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Learning Software QA Engineering and Testing in 2026

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Entering the field of Software Quality Assurance can feel like stepping into an endless pool of tools, techniques, approaches, methodologies, procedures, and technologies. However, it might be not that scary but it’s not an easy task! This article aims to guide you through this maze, offering insights, practical advice, and examples of resources to set you on the path to success in Software QA and Testing.

The Essentials

A strong foundation in QA fundamentals is crucial for any QA engineer or tester. Understanding the SDLC, testing methodologies, and different types of testing (e.g., functional, regression, performance, security, etc) is vital. Familiarize yourself with various testing environments, including web (frontend, backend), mobile, and desktop apps.

Platforms like Udemy, Coursera, LinkedIn Learning, etc offer comprehensive courses covering QA basics, You also can follow QA professionals on LI (and other resources such as HackerNoon) who share tech/useful insights. While websites like the Ministry of Testing, Software Testing Help, Guru99, EuroStar Huddle, the best tribe, QA Lead, Testing Tech News (TTN), etc provide in-depth articles and tutorials on testing methodologies and best practices.

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Your Technical Skills

Skills in programming languages, version control systems, and databases will elevate your QA career. Experience in any languages like Python, JavaScript, C#, and Go enables you to write useful scripts (for testing, performance tests, test data generation and migration) and autotests. At the same time, familiarity with version control tools like Git and/or SVN facilitates collaboration within dev teams.

Platforms like Codecademy, LeetCode, and HackerRank offer interactive coding challenges and tutorials, making learning programming and other technical skills easy. There are countless video tutorials online and for free.

Read Books

When it comes to books about QA and programming, there are lots of them available to suit various learning styles and levels of expertise. Books cover topics ranging from QA methodologies and best practices to programming languages and software development principles. Whether you’re a beginner looking to build foundational knowledge or an experienced professional seeking to deepen your understanding, there are books tailored to meet your needs. Additionally, many books offer practical insights, case studies, and real-world examples to help readers apply concepts in their professional endeavors. By exploring a diverse selection of books on QA and programming, you can improve your skills, expand your knowledge, and stay updated with industry trends and best practices.

  • “The Art of Software Testing” by Glenford J. Myers, Corey Sandler, and Tom Badgett.
  • “Agile Testing: A Practical Guide for Testers and Agile Teams” by Lisa Crispin and Janet Gregory.
  • “Python Crash Course” by Eric Matthes.
  • “Fluent Python: Clear, Concise, and Effective Programming” by Luciano Ramalho.
  • “Eloquent JavaScript: A Modern Introduction to Programming” by Marijn Haverbeke.
  • “You Don’t Know JS” series by Kyle Simpson.
  • Avoid Information Overload

Much like the field of AppSec, QA engineering boasts a wealth of resources and experts, each offering their unique perspectives and insights. While it’s tempting to absorb every piece of information available, it’s important to avoid overwhelming yourself and have enough rest, spend quality time with family and friends, do sports and hobbies, and have time for leisuring. Focus on your personalized repository of knowledge using tools like Evernote, OneNote, Notion, Trello, Google Keep, Obsidian, and Roam Research where you can organize useful content, learning tasks and practical tasks, tutorials, and QA methodologies.

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Learn Automation (but not overemphasizing)

While automation plays a significant role in modern QA practices, it’s important not to overlook other testing skills and approaches. Understanding when to automate tests versus when to perform manual testing is key. Automation tools can streamline repetitive tasks, but manual testing remains invaluable for exploratory testing and uncovering edge cases. Many aforementioned platforms and resources offer courses on test automation, covering popular tools like Selenium, Appium, PalyWright, Puppeteer, and Cypress. Such resources provide insights into automation frameworks and best practices.

