this year.

  1. DevOps and Closing of the Chasm between Development and Testing

 DevOps redefined the paradigms some more this year by bringing development and testing groups together. These teams started working together as part of a single unified DevOps group. The shift-left movement brought in the culture of testing early and often rather than waiting. This also meant that the quality teams would have to plug themselves in earlier in the game.

Recently we did a webinar on how every organization needs to imbibe an agile DNA mentality by integrating shift-left techniques and continuous monitoring methodologies. 2017 is going to see a lot of more fusing of development with operations and testing to become one team.

Test Automation, DevOps, Artificial Intelligence, Machine Learning, IOT testing,

  1. Virtual Test Environments with DevOps and Digital Transformation

With DevOps taking over due to digital transformation, there’s a need for test environments to evolve and take larger roles. Overall, there’s an increasing trend for enhancing the flexibility and feasibility of these test environments across all areas of testing. The World Quality Report states that 2016 saw enterprises struggling with provisioning test environments with the increased adoption of agile and DevOps.

It would be safe to say that this area is still somewhat green but we will see a lot more evolution here especially with testing in a virtual test environment. Currently, however, a lot more of the testing is focused on permanent test environments, followed by cloud-based temporary environments.

Test Automation, DevOps, Artificial Intelligence, Machine Learning, IOT testing,

  1. Behavior Driven Development

 BDD moves away from technical language and uses natural language constructs with English like sentences to express behavior and outcomes. BDD has specific emphasis on creating real end-user scenarios around customer experience, security and performance.

This becomes important when the business problem to solve is extremely complex. The usage of BDD has increased in the most recent times with a large number of organizations moving to natural language constructs and it will continue to see an uptrend.

  1. The Open Source Movement and Visual Validations.

 According to the digital quality report, the overall spending on QA and testing tools has been about 30% of the overall IT budget in 2014 and about 1% less at 29% in 2015. Adoption of open source tools and methodologies led to this decrease and we’re going to see alot more in 2017. Report states that these open source solutions are more malleable, more complete, better and hence a greater value for money. Apart from open source, the Java script frameworks are also going to see a spike.

Last but not the least, we’re living in a very visual world. And especially in the application world, UX and responsiveness is key. We can drive a lot of this by using automated testing tools to ensure that users see what we intend them to see.

Test Automation, DevOps, Artificial Intelligence, Machine Learning, IOT testing,

  1. More IoT, More Micro services

 According to Cisco, more than 50B devices will connect and talk to each other. And, it will be the business of quality to make sure that these applications work. IoT doesn’t have specific testing strategy, for most parts device manufacturers require to test and execute all test cases. 2017 is going to see larger push to deal with the overall testing strategy for IoT. This will involve an increased scope. The role of crowd and quality will play a huge role.

There will also be a wider usage of micro-services kind of architecture. These are very small and extremely focused services that make

up a complete application. And we need to test these applications through and through for this micros-services set up.

To conclude, in 2017, automated testing will be the name of the game for sure but there will also be an increased push towards autonomics, as the second level of automation maturity. Autonomics will see a wider usage of robotics replacing human interactions.  The third stage will be cognitive testing and we’ll talk about it in our future blogs. Stay tuned!

 

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