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Software testing and Automation: Emerging trends for 2018

Software testing and automation as dominant patterns for 2018

DevOps, CI/CD pipeline and the agile way of software testing dominated the conversation in 2017. However, for DevOps and Agile teams to see significant gains, the practices, tools, and processes need to evolve and become more agile. The key themes of 2018 seem to revolve around the same approach. But there are several tech trends and changes that will impact the realm of test management and testing tools.

We will see more innovation in tools and changes in the software testing and automation paradigm.  Some of the goals include: better coverage, unified solutions, focus on automation and exploratory testing, more intelligent and data-backed decision making. Here’s a quick rundown of the trends and technologies that will rule test management.

software testing and automation in 2018

  1. AI, IoT and blockchain

AI, IoT, and blockchain have been on every tech trend listicle for the past couple of years. 2018 appears to be the year when all these technologies converge and cause a further shakeup in the digital economy. How does this impact software testing and automation?

These three technologies are very likely tied up all the software used across industries. The technologies then, will not only alter the course of software development and how applications are used but also how they are tested.

  1. DevSecOps and DevTestOps

The speed of DevOps makes it more difficult to know what is trusted and what is not” reveals the opinion of about 79% company CIOs in a 2016 DevOps study. Security as an after-thought doesn’t work at all. But the software testing landscape is now extremely complicated.

The thousands of devices, a variety of screen sizes, different OS browsers and networks demand a more thorough and advanced testing process. More complicated and advanced testing scenarios coupled with agile approach mean that developers and testers will require a robust DevSecOps practice to prevent security lapses.

The DevTestOps model continues to be important for agile teams as an integral part of the CI/CD pipeline.  When done right it can significantly improve the velocity of your releases. There are many ways to go about it. Automation of various tests – unit tests, functional tests, process tests and performance tests is just one of the many ways to achieve this seamless quality at speed.

  1. Shift from Performance testing to Performance engineering

Performance engineering is a quantitative, systematic and software-oriented approach. It focuses on design, architecture, implementation choice and cost-effective software development to meet performance requirements on time.

The shift from performance testing to performance engineering requires the shift-left approach to address performance earlier on in the development process. This is again, perfectly in tune with the agile way of life.

  1. Toolset integration and consolidation

Continuous testing is often called the missing link in the Continuous Delivery process. Companies on their journey to digitally transform, require better software faster to speed up their initiatives. Testing therefore and continuous testing is the vital link that makes it happen.

This focus on continuous testing for software testing and automation will lead to a tool convergence. Companies will not only require new agile tools for test automation but will need a more integrated and omnichannel test management approach. Modern test automation and management tools will offer features and options to integrate with ALM toolsets and environments to promote smarter decision making.

  1. The evolution of metrics

As Agile testing methods and the DevOps culture gain more maturity, there is an increasing need for more data and analytics that help companies make better decisions. In fact, the use of artificial intelligence and machine learning algorithms will allow businesses to test more intelligently and optimize their test automation.

More companies will make use of Predictive and Prescriptive QA to anticipate defects earlier on in the dev cycle and streamline test automation to achieve the desired digital maturity.  As such, this will lead to a demand for smarter tools and processes. Tools that help predict the defect ranges and risk of modules for next versions, assess application lifecycle efficiency drivers and improve the overall quality of outcomes.

Final thoughts

software testing and automation

The dominant themes from 2017 – automated testing, Agile, DevOps continue to hog the limelight in 2018 as well. The key enablers are the maturity of processes and a shift in the overall approach and toolset.  We will see a rise in the level of intelligent test automation, investment in smarter QA platforms and more of DevTestOps in the coming months.

 

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