Exploring Tools and Technologies

Being an effective QA Engineer requires the right set of tools and strategies. By leveraging the following tools and approaches, you can streamline your workflow and add value to your role within the product team:

  • Use programming to solve different tasks such as test data generation, scripting for manual tests, fuzzing, load testing, data analysis, and report creation.
  • Experiment with performance testing tools like JMeter or LoadRunner, which can also be used for functional API testing, improving your testing skills across different domains.
  • Utilize Postman for API testing automation. It’s simplicity and useful features make it a valuable tool for API testing workflows.
  • Familiarize yourself with platforms like GitLab and GitHub. Setting up your development environment and running applications locally will provide you with a deeper context.
  • Explore Docker for containerization. Start with simple setups and gradually go into more advanced configurations to improve your understanding of containerization.
  • Experiment with virtualization software such as VirtualBox to gain insights into different operating systems (Windows (including Windows servers), Linux, Ubuntu, MacOS, CentOS, Fedora, etc and their configurations, enriching your testing environment setup.
  • In agile environments, try collaborative tools like Google Sheets, Docs, and Trello as alternatives to Atlassian tools and TestRail, fostering efficient communication and task management.
  • Explore security testing tools like Nmap, Nessus, OWASP ZAP, BeEF, SQLmap, Sn1per, Nikto, Metasploit, BurpSuite, etc to get an understanding of security/penetration testing methodologies and techniques.
  • Use tools like Fiddler, Charles (or even Wireshark) for efficient traffic analysis, enabling you to diagnose and troubleshoot API- and network-related issues effectively.
  • Experiment with automation frameworks such as Playwright, Puppeteer, pytest, Katalon, Cypress, and Flutter to automate something.
  • Gain familiarity with HTTP(s) methods and different protocols like HTTP, HTTPS, and WebSockets to understand the nuances of web communication and ensure thorough testing coverage.
  • Learn about browser dev tools and how they can be useful for QA/Testers/Devs.
  • Leverage AI-powered tools like ChatGPT and GitHub Copilot for assistance with programming tasks, enhancing your productivity and efficiency.
  • Familiarize yourself with frontend tech stack like HTML, and CSS to understand how web apps work and ensure comprehensive testing of UI.
  • Learn basic debugging techniques for mobile and desktop applications to effectively identify and resolve issues across different platforms.
  • Explore tools for monitoring resources, detecting memory leaks, and optimizing resource usage to ensure the stability and performance of apps under test.
  • Understand the differences in behavior and rendering across various browsers and OSs to ensure consistent user experience across different envs.

Remember, proficiency in every tool is not necessary and you don’t even need to try every tool, just one from a group of similar ones for the same tasks is enough. Focus on gaining basic knowledge and periodically utilizing these tools to enhance your efficiency, making your work faster and more enjoyable.

Real-World Experience

One of the most effective ways to develop your QA skills is by gaining real-world experience. Consider participating in open-source projects, contributing to testing efforts within any IT projects, exploring freelance QA opportunities, or seeking trainee programs in companies. Additionally, platforms like Test Automation University, Udacity, Coursera, Pluralsight, edX, etc offer virtual labs and real-world projects where you can apply your skills in a simulated environment.

Mindset and attitude

In addition to technical expertise, having a diverse set of soft skills, the right attitude and mindset are crucial for success as a QA Engineer. A foundation in technical matters lays the groundwork for understanding the complex architectures of different systems and services. However, demonstrating leadership by efficiently managing and closing tickets showcases initiative and accountability. An invaluable quality is a selfless attitude, and willingness to tackle problems of any complexity without hesitation. Persistence is an important quality when faced with challenging tasks, while a sense of independence, together with a willingness to act and collaborate, lead to productive teamwork. Effective communication with cross-functional teams, understanding business requirements, and aligning tech solutions with business goals show the importance of being result-focused and business-oriented. 

As a QA/Tester, prioritize these qualities, develop and embrace them; they serve as a guiding principle in many companies.

Continuous Learning and Certification

The field of QA engineering is evolving maybe not fundamentally but new technologies and tools emerging regularly. Stay updated with the latest trends, tools, and working approaches by attending conferences, webinars, and workshops. Also, consider pursuing relevant certifications like ISTQB, CAT, CSTE, CEH, CompTIA Security+, OSCP, Microsoft Certified: Azure Fundamentals, or AWS Certified Developer (not all certifications listed are specific to the QA field, and having them may not be necessary. But having certifications like those mentioned can be advantageous, offering additional depth of knowledge. Certifications specifically tailored to QA/Testing provide valuable insights into the field but may not always translate directly into market benefits), which validate your expertise and enhance your credibility as a QA professional.

