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Generative AI
Cloud
Testing
Artificial intelligence
Security
January 29, 2024
In our latest World Quality Report – our annual global survey in which we reach out to 1,750 organisations in more than 30 countries to assess trends and attitudes in and around Quality Engineering & Testing – we wanted to try and gauge how these changes were impacting the QE&T department. We also wanted to evaluate the levels of readiness organisations were demonstrating to support the move to agile, and the impact this was having on skillsets.
Notably, two distinct approaches are being taken by quality engineering organizations – some have taken a ground-up approach, focusing first on workforce transformation, while others have taken a top-down approach, choosing to restructure their quality engineering (QE) organization from a process standpoint.
Those that are undergoing some form of workforce transformation are evolving their traditional quality skills into full-stack quality engineers. These organizations are now prioritizing development skills over traditional testing skills as the most critical tools for quality engineers. Development-focused skills like C#/Java/SQL/Python and CI/CD are all ranked in the top 5, while traditional testing skills like automation and performance tooling ranked at the bottom end of the results.
Delving further into the detail, our survey revealed that 42% of the respondents felt scripting language like C#/Java/SQL/Python is the most critical skill required by today’s quality engineer, 39% voted for CI/CD and orchestration closely followed by BDD/TDD at 38%; compared to just 28% for automation tooling and 24% for performance tooling. While skills like ETL, open-source testing solutions, Artificial Intelligence (AI), Machine Learning (ML), cloud, and tooling were considered important; the above-mentioned three stood out above the rest.
While this trend of prioritizing development skills over traditional testing skills appears to be consistent, each region appears to have its own set of unique challenges which aligns with how the QE organizations are set up today. The US and Canada face similar primary challenges, more than two-thirds of respondents confirming a general lack of supporting test processes. However, 86% in Canada confirm a lack of coding skills, with 70% of US respondents confirming a limited career path.
Meanwhile, other regions like the UK reported a lack of knowledge of agile techniques as the most common challenge (77%). This could indicate the speed at which these organizations moved into a product-aligned QE model while still trying to utilize their traditional testers.
As quality engineers continue to adopt more of a developer mindset, their ability to introduce automation earlier in the lifecycle increases as does their ability to troubleshoot and even remediate defects on a limited basis. This evolution of agile practices, the integration of AI and ML, and the synergy between DevOps and agile are transforming quality engineering in infinitely futuristic ways.
In doing so, organizations are increasingly pushing to get new features and enhancements out faster, which puts an even greater focus on speed to market. This leads us to the following recommendations to increase the value from your quality automation initiatives:
Quality Engineering & Testing, Financial Services
Portfolio Manager, Testing Deal Architect for Global Sales Support Team, QE&T, Capgemini Financial Services