The Future of Test Automation Requires More Than Technology


Technology is a means to an end.

Our ecosystem with accelerated innovation and competition pushes to increase the test automation contribution to Quality at Speed.

While new technologies are coming, the key to success lies in connecting users, processes, and technology within the test automation lifecycle.

We need to focus on the three areas of test automation requiring fast feedback loops: test repository, test execution and test reporting.

This article shares the current technology and test automation landscape before digging in the future of each test automation area.

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The existing test automation landscape

The test automation challenge is to accelerate the delivery of valuable software by contributing across the software delivery lifecycle.

Once reserved to narrowed specialists, solutions evolve for transversal collaboration, easier onboarding, and maintenance.

Test automation can be improved without an end-to-end AI.

The existing technologies already are available to provide:

  • Modern user interfaces with a shared language,
  • Native integrations with other platforms like CI/CD or Cloud testing,
  • Built-in reporting and analytics that can detect anomalies.

Let’s see how the evolution of these technologies can contribute to the future of test automation.

Test Management with next-generation low-code

A requirement repository is one of the main assets for Quality at Speed to keep a central vision and identify the required test automation in different contexts.

The implementation of automated tests still requires significant efforts of translation from business requirements to an executable technical component.

Too much time is lost in translations.

Figure 1: Many translations required for test automation, QATestLab.

Codeless, AI (e.g. Natural Language Processing) aims to automate these translations by defining tests from requirements or observability of the software.

Like any tool, the value depends on the usage. 

The goal of test management is to rapidly define, implement and maintain a set of functional and non-functional business requirements.

More than technology, effective test management requires fostering end-to-end collaboration and skills development for fast adaptation.

Test Execution for large distributed systems

The successful execution of automated tests requires supporting multiple environments for rapid, stable and parallel test runs.

A cross-functional team needs fast feedback when they perform a software change: is my change working as expected? Are all the other features stable?

Stability is a challenge in a distributed environment with faster changes.

Figure 2: IoT on the Edge with complement Cloud testing. Avnet

IoT, Augmented Reality, Virtual Reality – these technologies are contributing to the explosion of Big Data started by the Cloud and Social Media.

Test automation will have to support more API Testing with a variety of devices, context (Cloud & Edge), and massive data streams.

More than technology, solid methodologies, architecture and skills of data processing, APIs and distributed computing will make the difference in test automation.

Test Reporting with faster insight to action

Fast test execution supports software meeting their requirements more quickly, where the human part is part of the limiting factors.

A lot of teams still consume hours to produce specific reports based on their execution data. They need to use their time more effectively.

All the time passed in building reports does not improve the product.

Figure 3: Cerberus Testing natively provides you with native dashboards, Cerberus Testing.

A test automation solution must therefore provide reporting and analytics as native features; even with existing user interface technologies.

Data science aims to accelerate the report lifecycle by providing advanced dashboards, automated alerts and correlations hardly detectable for humans.

More than technology, the analysis of automated tests still requires understanding the data, defining the useful metrics and driving the action plans.

Test Experience augmented by composition

Test automation domains are usually fragmented between test repository, execution and reporting; slowing down the team feedback loops.

We dream of an end-to-end test automation experience streamlined across the test lifecycle, supporting the delivery of Quality at Speed for our teams.

This dream requires collaboration.

Figure 4: Cerberus Testing provides a growing set of integrations, Cerberus Testing.

The composition of technology will unify the test automation processes by providing automated test generation, native quality gates with embedded alerting.

Hence, integrating solutions through open and standard APIs is critical to improving the test automation experience, with or without AI.

More than technology, human collaboration will remain an essential requirement to capture the value of streamlined end-to-end processes.

The Future of Test Automation requires collaboration

We are all facing similar challenges in evolving the digital landscape and supporting technologies.

Our accelerated world requires fast adaptation in the changing ecosystem; changing too late means lost opportunities for organizations.

We have to go fast and together. The speed gained with a large collaboration enables all of us to benefit from joint efforts, avoiding siloed initiatives.

The future of test automation is about collaboration, open-source, and platforms to remain valuable in a world of Quality at Speed.

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