Conclusion

Embarking on a career in Software Quality Assurance Engineering/Testing in 2024 may seem daunting, but with the right guidance and resources, you can navigate this dynamic field with confidence. Remember to prioritize mastering the fundamentals and continuously expanding your technical skills. Leverage a variety of resources, from online courses to real-world projects, to gain practical experience and stay ahead of the curve. By remaining adaptable, curious, and committed to learning, you’ll be well-equipped to thrive as a QA professional.

EuroSTAR Huddle shares articles from our community. Check out our library of online talks from test experts and come together with the community in-person at the annual EuroSTAR Software Testing Conference. The EuroSTAR Conference has been running since 1993 and is the largest testing event in Europe, welcoming 1000+ software testers and QA professionals every year. 

RisingSTAR Update: Using AI for Testing Tasks

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Joonas Palomäki was the EuroSTAR 2023 RisingSTAR Award winner for his idea of utilising AI to help in testing related tasks. The original title was about using AI to make test cases 50% faster, but the subject has been broadened to cover more areas where Artificial Intelligence can be used to help testers work more efficiently. This is a sneak peek into the evolving work.

A classic example of AI generated image – looks good but does it make sense?

It has been an interesting time! A lot has happened during a year. The word AI is everywhere. It is at the same time a buzzword that is added to toothbrushes to sell them, and at the same time the core AI services are developing so fast that people and companies have hard time learning to utilize them properly. We are just starting to see how they are incorporated into uses and really useful products. Depending on who we listen the AI is a futile gimmick that just creates trash content and is actually counterproductive, or it is a miracle that will do our work for us. I’ve been finding uses for LLM AIs that help software testers in their work, and I’ve found that the AIs can be used as very effective tools when used correctly. This is an update about the progress I’ve made so far.

What are these AIs made of? – How to Use them and Get the Benefits

To be clear, when I’m talking about AIs I’m talking about Large Language Models, LLMs. To use them as effectively as possible, it is needed to understand a little bit about AIs – how they work to understand what are their strengths and their weaknesses. In EuroSTAR I will delve much deeper into this, but here’s a few key points

  • When you ask non-agent AI ( Like ChatGPT ) to do something, it works very differently than a human who is able to iterate on the work and has the ability to control the work itself. This makes a huge difference on what kind of tasks AI can solve.
  • AIs are the most effective when the user outsources the parts of the tasks to AI where the machine is best and does the parts itself where the human brain is needed.
  • AI is “Tabula Rasa” – it does not know anything about users or users’ needs. It is super knowledgeable about the world. It surpasses any human in general knowledge because it knows quite much about everything. It just does not know what the user wants. By being verbose about what the AI should be doing leads to much better results.
  • Different LLMs perform differently. The difference is absolute on complex tasks – weak AIs always fail, strong AIs do perform. 
  • There are limits to what AIs can do. They can not do everything – know the limits!
  • AIs do make mistakes. Expect that. It does not mean the whole AI is not useful if you get good answers often enough.
  • You can expect at most as good results as how well you have defined the task for the AI. Basically this means you need to input quite a lot of information to the AI so it can take that into account in its answers. 
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Uses for AI in the Field of Testing

So the approach for utilizing AIs is to use it for small enough tasks that are

  • Easy enough for user to define
  • Easy enough for AI to handle
  • Complex enough to benefit from the AIs answers

Another thing I’ve found effective to think of AI uses is to differentiate tasks where you use AI to give you insights on something, and when you also use AI to formulate data into more permanent format. When you do these steps separately, your workflow is more efficient. 

