Testing is an integral part of software development, ensuring the quality, reliability, and safety of products. Today, it extends beyond IT, permeating medicine, finance, manufacturing, and even artificial intelligence. But how did testing become so important? And what awaits this profession in the future?

Testing has long transcended the boundaries of IT and has become an integral part of many industries:

• IT and software development: Testing web and mobile applications, operating systems, games, and cloud services. This includes everything from the interface to performance under load.
• Finance and banking: Testing the reliability of banking systems, payment gateways, and exchange trading algorithms. Mistakes can cost a lot of money, so testing is especially strict in this field.
• Medicine: Validating medical equipment, diagnostic software, and electronic patient records. People's health and lives depend on the quality of testing.
• Automotive industry: Testing autopilot software, onboard electronics, and safety systems. As self-driving cars become more common, the importance of testing is increasing.
• Internet of Things (IoT): Testing the firmware, security, and compatibility of smart devices, from refrigerators to industrial sensors.
• Artificial Intelligence: Validating machine learning models, checking for bias, accuracy, and ethics. For example, testing chatbots or facial recognition systems.

The interest in testing as a separate and critical discipline peaked in the 2000s and 2010s. This was a time of rapid growth for the Internet, mobile technologies, and the globalisation of IT services. Let's explore what contributed to this boom and why testing became an integral part of development.

Reasons for the growing popularity of testing

• The Internet revolution and web applications. In the early 2000s, companies were actively transitioning to online platforms, with the emergence of social media platforms (Facebook, VK), search engines (Google, Yandex), and e-commerce platforms (Amazon, Ozon). Users demanded stable services, and competition forced companies to prioritise quality. Testing has become necessary to avoid crashes, data loss, and reputational risks.
• The mobile revolution. With the advent of smartphones (the iPhone in 2007 and Android devices), there was a need to test applications on different platforms, screens, and OS versions. Testers became in demand to verify compatibility, performance, and user experience (UX).
• Agile and flexible methodologies. The traditional "waterfall" development model (where testing was conducted only at the end of the project) has given way to Agile, Scrum, and Kanban. Testing was integrated into every sprint, which required more specialists and new approaches (for example, shift-left testing — shifting testing to early stages of development).
• Cloud technologies and DevOps. With the development of cloud services (AWS, Azure) and DevOps practices, testing became an ongoing process (CI/CD). Automated tests were run with every code change, which increased the demand for automation tools (Jenkins, Selenium, JUnit) and specialists who could work with them.
• Cybersecurity and data protection. The rise of cybercrime and the tightening of data protection laws (such as the GDPR in Europe) have led companies to focus more on security testing. New areas have emerged, including pen-testing (penetration testing), fuzzing (finding vulnerabilities through incorrect input data), and code auditing.

The term "peak" does not mean that interest in testing has decreased. On the contrary, testing has become an integral part of development, but it has ceased to be a standalone "hot topic." Today, testing is a standard, not an innovation. However, new challenges (AI, quantum technologies, IoT) are opening up the next waves of development.

Yes, AI has already replaced and will continue to replace routine tasks, but not the tester as a specialist. Here's what AI can take on:

• Automated regression testing: AI can quickly run thousands of tests after each code update, compare the results, and identify deviations. This saves time and reduces the risk of missing a bug due to human error.
• Test case generation: based on code analysis or requirements, AI can suggest test cases that a human might not have thought of.
• Log analysis and anomaly detection: AI can process large amounts of logs, identify suspicious patterns, and even predict potential failures.
• Interface testing: Using computer vision, AI can check the layout, positioning of elements, color schemes, and other visual aspects of applications.

However, AI will not be able to completely replace a tester, because:

• Creativity and intuition: A human is able to come up with non-standard use cases that are not obvious to an algorithm.
• Contextual understanding: A tester takes into account business logic, user experience, and ethical nuances that AI may miss.
• Communication and analytics: A tester not only finds bugs, but also explains them to developers, suggests solutions, and analyses risks, which requires empathy and expert judgment.

Conclusion: AI will become a powerful assistant that takes over routine tasks, but the testing profession will not disappear; it will transform. In the future, specialists who can work with AI, analyse data, and make strategic decisions will be in high demand.

Testing has evolved from manual verification to a complex and multifaceted discipline. Today, it is a key element of innovation, and tomorrow, it will become even more important due to technological advancements. Testers of the future are not just bug finders, but strategists, analysts, and developers' partners who can work hand in hand with AI.

The team at ROOT CODE consists of highly qualified specialists who are ready to help test your programs for bugs and malfunctions, improve them, so that you can already launch them!