Alive & Kicking!
Quality Engineering is at the Forefront of Innovation

Let’s take a closer look at what sets these frameworks apart—and how they can support your automation goals.

Meet the Frameworks

Selenium: The Established Leader

Selenium has long been a cornerstone of web automation. As an open-source framework, it offers broad compatibility across programming languages—Java, Python, C#, Ruby—and supports all major browsers.

Key Features:

• Cross-browser and cross-platform support
• Integration with CI/CD pipelines
• Headless and headed execution
• Selenium Grid for parallel testing
• Extensive community and documentation

Pros:

• Mature and well-supported
• Flexible language options
• Rich ecosystem of plugins and tools

Cons:

• Slower execution speeds
• Tests can be brittle with dynamic DOMs
• Limited support for desktop applications

Playwright: The Agile Innovator

Playwright, developed by Microsoft, is designed for modern web applications. It supports JavaScript, TypeScript, Python, C#, and Java, and automates Chromium, Firefox, and WebKit browsers.

Key Features:

• Auto-waiting for elements
• Native support for tabs, frames, and events
• Built-in test runner and tracing
• Headless and headed execution

Pros:

• Fast and reliable execution
• Excellent support for modern web features
• Streamlined setup and debugging
• Rich API for advanced scenarios

Cons:

• Smaller community (but growing rapidly)
• Fewer third-party integrations (currently)

Framework Comparison at a Glance

Reputational challenge persists

Despite this positive shift we have witnessed, the role of the Quality Engineering function still appears to face a reputational challenge in many organizations, as it is still not seen as a strategic function. This concern was highlighted by 56% of respondents in our survey. Despite varying challenges across regions and sectors, it’s disheartening to see this issue continues to persist, especially against the backdrop of its significant role in driving innovation.

As development skills have become less critical and the focus has intensified on Gen AI and core Quality Engineering competencies, it appears that the broader value of Quality Engineering is not being fully recognized. The core problem may not lie in the alignment with development teams, but rather in demonstrating tangible value. Despite an increase in the use of advanced technologies like Gen AI and expanded automation coverage, the perceived value of Quality Engineering remains underwhelming.

To address this, organizations need to shift towards metrics that highlight business impact – such as revenue growth, customer acquisition, and overall business performance. By aligning Quality Engineering metrics with business outcomes, organizations can better showcase the strategic value of their quality initiatives and drive meaningful change.

Upskilling for the future: Elevating Quality Engineering through learning

In an area where organizations that are standing still are effectively falling behind, continuous learning and upskilling are critical to Quality Engineering. Our recent survey reveals that 82% reported having an enterprise-wide repository with learning pathways for Quality Engineering roles; however, only half of them track the usage. The number of respondents with dedicated learning pathways for quality engineers is encouraging, but there is a need for an increase in tracking and monitoring the usage of those pathways.

These insights shine a light on the importance of not only providing training, but also ensuring its effective utilization. To truly elevate Quality Engineering, organizations must focus on both the availability and the impact of their training programs for quality engineers. And from a cost perspective, it’s always cheaper to build from within and nurture the talent, than it is to buy in the requisite skills.

In summary…

It’s abundantly clear that the Quality Engineering industry is evolving, and innovation is a key driver behind the comeback that we have witnessed in recent times. Yet the function is still not seen as being strategically important, perhaps as its true value is not measured accurately, nor aligned to business value. So here are our key recommendations:

Include business understanding in training programs to align Quality Engineering efforts with organizational goals.es.

• Adopt a product-aligned Quality Engineering structure:

Integrate quality engineers directly into product teams to ensure their work is closely connected with product development and outcomes.

Setup “as a service” capabilities for Quality Engineering functions that can be run as a shared service like test data and test environment management.

Maintain the independence of testing – as systems continue to increase in complexity with multiple technologies and hosting locations, the benefit of an independent testing team will pay dividends.

• Shift focus to broader metrics:

Move beyond measuring process efficiency and automation coverage.

Evaluate how Quality Engineering contributes to business objectives, such as customer satisfaction, revenue impact, and overall product quality.

• Expand training beyond technical skills:

Provide education in risk management to proactively address potential issues.

Include business understanding in training programs to align Quality Engineering efforts with organizational goals.

As we move forward, the balance between Agile alignment and core Quality Engineering principles will be essential in navigating this new era. The journey ahead promises further evolution, and Gen AI looks set to play a pivotal role in meeting the industry’s ever-changing demands.

To find out more, download a copy of the World Quality Report.