Practical Uses

GPT-4 was the first strong enough LLM AI that was able to produce good enough test cases from the specification to be useful. By just giving GPT specification and asking for tests does produce tests, but hardly good enough – as too big portion of the tests are less than useful. By splitting the task – asking AI for ideas for testing – test factors – then reviewing those and finally formulating the test case yields much better results. 

That is hardly the most interesting use for AI. There are multiple other uses where AI can be used to help in various testing related tasks. Here are some examples I’ve been using AI for

Doing Exploratory Testing with AI
    • Test cases are one way to document the testing work and known to everyone, but on many cases they are not needed. 
Writing Better Bug Reports
      • AI can be used to double check if the user has missed something important.
Writing Better Improvement Ideas for / or change requests
    • Pretty much the same idea than with bug reports but AI is given different information to work with.
Incorporating Change Requests into Specification
    • Automatically finding the the specification items where the change request belongs
    • Suggesting improvements to specification
    • Helping formulate the specification based on suggestions and other input

Using AI works in all these cases – in certain circumstances. It all depends on the project, available data and also personal preferences. Some like to ideate with AI, some hate it. 

These are not all traditional tester tasks, but then again the role of software testing has long been intertwined with other development tasks. In addition to these, there are numerous other uses for AI especially in test automation and data handling and generation that I would love to dive into, and plan to after EuroSTAR. 

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What about the Future – will there be a renaissance of the specifications? What will Testers do?

Related to utilising AI, a brief look at the future – my prediction about what we are likely to see in the future.  As a tester I have always valued specification – especially a maintained one. 

Maintaining up to date specification is often a bit overlooked – especially with agile methods the focus is usually in doing, not documenting. It is common to document the thing currently being done, but leaving the old stuff as is. This is problematic for the mentioned AI techniques, new people in the project and AI code generation tools as well. Companies that want to increase their efficiency by using AI code generation tools should also think about this – is the important specification data in a format that can be easily read and understood by people AND can it be sent to AI to help coders in their work. I see that very likely future as we are already seeing tools that do exactly that – make software from the specifications. They are still rudimentary, but are developing fast. 

That will then open up a question – what will be testers’ role in the future? In a broad sense, the essence will probably be the same – Someone should be in control of the quality. The AI is just another tool – albeit a powerful one, that helps getting more done during the workday. Still, someone needs to use that or those tools – to make sure the tool did what it was supposed to. Testers’ role will probably intertwine more deeply with business and development – towards overseeing quality control by defining what software should be doing and using AI tools to automate the actual testing.

The 2024 RisingSTAR Award was won by Bart Van Raemdonck (Belgium), for his idea of creating a Quality Evolution Tracker. See more about Bart’s idea and all the 2024 finalists. Over the coming year, Bart will be mentored by the panel of RisingSTAR Supporters and will take to the EuroSTAR stage in June 2025 to share his project story and updates.

The 2025 RisingSTAR Award will open for submissions in the New Year. The RisingSTAR Award recognises innovation in the software testing and quality assurance industry. It is self-nominated and the winner is chosen by the RisingSTAR supporter group who provide mentorship and guidance to the winner as they develop their idea int

From Bug Bash to Automation: The Evolution of Software Testing

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“Quality means doing it right when no one is looking” – Henry Ford

Quality is always going to be a big factor and priority in anything we do in life, and the same is true with software. Companies and people build software to make a difference, to help make the world a better place.

Imagine building a house without ever checking if the walls are plumb or the roof leaks. In the early days of software development, that’s how software testing went. Today, however, software testing is a sophisticated science that ensures the applications we rely on function smoothly and securely. Let’s take a trip down memory lane and explore how software testing has evolved, using some relatable real-life references.

The Early Days: Bug Bashing and Chaos

In the 1960s and 70s, software testing was a wild west. With limited resources and methodologies, testing often involved large groups manually clicking through features, hoping to find bugs. This chaotic approach, sometimes called “bug bashing,” resembled students cramming for an exam the night before – stressful, inefficient, and prone to errors.

Example: Remember that time you “tested” your school project by staying up all night frantically rewriting it before the presentation? That’s bug bashing in a nutshell!

