The Evolution of Testing in the Digital Era

The Evolution of Testing in the Digital Era

The modern paradigm of testing is primarily rooted in placing pre-deployment testing at the center of software quality assurance, and understandably so. However, the testing school of thought didn’t always work this way!

Originally, software testing was just a minor part of software engineering, and not the end-to-end testing strategy that it is today.

But why is that important in the current context? Because it lets us understand the evolution that has led to the current state of software testing. Knowing what came before also helps us identify the new challenges and their possible solutions for adapting to the current reality.

The Early Days of Testing

Between the 1950s and 1970s, the goal of software testing was only to test the software’s functionality, not its quality. It was only in the 1980s that testing came to be considered a key activity to assess application quality. This was also when automated testing started emerging in force and focused on performing high-volume testing, saving time on repetitive testing tasks, and improving the application’s quality.

The Evolution of Continuous Testing and Agile Testing

In the 1990s, customers’ increasing unwillingness to wait for a final product led to the initial adoption of Agile methods, leading to Continuous Integration/Continuous Deployment (CI/CD) and continuous testing.

Then, in the early 2000s, more teams started adopting such agile and iterative testing, an approach that emphasized iterative and incremental testing and collaboration between self-organizing groups. Testers also started adopting testing techniques like exploratory testing, rapid testing, and risk-based testing.

Advancements in Automated Testing

In the 2000s, many automated testing tools and support systems emerged, including Jira (2002), Selenium (2004), and Soap UI (2005). Several test automation frameworks also evolved, including:

  • Test-driven development (TDD): Developers write the tests while focusing on feature implementation.
  • Behavior-driven development (BDD): Testers create automated specifications to test system behaviors.
  • Modularity-driven testing: An automated testing framework in which independent modules of automation scripts are developed for a particular test case
  • Code-driven testing: Unit tests are executed to determine whether the code is behaving as expected under various conditions.
  • Data-driven testing: Applications are tested with different input datasets to check if they continue to work correctly.

Many other testing methodologies also evolved in the 2000s, including keyword-driven testing, stress testing, automated test scripts, and regression testing.

The Emergence of Cloud Testing

The rising popularity of cloud computing in the 2000s led to the emergence of cloud testing. Cloud testing is performed on a third-party cloud computing environment to assess if the application meets the organization’s requirements for performance, reliability, security, and scalability.

Cloud testing offers numerous benefits over traditional on-premises testing. Testers can test their applications in a dynamic testing environment that easily keeps up with evolving requirements, making it a scalable testing approach. Testers can also emulate an end-user-centric testing environment without added costs or geographical constraints.

Cloud testing also offers increased test coverage, reduced test maintenance, and better testing, not to mention more accuracy, reusability, and cost-efficiency.

How to Use Cloud Testing Tools to Test Modern Applications

Cloud-based testing tools emulate real-world environments. Testers can configure the testing environment according to their requirements. They can also leverage cloud-based testing labs, device cloud, service virtualization, and other capabilities.

With cloud testing tools, testing teams can perform:

  • Functional testing, including system, integration, and acceptance testing
  • Non-functional testing to review application performance, usability, and scalability
  • Ability testing to confirm if users will receive application services from the cloud on-demand

To get the best possible results and ROI, organizations should look for cloud testing tools that:

  • Support the devices and browsers end-users might use to access the software application
  • Offer advanced security capabilities
  • Minimize wait times for queued tests
  • Support team-wide testing on a single plan
  • Enable tracking of testing status and testers’ progress

The Future of Software Testing: The Case for AI and ML

Lately, testing teams are also adopting Artificial Intelligence (AI) and Machine Learning (ML) tools to automate and optimize their testing processes. Per one 2021 report, 88% of organizations plan AI-based testing initiatives in the coming year.

AI-based testing tools help reduce the need for manual and scripted testing. They automate many tedious testing tasks, speed up the testing process, and generate better results – and thus a better quality product – with the power of algorithms, data, and logical reasoning.

Teams can now take advantage of real-time AI-driven monitoring and integration of any technology stack and leverage applied analytics to gain deep test insights from their increasing data volume and variety.

Some AI-enabled tools also have built-in “self-healing” capabilities. Self-healing test automation – considered the “next big thing” in software testing – means that AI is applied to identify when a function has changed. The test can automatically update itself, and the tool heals the test scripts.

In the future, AI and ML tools will more effectively mimic human intelligence and allow computers to “learn” and continually improve their capabilities. These technologies will support the emergence of next-gen DevOps that will empower organizations to move beyond function- or script-driven approaches towards automated decision-making, touchless testing, and a genuinely virtual/borderless organization.

Powered by AI tech, testers will use differential, declarative, and visual testing techniques to reduce application defects, increase test coverage, and accelerate time-to-market and time-to-ROI.

The Future of Software Testing: Testing as a Service (TaaS)

TaaS is growing in popularity as an affordable and efficient approach to software testing. Unlike traditional testing environments, TaaS involves outsourcing the testing function to a specialist testing firm like Calsoft.

TaaS provides a cost-effective consumption-based payment model, allowing organizations to reduce testing costs while achieving scalability and high-quality test outcomes. Organizations don’t have to invest in expensive infrastructure, tools, testers, or software licenses because the TaaS provider will take care of all these aspects.

Together, TaaS and cloud-based testing provide better results in terms of bugs identified, application quality, testing standardization, ROI, and repeatability.


Software testing has come a long way. Today’s testers have access to a plethora of automated, cloud-based, and AI-based tools that make their lives easier and enable organizations to put out high-quality, user-centric applications.

Calsoft offers end-to-end agile QA solutions so you can deliver top-notch products to your customers. To know more about our advanced testing techniques, QAOps workflows, test automation capabilities, and TaaS offerings, click here.


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