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Impact of COVID-19 On Software Quality Engineering

George Ukkuru, Head of Quality Engineering at UST

IT teams have made numerous changes to the network and security controls to establish connectivity to office networks and applications.

George Ukkuru, Head of Quality Engineering at UST

The COVID-19 pandemic has wreaked havoc on every industry resulting in the slowdown of many businesses. This universal decline in activities in all the sectors will directly affect IT services and product companies. Forrester has predicted that the Global Technology Market Growth would slip to 2% in 2020, and one can expect further decline as the COVID-19 spread has increased in the last thirty days.

With release teams working from their homes to reduce the spread of the virus, COVID-19's challenging constraints are the biggest to impact the quality engineering discipline since it began three decades ago. While introducing positive impacts like eliminating time spent commuting and reducing operational cost of facilities, etc, there is still a curve to climb for teams to perform in this new reality. It’s a long-standing belief that co-locating Agile software development teams increases productivity. Yet, this also increased software development costs as offshoring or near-shoring was minimal. And there have always been challenges in getting DevOps Engineers, Chaos Engineers, SDET's etc. in a single location.

Today, as the Coronavirus changes the global workforce, organizations must source top quality engineering talent from around the world as co-location is not mandatory anymore. As remote Agile teams shift from offices to their homes, it requires a dedicated focus to maintain the team mindset , approach, productivity levels, and transparency. The biggest impact to quality engineering is that the physical labs and devices used for testing are not directly accessible from homes. Quality Engineering leaders and architects should revisit tool-sets, automation approach, testing strategies and test data management procedures to ensure teams can collaborate and minimize silos.

We will be discussing some of these emerging tools and practices in our upcoming webinar, featuring Forrester VP and Principal Analyst Diego Lo Giudice. Register here: Cracking the Code: Quality Engineering Models for Continuous Delivery

Here are six practices that Quality Engineering teams must adopt as they manage software delivery projects remotely during the COVID-19 pandemic.

Our experience has shown us that every crisis presents us with a set of opportunities, and organizations should be prepared to reap any potential benefits. It is crucial to evaluate the change in market conditions regularly and adjust your quality engineering strategies to minimize disruption. Test optimization activities should take a very high priority as one can expect shrinkage in quality engineering budgets. Set aside time to evaluate services that will be of demand in the post-COVID scenario and invest in building capabilities. Let us attempt to make the best of what's still around in the midst of chaos.

Redefining Quality Engineering Strategies in the Age of Covid -19

As there is a growing need to drive sales and support via digital channels, engineers need to test their websites and apps on multiple devices, resolutions, and screen sizes. SDET's engaged in digital testing have started adopting public and private cloud device farms like pCloudy to tackle the situation. A cloud-based device solution provides remote access to devices, API based integration with automation frameworks and concurrent execution of tests on multiple devices. This shift will help to improve the device coverage and eliminate the dependencies by providing access anytime, anywhere.

The COVID-19 pandemic has also required additional focus on test data management strategies and procedures. Engineers were testing applications using masked data from production with the help of a centralized test data management team. The testing was typically performed from office or from an offshore development centre where there were security restrictions on the usage of mobile devices, paper, pen, etc.

Now with engineers moving to the comfort of their homes, organizations prefer to eliminate the production data dependency and prefer to use tools like GenRocket. The test data management efficiencies can be improved by deploying self-service test data bots and portals that will empower engineers to provision data on their own.

The cyber-attacks have increased after the start of the pandemic as cyber criminals are exploiting new and existing vulnerabilities. There are high chances many applications have not undergone a static and dynamic security scan as they were not exposed to external networks. So, it is vital to carry out static and dynamic scans of applications to identify and remediate security flaws by working with the application developers. In the longer term, SDET should look at implementing automated security scans of the applications by enhancing the automation framework that is in use, by adding capabilities like BDD security to minimize business risks.

The pandemic has also generated a need for rapid deployment of digital solutions for various needs like pre-screening, contact tracing, social distancing etc.

All of these applications will have to be tested on multiple devices and form factor at speed. Adopting crowd-sourced testing will help organizations to improve device coverage and speed by keeping the testing costs to a minimum.

Learn more about automated testing and remote strategies for Quality Engineering in our upcoming webinar, Cracking the Code: Quality Engineering Models for Continuous Delivery, featuring Forrester VP and Principal Analyst Diego Lo Giudice.