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The Rise of Structure: Methodologies and Testing Phases

The 80s and 90s saw the introduction of structured methodologies like the Waterfall model. This brought some order to the testing process with defined phases like unit testing, integration testing, and system testing. Imagine building a house with a blueprint – a much more organized and predictable approach.

Example: Think of building a Lego® set. First, you count up all the pieces (unit testing). Then, you connect the smaller sections (integration testing). Finally, you assemble the entire model to ensure everything works together (system testing).

The Automation Revolution: Efficiency and Beyond

The 21st century ushered in the age of automation. Repetitive manual testing tasks were replaced by automated scripts, freeing up testers to focus on more complex scenarios. This is like having a robot vacuum cleaner – it takes care of the mundane tasks, allowing you to tackle more challenging cleaning projects.

Example: Imagine ordering food online. In the past, you might have called the restaurant directly (manual testing). Today, with online ordering systems, the process is automated, freeing you up to browse the menu and customize your order (focusing on complex choices).

The Future of Testing: AI, Continuous Integration, and Beyond

The future of software testing is brimming with exciting possibilities. Artificial intelligence (AI) is poised to play a bigger role, helping identify patterns and predicting potential issues. Continuous integration (CI)/Continuous delivery (CD) pipelines will further integrate testing into the development process, ensuring software quality from the get-go.

Example: Think of a fitness tracker that constantly monitors your activity and provides personalized recommendations (AI). CI/CD is like having a personal chef who constantly adjusts your diet based on your daily goals and activity levels.

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Why Does Software Testing Evolution Matter?

The evolution of software testing isn’t just about efficiency; it’s about user experience and safety. By catching bugs early and ensuring software functions as intended, we avoid costly delays, frustrating crashes, and even potential security breaches. In today’s world, where software is woven into the fabric of our lives, effective testing is more important than ever.

IT professionals, those in the software testing area in particular, are focusing on areas that have always been improving but also looking at new trends:

  1. Manual to automated testing – yes, it’s still there, still evolving, and there is still tons of manual testing being done.
  2. AI – like it or loath it, AI/ML is here to stay, and while it might not be viable for all areas, it is certainly something that will help this testing area.
  3. CI/CD – while this has gone into hiding a little compared to a few years ago, it is a big part of ensuring testing is done comprehensively and across different platforms.

So, the next time you use a flawless app or enjoy a seamless online experience, remember the army of testers (and automation tools!) working tirelessly behind the scenes to make it all possible.

Damien Walsh, Director, International Solutions Engineering, SmartBear

EuroSTAR Huddle shares articles from our community. Check out our library of online talks from test experts and come together with the community in-person at the annual EuroSTAR Software Testing Conference. The EuroSTAR Conference has been running since 1993 and is the largest testing event in Europe, welcoming 1000+ software testers and QA professionals every year. 

Sustainable Software Testing – How to implement it

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Sustainability refers to the idea that resources are limited and should be used carefully, sensibly, and with consideration for long-term goals. Sustainable software development involves designing, creating, testing, and maintaining software with the aim of minimising negative impacts on the environment, society, and the economy, thereby ensuring its long-term viability. Testing software in a manner aligned with sustainable principles is known as sustainable software testing. The following key topics will explore how sustainable software testing can be implemented, and its contribution enhanced:

  • Green Software Testing Practices
  • Risk-Based Testing (RBT) Strategies
  • Resource Optimisation
  • Testing Environments
  • Packaged Solutions
  • Test Automation
  • Remote and Off-Peak Testing
  • Software Waste
  • Net Zero Testing

Green Software Testing Practices:

An approach to software development called “green software development,” sometimes referred to as “sustainable software development,” emphasises environmental sustainability and reduces the impact of software on the environment throughout its entire lifecycle. The main objective of green software testing approaches is to minimise the harmful environmental effects of software testing. Achieving this goal requires understanding the energy consumed, resources utilised, and waste generated during testing.

