Software Testing Trends for 2023

Coming out of 2022, and into 2023, there’s no doubt that technology is still developing at an astounding pace. Software testing principles and tools are evolving to keep up, at a time when software creation and iteration must achieve the ultimate in performance and in cyber safety.

Software testing trends in 2023 will continue to feature themes common from previous years, such as automation, continuous improvement, DevOps, data, and cloud developments. They will also be greatly influenced by a defining moment for AI, the launch of ChatGPT. And also, by mounting cybersecurity concerns, during the current period of geopolitical turmoil.

Testing constitutes a significant proportion of software development activity amidst a shift-left to ensure bugs and vulnerabilities are rectified before launch, rather than costly-post launch amendments. Let’s summarize software testing themes likely to be prevalent this coming year.


Companies are already investigating the use of AI and ML to improve software testing practices. Algorithms can be developed for better scripting and test cases, test data and even reporting. Predictive modelling can help to plan testing and smart analytics can help to understand risk. 

Enter ChatGPT and its competitors that will surely shortly follow, and 2023 will see more use of AI for scripting, prediction, and risk identification. AI is far from perfect but its speed, demonstrated by ChatGPT, already makes it a tool that can support the work of software developers. 

Katalon executives and researchers predict that AI-enabled software quality management platforms will become easier to use this year, and testers will use AI powered tools for automated test generation. 

Test Automation

Driven by recession fears, corporate downsizing, and a greater need for efficiency, automation is a continuing trend in software testing. Where testing or reporting can be automated, especially in existing systems, there are substantial time savings. Developers can step back from legwork and concentrate on higher-level issues. Automating testing using AI and ML can cover much more ground, include more data in the testing process, and increase the frequency of testing and reporting. 

Big Data Testing

Gigantic datasets are more and more common, and their size dictates a need for scalable testing techniques and testing frameworks specific to big data. These techniques and frameworks will continue to be deployed and developed in coming years and both performance and security testing for such silos, systems, and software is vital. 

DevOps/Continuous Performance Testing

DevOps agile methodologies are increasing relevant for software testing. Coupled with the shift-left evolution in testing, DevOps encourages continuous performance testing and live testing of new developments whilst they are in production. The goal is to identify and rectify problems early and deliver a better product to market, faster. The term coined for Agile and DevOps in reducing the period of time from development to launch or operation is “Quality of Speed.” Furthermore, QAOps is a progression of DevOps and testing where quality assurance is at the core of product development. 

IoT Testing

In an ever connected and smarter world, IoT testing must feature strongly both to ensure the security of data as it passes from device to device but also to ensure compatibility, reliability and scalability for devices and software. As with a need for software compatibility for mobile devices, IoT software must operate perfectly in a variety of environments.

Mobile Device and Resiliency Testing

Even if a piece of software doesn’t have a specific mobile application, there’s every chance it will be accessed in some way via a mobile device. 62% of all web traffic now comes from mobile so compatibility testing must be factored into the software development process. 

Resilience testing is especially important for mobile, where consumer products have little technical support so must work every time. Consumers have minimal patience for malfunctions and disruptions. 

Resiliency testing can cover what happens in an application if connectivity drops or software is interrupted, how notifications work, and what happens if an app fails completely. 

Blockchain Testing

A substantial 44% of the top 100 publicly listed companies in the US are already using blockchain technology in some way so it’s no surprise that blockchain testing will be an expanding theme in 2023. Blockchain testing must ensure the security of these network’s distributed ledger technologies as well as help develop their capacity and scalability. 

Integration Testing

From IoT, to mobile, to blockchain, and to AI, all these technologies and the software that empowers them must communicate, and often integrate. Software systems within a corporate stack must work hand in had with each other. Consumer software must be bug-free on every device. IoT devices will only remain smart if the transfer of data and commands is fluent. So, integration testing will once again be a common theme in 2023. 

Security TestingCybersecurity must permeate every aspect of technology in the same way that technology is becoming embedded in our every activity. The World Economic Forum’s latest Global Cybersecurity Outlook delivered a chilling statistic: 93% of cyber leaders and 86% of business leaders believe a systemic cybersecurity event could occur in the next two years. This fear is greatly influenced by geopolitical instability, which accelerated greatly in 2022. It will likely impel a stronger push for better cybersecurity. Cybersecurity testing identifies vulnerabilities in software that could be exploited by hackers and viruses and any malicious actors behind them, therefore it’s critical to prevent security and data breaches.

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