DEVOPSdigest

Industry experts offer thoughtful, insightful, and often controversial predictions on how DevOps and related technologies will evolve and impact business in 2024. Part 4 covers testing.

Start with: 2024 DevOps Predictions - Part 1

Start with: 2024 DevOps Predictions - Part 2

Start with: 2024 DevOps Predictions - Part 3

GENAI DISRUPTS TESTING LANDSCAPE

The impact of AI in the quality testing space is unquestionable. The rapid advancement of GenAI will disrupt the testing landscape, enabling teams to significantly expand their testing capabilities with minimal additional resources. It will be used to facilitate automatic test creation and maintenance, address often overlooked edge cases, and rapidly generate insights to aid teams in critical decision-making processes.
Prashant Mohan
Senior Director of Product Management, SmartBear(link is external)

AI, especially Generative AI, is reshaping testing. AI tools streamline the conversion of user stories to test cases, ensuring consistency, and adaptability to changing requirements. These tools enhance product quality by covering all scenarios, including those humans might miss. Integration with management tools is becoming common, and tools using large language models are on the rise. Machine learning is also pivotal for analyzing test results, predicting defects, and enabling teams to allocate resources more efficiently.
Adnan Khan
Principal Architect, SPR(link is external)

AI & Testing: Always on Becomes the Baseline

As AI becomes increasingly embedded in software, the systems will become more autonomous, which increases risk and complexity and makes testing a real challenge. As a result, a fixed set of tests (scripts) will no longer suffice when evaluating intelligent systems; instead, AI will be needed to automatically and continuously test AI applications. The future of software testing is autonomous test design and execution.
Gareth Smith
GM Software Test Automation, Keysight Technologies(link is external)

TEST AUTOMATION IS IMPERATIVE

Test automation is no longer a "nice to have" — it is an imperative for organizations to increase productivity and improve efficiency across the software delivery pipeline in 2024. AI-powered test automation in particular not only helps to augment people and empower exploratory testers to find more bugs and issues upfront — it's also providing valuable metrics that help to define decision-making processes. Critical UX and performance issues can now be addressed through real-time tracking of key performance indicators such as network, location, response time, CPU, and more, meaning organizations everywhere can ship faster, more frequently and with greater consistency.
Bryan Cole
Director of Customer Engineering, Tricentis(link is external)

Looking ahead to 2024, companies will increasingly rely on automated testing solutions to improve efficiency and reduce manual testing efforts. AI-powered testing tools will become more prevalent, enabling faster and more accurate testing processes. Companies will seek test automation solutions that are seamlessly integrated into the DevOps process, allowing for continuous delivery of high-quality software.
James LeBlanc
VP of Product Marketing, Copado(link is external)

Autonomous testing design and reporting

We will see the first viable generation of software testing technologies that will not only execute tests on behalf of the humans but also design tests and report defects semi-autonomously.
Esko Hannula
SVP, Product Management, Copado(link is external)

HIGH DEMAND FOR SKILLS IN AI AND TESTING

While AI is helping software engineers and test automation engineers produce more code faster, it still requires the highly skilled eye of an experienced engineer to determine how good and usable the code or test is. In 2024, there will be a high demand for skilled workers with specific domain knowledge who can parse through the AI-generated output and determine if it's coherent and useful within the specific business application. Although this is necessary for developers and testers to start trusting what the AI generates, they should be wary of spending inefficient amounts of time constructing AI prompts, as this can ultimately lead to decreased levels of performance.
Alex Martins
VP, Strategy, Katalon(link is external)

AI-POWERED TESTING TOOLS FOR NON-CODERS

We're going to soon start seeing AI-powered testing tools for non-coders that focus on achieving repeatability, dependability and scalability so that testers can truly use AI as their primary testing tool, and ultimately boost their productivity.
Alex Martins
VP, Strategy, Katalon(link is external)

QUALITY ENGINEERING ACROSS THE SDLC

In 2024, we're going to see quality engineering become even more ingrained into the fabric of software testing and delivery. Today's organizations operate in a highly volatile landscape with ever-changing customer expectations and demands. To ensure success, they must rapidly produce high-quality, high-performing, highly secure software that allows them to innovate faster, increase team productivity and exceed their customer's expectations. This can be achieved if quality engineering is embraced throughout the entirety of the development lifecycle — a reality made possible through automated, end-to-end software solutions.
Mav Turner
CTO of DevOps, Tricentis(link is external)

HUB-LIKE SOLUTIONS ADDRESS MULTIPLE USE CASES

In the next 1-2 years, we'll witness a rise in the adoption of hub-like solutions designed to address multiple use cases, replacing niche products that cater to specific problems. For instance, consider the repurposing of a manual test case written in natural language into an automated test with minimal user intervention. This functional test can then be extended across various browsers and devices for cross-platform validation. Furthermore, it can be repurposed as a load test, simulating hundreds of thousands of virtual users instantly while ensuring the expected functioning of the underlying APIs.
Prashant Mohan
Senior Director of Product Management, SmartBear(link is external)

Testing Infrastructure as a Code IMPROVES QUALITY

Testing Infrastructure as a Code (TIaaS) will enable agile, scalable and cost-effective testing environments, ensuring the highest standards of quality in software and systems.
Sanjit Debroy
Global Head of Client Services, AgreeYa Solutions(link is external)

User Acceptance Testing Remains a Bottleneck

Traditional User Acceptance Testing (UAT) will continue to be a release bottleneck as IT Teams deliver digital transformation at a higher rate than ever before. This means that more business users will be brought into UAT, along with their rising expectations to easily explore applications, provide their feedback, and quickly adopt the latest and greatest releases without any issues.
James LeBlanc
VP of Product Marketing, Copado(link is external)

TESTING SHIFTS LEFT

No matter what companies learn from the TicketMaster or Southwest Airlines fiascos, apps and websites are still going to crash — but that doesn't mean teams should give up and forego performance testing. In fact, applications crash because the company didn't properly test their app's performance and instead relied on the testing that they've previously done for the load they currently handle. As we enter 2024, more companies will prioritize performance testing, with an emphasis on shift left testing. Shift left testing, when testing is done while code is still being written instead of waiting to test at the end of development, is a trend that has gained momentum over the last decade, but performance testing is catching up to functional testing. Testing early, and testing an application's individual components or services, allows teams to catch problems faster, resulting in a more reliable test and therefore better app experience for end-users.
Stephen Feloney
VP of Products — Continuous Testing, Perforce Software(link is external)

Go to: 2024 DevOps Predictions - Part 5, covering the impact of AI on DevOps and development.