Some commonly used fundamental green software testing practices include early problem detection in the development cycle, test environment optimisation (including reducing or eliminating the number of test environments), test automation, decommissioning redundant test resources, and resource optimisation.

By adopting green testing techniques, you can significantly reduce the environmental impact of software testing. Software testing, in turn, can support green development techniques by creating reusable test artefacts and optimising testing processes. Cleaner testing methods are typically more efficient, producing software that is less harmful to the environment, with minimal energy use and fewer resources required.

Shutting down non-production servers and test environments during off-peak hours (e.g. 8pm–6am) can be an effective approach to improving your organisation’s sustainability efforts and reducing its carbon footprint. This is especially beneficial, as idle servers continue to consume a significant amount of power. Even switching off production servers over the weekend (or for an alternative agreed period of time) for systems with the lowest business criticality (BC) can have a considerable impact on the organisation’s efforts to achieve sustainability.

Risk based Testing (RBT) Strategies:

Risk-based testing is a methodology where testing efforts are prioritised based on the likelihood and impact of potential failures (risks). This approach ensures that the most critical functionalities are thoroughly tested, but only when necessary, reducing both the risk of major system failures and the amount of testing time. By focusing testing efforts on high-risk areas, resources are optimised, leading to reduced energy consumption during the testing phase. Early identification and mitigation of high-risk issues contribute to long-term software stability, aligning with sustainability goals.

Risk-based testing plays an important role in the sustainable software testing domain. Integrating risk-based testing with sustainable practices creates a synergy that enhances both the overall quality and environmental friendliness of software testing. By efficiently identifying and addressing risks while minimising the environmental impact of testing processes, testing teams can contribute to the creation of resilient and sustainable software solutions.

Remember that the risk of some activities failing may be so low that no tests are necessary. If the impact of a defect in production is negligible, it is better to avoid testing, as this reduces costs and supports sustainable goals. It is important that risks are regularly reviewed and updated, and the testing approach is amended accordingly.

Resource Optimisation:

Sustainable software development and testing should utilise all resources efficiently. Optimising resources and promoting sustainability are crucial aspects of responsible software development. Consolidating test environments, virtualising resources, or using cloud-based solutions for testing will increase efficiency and reduce the physical hardware footprint. This involves hardware, software, and components such as memory and CPU, among others. Energy usage during the testing phase can be minimised by optimising resources, scheduling tests (e.g., during off-peak hours, nights, or weekends), and concentrating testing efforts on key areas.

Right-sizing testing resources (downsizing or upsizing) and using appropriate resources are key factors in achieving sustainable goals. Right-sizing hardware, software, and infrastructure while ensuring sustainable testing practices not only saves costs but also minimises your environmental impact, such as by identifying idle or underutilised resources. Optimising testing teams and resources is not just about numbers; it’s about making strategic decisions that balance business needs, project status, testing requirements, employee well-being, and environmental responsibility. Right-sizing goes beyond merely increasing or decreasing resources and headcount; it’s about doing so sustainably and responsibly, considering both testing needs and team well-being. Balancing downsizing and upsizing while prioritising sustainable testing requires a strategic approach at the organisational level.

It is important to periodically audit the test approach and requirements, updating or removing unused or outdated tests. This frees up resources and enhances the sustainability of the test systems. Cloud testing platforms and environments offer flexibility and scalability, allowing resources to be provisioned only when needed. This eliminates over-provisioning of infrastructure, reducing both hardware and energy consumption.

Test data optimisation is another effective method to minimise data footprints and redundancy, supporting sustainability principles. This involves refreshing the test environment as needed with the right amount of data. A functional testing cycle may not require a full data refresh compared to a testing environment used for performance or volume testing. It is also important to clean up the environment after testing.

