Continuous testing in the age of digital transformation: Trends and challenges

Organizations must embrace digital transformation to stay competitive as technology advances rapidly. Simply maintaining legacy systems is no longer sufficient. To achieve successful digital transformations, continuous testing has become essential for improving the speed and quality of software development processes.

In this article, we explore the current and emerging trends shaping continuous testing and discuss the challenges organizations encounter when adopting these technologies. We also provide practical tips for overcoming these obstacles.

Trends in (& due to) Continuous Testing

1- Cloud-based Testing

For newer companies, cloud-based solutions are the first option for software testing (and development) due to the cost savings, scalability, and agility it offers. However, this wasn’t always the case.

In my many years in the financial services industry, I have seen firsthand how cloud-based solutions wouldn’t even be considered (even if they were cheaper). Heavily regulated industries like banking, financial services, healthcare etc. watched the cloud wave with curiosity, but did not make any strides to adopt them.

However, as technology has advanced, cloud-based testing has become more mainstream and is increasingly being adopted by organizations from all industries, including the conservative ones.

Most organizations now base their architecture on the ‘cloud first’ principle, making a significant difference in their openness to adopting cloud based testing solutions.

2- Merging Lines Between Business and Test Professionals

A significant trend in continuous testing is currently the blurring of lines between business and test professionals. Testing has historically been viewed as a specialized function within IT departments, but as software development becomes increasingly collaborative and cross-functional, the role of business professionals in testing is expanding.

Less technical professionals such as business analysts, product owners, and other stakeholders are becoming more involved in testing processes, contributing to test case creation and definition of acceptance criteria. This collaboration between business and test professionals enhances overall product quality by ensuring testing efforts align with business objectives and customer needs.

The Agile development methodology exemplifies the real-world collaboration between business and test professionals, where communication and feedback are prioritized throughout all stages of the development process. This collaborative approach guarantees that software products align with the business’s and its customers’ changing needs, ultimately resulting in high-quality software products.

3- Testing gets a seat at the table

The significance of testing is increasingly being acknowledged as an integral component of software development. Previously, testing was perceived as a distinct and less important phase within the development process, leading to restricted resource (& budget) allocation. Nonetheless, this viewpoint is evolving, with a rising awareness of the crucial role testing serves in guaranteeing software excellence and fulfilling client requirements.

This change in mindset has led to increased investment in testing activities and technologies, including adopting continuous testing practices. Organizations now recognize that effective testing can help identify and address issues earlier in the development process, reducing the overall cost and time required to deliver high-quality software. As someone who started as a test lead and moved to delivery roles within agile frameworks, I have seen how my influence on quality-related inputs has increased over time.

Consequently, testing professionals are now given a seat at the table and included in key decisions related to software development. This shift in mindset has resulted in better collaboration, improved software quality, and enhanced customer satisfaction.

4- AI & ML in Testing

The use of AI and ML in software testing is becoming increasingly popular due to its ability to improve accuracy, speed, and efficiency. AI and ML algorithms can analyze large volumes of data quickly and efficiently, enabling them to identify patterns and anomalies in testing data that human testers may miss. This has proven especially useful in complex scenarios where traditional testing tools may need to catch up.

In addition, AI and ML algorithms can learn from historical data to identify patterns and anomalies that may indicate issues, making it easier to create and execute test scenarios. This improves testing efficiency and enables organizations to detect potential issues more quickly and accurately.

Using AI/ML-based solutions is especially useful in areas like data quality analysis, data migration-related testing and complex (& data-intensive) places like Fraud/AML/Security & Risk, etc., where for the same set of data, hundreds or thousands of tests need to be written and executed.

AI and ML can also be used to conduct predictive analytics in continuous testing. By analyzing historical testing data, AI and ML algorithms can predict potential issues and identify areas that require further testing. This can help organizations prioritize testing efforts and allocate resources more effectively, leading to more efficient testing and improved software quality.

5- Low Code/No Code Testing

As the need for continuous testing increases, low code/no code testing solutions have emerged as a potent means for non-technical business experts to engage in the testing process.

Low code/no code testing brings a host of advantages. Low code/no code testing offers several benefits. It encourages non-technical professionals to participate in testing, boosting collaboration and knowledge-sharing among teams. It also speeds up test creation and execution, shortening testing cycles. Moreover, it improves product quality by enabling organizations to test more thoroughly and efficiently.

