Amazon Web Services (AWS) announced the general availability of Amazon Q, a generative artificial intelligence (AI)-powered assistant for accelerating software development and leveraging companies’ internal data.
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
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
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
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
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
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
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
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
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
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
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
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
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
Go to: 2024 DevOps Predictions - Part 5, covering the impact of AI on DevOps and development.
Industry News
Red Hat announced the general availability of Red Hat Enterprise Linux 9.4, the latest version of the enterprise Linux platform.
ActiveState unveiled Get Current, Stay Current (GCSC) – a continuous code refactoring service that deals with breaking changes so enterprises can stay current with the pace of open source.
Lineaje released Open-Source Manager (OSM), a solution to bring transparency to open-source software components in applications and proactively manage and mitigate associated risks.
Synopsys announced the availability of Polaris Assist, an AI-powered application security assistant on the Synopsys Polaris Software Integrity Platform®.
Backslash Security announced the findings of its GPT-4 developer simulation exercise, designed and conducted by the Backslash Research Team, to identify security issues associated with LLM-generated code. The Backslash platform offers several core capabilities that address growing security concerns around AI-generated code, including open source code reachability analysis and phantom package visibility capabilities.
Azul announced that Azul Intelligence Cloud, Azul’s cloud analytics solution -- which provides actionable intelligence from production Java runtime data to dramatically boost developer productivity -- now supports Oracle JDK and any OpenJDK-based JVM (Java Virtual Machine) from any vendor or distribution.
F5 announced new security offerings: F5 Distributed Cloud Services Web Application Scanning, BIG-IP Next Web Application Firewall (WAF), and NGINX App Protect for open source deployments.
Code Intelligence announced a new feature to CI Sense, a scalable fuzzing platform for continuous testing.
WSO2 is adding new capabilities for WSO2 API Manager, WSO2 API Platform for Kubernetes (WSO2 APK), and WSO2 Micro Integrator.
OpenText™ announced a solution to long-standing open source intake challenges, OpenText Debricked Open Source Select.
ThreatX has extended its Runtime API and Application Protection (RAAP) offering to provide always-active API security from development to runtime, spanning vulnerability detection at Dev phase to protection at SecOps phase of the software lifecycle.
Canonical announced the release of Ubuntu 24.04 LTS, codenamed “Noble Numbat.”
JFrog announced a new machine learning (ML) lifecycle integration between JFrog Artifactory and MLflow, an open source software platform originally developed by Databricks.
Copado announced the general availability of Test Copilot, the AI-powered test creation assistant.