One practical way to enhance your company’s sustainability efforts and lower its carbon footprint is to turn off non-production servers during off-peak hours (e.g., 8 pm to 6 am). The main advantage is that idle servers still consume significant amounts of electricity. Research indicates that a large portion of an organisation’s energy usage is attributable to its IT infrastructure, and shutting down non-essential servers can lead to substantial energy savings. Reduced energy consumption directly lowers electricity costs. While exact savings may vary depending on factors such as server location and size, this can still be a significant cost-saving strategy. Lowering your company’s energy usage immediately helps to reduce its carbon footprint and lessen its impact on climate change. However, be aware that servers may require time to restart, which could result in delays, increased power consumption, and other environmental effects. Careful planning and automation techniques are essential to ensure that shutdown and startup procedures run smoothly without human intervention, effectively implementing this strategy. Even turning off production servers over weekends (or for a set period) for systems with the lowest business criticality (BC) can significantly contribute to the organisation’s sustainability targets. For instance, if a company can operate without a BC4 (lowest BC) system for a few days, it may not need to power it over the weekend. If it is not possible to completely shut down non-production servers, alternative options should be considered. Most modern OS systems and cloud providers offer power management capabilities that enable servers to enter low-power states when idle, greatly reducing energy consumption. Which strategy is best for you will depend on your priorities and specific needs. By carefully weighing the potential benefits and drawbacks, you can increase your organisation’s sustainability while maintaining efficient development and testing processes.

An optimised testing approach, coupled with effective strategies, plays a significant role in achieving sustainable testing goals. Utilising off-the-shelf product features, including the product’s built-in automated testing suite, will help reduce costs and support sustainability goals. It may be possible to avoid performance and volume testing, as well as accessibility testing, by reviewing the information provided by the software vendor against the implementation architecture and design. For example, an off-the-shelf product with W3C AA compliance may not require W3C AA accessibility testing if customisation and configuration during implementation are minimal.

Note: To assist everyone in creating a web that adheres to the ideals of accessibility, internationalisation, privacy, and security, the World Wide Web Consortium (W3C) creates standards and recommendations. There are three levels in WCAG: Level A (the lowest level), Level AA, and Level AAA (the highest level). These are usually pronounced as ‘single A’, ‘double A’, and ‘triple A’. Conformance at higher levels also indicates conformance at lower levels.

Testing Environments:

Creating sustainable testing environments can contribute to achieving overall sustainability goals. Utilising energy-efficient hardware and optimising test environments can reduce the environmental footprint of testing. This includes decommissioning unused environments and, in some cases, not using a dedicated testing environment at all (i.e., testing on production). Large programmes and enterprise solutions often maintain multiple Development, System, Integration, Non-Functional, UAT, Training, and Pre-Production testing environments. Maintaining multiple environments is often a resource- and cost-intensive process.

Cloud testing platforms and environments offer flexibility and scalability, enabling the provision of resources only when needed. This eliminates over-provisioning of infrastructure, reducing both hardware and energy consumption. However, it is important to optimise infrastructure usage. According to a major study by IDC, 64% of global organisations spend more on cloud than originally budgeted, and 21% of mature cloud users in Europe admitted they do not know how much money they are wasting on public cloud services. Controlling rapidly growing cloud costs is now the top priority and challenge of cloud adoption (State of Cloud Report, Flexera, 2023).

Leveraging virtualisation technologies and cloud-based testing platforms can contribute to sustainability by reducing the need for physical hardware and infrastructure, thus lowering energy consumption and resource usage. Creating green testing environments involves employing eco-friendly practices, such as energy-efficient data centres and responsible disposal of hardware, to support the testing process. Sustainable software testing aims to use resources such as hardware, test environments, personnel, and testing tools efficiently to minimise waste and reduce the environmental impact associated with testing processes.

Packaged Solutions:

A packaged solution is designed to fulfil a specific need or address a particular issue. It may consist of several components, including services, support, software, and training. Packaged software, sometimes referred to as off-the-shelf software, can be implemented more quickly, at a lower cost, and with less environmental impact than custom software.

When compared to custom development, a packaged software solution saves time and money while still providing a dependable, high-quality software product. The use of reusable test frameworks and scripts reduces the need to create new tests for every product update. By focusing on essential features during testing, the test suite can remain relevant even when minor feature additions are made to the software. This approach makes the process more sustainable in the long term by reducing rework and streamlining future testing efforts.