Challenges Associated with Implementing Continuous Testing

Continuous testing offers many benefits to organizations, including faster feedback, improved quality, and reduced costs. However, implementing continuous testing has its challenges. This section will discuss the five main challenges of implementing continuous testing and offer some tips for addressing them.

1- Convincing stakeholders to invest in continuous testing

One of the main challenges of implementing continuous testing is persuading key stakeholders of its value as an investment. Stakeholders might be reluctant to allocate resources to continuous testing due to apprehensions about expenses, the learning curve for new tools and procedures, and the potential influence on delivery schedules.
To tackle this issue, crafting a compelling business case that distinctly highlights the advantages of continuous testing is essential. These benefits encompass expedited feedback, enhanced quality, and long-term cost reductions, among other positive outcomes.

For cost-conscious stakeholders, it is also important to demonstrate the return on investment (ROI) of continuous testing by tracking key metrics such as defect density, test coverage, and time to market. Traditional metrics such as ‘cost of defect’ can also be used to give solidity to the business case.

Another way to convince stakeholders is to start small and gradually scale up. This approach can reduce the perceived risk associated with adopting new tools and processes while allowing teams to gain experience and build confidence in the benefits of continuous testing.

2- Balancing glamorous targets with practical considerations

Balancing glamorous targets with practical considerations is a significant challenge when it comes to implementing continuous testing. Organizations may aspire to achieve 100% test automation or 5 builds daily, but this may not always be practical or feasible (or even needed).

Balancing automated and manual testing and being realistic about what can be achieved with the available resources certainly helps.

Rather than aiming for complete test automation, focus on automating the most critical and time-consuming tests while leaving less critical tests for manual testing or another approach. Prioritizing ruthlessly based on business value can maximize the benefits of test automation while ensuring that testing efforts align with the organization’s business objectives.

Also, taking a MVP approach and highlighting your initial wins helps you build more influence with your stakeholders (read previous point).

3- Maintaining test environments

Another challenge associated with continuous testing is managing test environments. With frequent code changes and updates, organizations must ensure that they have the necessary infrastructure to support continuous testing. This includes maintaining multiple test environments that can replicate the production environment as closely as possible, providing test data that reflects real-world scenarios, and ensuring the test environment is stable and secure.

Organizations can leverage cloud-based testing environments to overcome this challenge, which can be easily scaled up or down based on demand. These environments provide the flexibility and scalability to support continuous testing without costly infrastructure investments. Additionally, organizations can invest in test data management tools to help create, manage, and maintain large and complex data sets, allowing for more accurate and comprehensive testing.

4- Lack of Test Automation Expertise

A lack of test automation expertise presents a significant challenge in implementing continuous testing. The problem is compounded by exploding demand from the increasing number of organizations embracing agile and DevOps practices.

To tackle this predicament, companies can allocate time, attention and resources towards educating and enhancing the skills of their existing workforce. Furthermore, organizations can collaborate with external service providers who are test automation experts to reinforce their in-house capabilities.

Adopting low-code or no-code test automation instruments can also be a valuable supplement. Utilizing these tools empowers business analysts, product managers, and other non-technical team members to participate in the testing process, consequently easing the workload of test automation specialists.

5- Integrating Testing into the DevOps Pipeline

A scarcity of expertise in test automation is a significant obstacle in executing continuous testing. This deficit in skilled professionals is intensified as the demand for test automation rises with an increasing number of organizations embracing agile and DevOps practices.

To tackle this issue, organizations can allocate resources towards educating and enhancing the skill sets of their existing workforce to become adept in test automation. Furthermore, collaborating with external vendors specializing in test automation can also help augment in-house capabilities.

Utilizing low-code or no-code test automation platforms can be a useful supplement to the above. By doing so, business analysts, product owners, and other non-technical team members are empowered to participate in the testing process, thereby reducing the pressure on test automation engineers.

Wrap Up

Continuous testing is key to any successful DevOps and agile transformation, but implementing it effectively can be challenging. Organizations must ensure they have the necessary resources, infrastructure, and expertise to support continuous testing. Additionally, organizations must adopt a DevOps mindset emphasizing collaboration and feedback across all stages of the development process.

Finally, leveraging cloud-based testing environments and test automation tools can help organizations overcome many of the challenges associated with continuous testing. With the right approach and tools, organizations can confidently embark on their journey towards continuous testing.