There are advantages to implementing off-the-shelf products (e.g., SAP), but some solutions can become bloatware if software providers continually update their products with new features to stay competitive and maintain or extend their market share.

Test Automation:

Software test automation makes a significant contribution to sustainability in several ways. By automating repetitive and time-consuming test cases, tests can be run faster and more efficiently, requiring fewer servers and workstations. Automation often involves the use of specialised testing frameworks and tools with lower resource requirements compared to manual testing. This minimises software overhead and enhances overall resource efficiency and sustainability.

Automated tests can be scheduled to run during off-peak hours when energy demand is lower, taking advantage of reduced electricity rates and further minimising peak resource utilisation. Automation also decreases the time and resources needed for testing, making it a more sustainable option compared to manual testing. CI/CD and DevOps practices encourage the frequent integration and testing of code changes, enabling early issue detection and resolution. However, frequent testing can result in substantial energy, resource, and infrastructure consumption, which negatively impacts efforts to achieve sustainability goals.

Remote and Off-Peak Testing:

Remote testing can eliminate the need for a dedicated environment restricted to a specific testing type, such as performance testing or penetration testing. This approach allows for the continuous utilisation of the environment 24/7, aligning with sustainable principles. For example, the team can be optimised to conduct testing during non-office hours, or remotely test the solution from a different geographical location.

Software Waste:

Sustainable testing aims to minimise electronic waste (e-waste) by ensuring that software is thoroughly tested and free of critical defects before release. This helps prevent the need for frequent updates or replacements due to software issues. Post-launch software testing often involves monitoring for issues and collecting user feedback. By promptly addressing problems and improving user satisfaction, software can have a longer and more sustainable lifecycle. Leveraging virtualisation technologies and cloud-based testing platforms contributes to sustainability by reducing the need for physical hardware and infrastructure, thereby lowering energy consumption and hardware wastage.

Net Zero Testing:

Net zero, often referred to as carbon neutrality, refers to a state where the greenhouse gases emitted into the atmosphere are balanced by the removal of an equivalent amount of greenhouse gases. This means that while we may still be emitting some greenhouse gases, we are actively removing them from the atmosphere through various methods such as planting trees, investing in renewable energy, and utilising carbon capture and storage technologies.

Net zero sustainable software testing takes the concept of sustainable testing a step further, focusing on achieving carbon neutrality throughout the testing process. This means that any greenhouse gas emissions generated during testing are balanced by removing an equivalent amount from the atmosphere. It involves precisely calculating the carbon footprint of the entire testing process, taking into account emissions from data centres and network traffic, as well as energy use from hardware, software, and infrastructure. After conducting this assessment, testing strategies can be created to reduce emissions or identify testing activities that can be eliminated to offset greenhouse gases. Some of these strategies include reducing testing cycles and environments, using energy-efficient hardware and software, optimising resource utilisation, utilising renewable energy sources, automating tests to reduce resource consumption, optimising cloud technologies, and selecting effective testing frameworks and tools.

Synopsys:

Sustainable testing considers the environmental impact of testing activities throughout the software testing lifecycle. A well-tested software product tends to provide a better user experience. When users can accomplish tasks efficiently and without frustration, they are less likely to abandon software prematurely, thereby reducing the need to seek alternatives or updates. Sustainable software testing focuses on conducting testing activities in a manner that minimises resource consumption, reduces waste, and takes into account the environmental impact of testing processes. It aligns with broader sustainability goals and can contribute to greener software testing practices.

Software testing and sustainability may seem like two unrelated concepts, but they can be interconnected in several ways. Sustainable testing can, in turn, contribute to a greener and more environmentally responsible digital world.

It’s worth noting that “too little testing is a crime, and too much testing is a sin”—a sustainability sin against the planet and future generations. It is highly recommended to appoint a Sustainability Champion for every software development or production team to thoroughly examine requirements, solutions, architecture, test approaches, and so on, through the lens of sustainability. By embracing sustainable testing practices, you can create a win-win situation for your team, your projects, and the planet.