Tag: Software Testing
Turning testing into context for AI development
Test artifacts and execution evidence give AI the product context it needs to build toward expected behavior and reduce costly rework.
Test evidence vs. test activity: What auditors actually want from your automation
Running tests isn't the same as proving compliance. Auditors need context on test design, ownership and maintenance too.
Testing should guide AI, not just check its work
Connecting AI to test artifacts and execution evidence turns individual coding tasks into a continuous, context-aware SDLC workflow.
The evolution of test management: How AI is shaping the next chapter
As software development accelerates with AI, test management must evolve to maintain code quality and prevent bottlenecks across release cycles.
Scale software automation with AI assisted code tools
Using AI to automate repetitive boilerplate setup helps QA engineering teams eliminate pipeline friction, scale workflows, and improve test quality.
In regulated industries, faster testing still has to be defensible
Devs must balance the pressure for faster AI driven releases with the strict requirements for documented validation and clear audit trails.
Why AI Testing Demands Multi-Dimensional Evaluation
Traditional pass or fail testing models fail to capture the probabilistic nature of AI. Teams must shift to multi-dimensional scoring for quality.
The software leader’s guide to conducting a successful code audit
Learn why a 2026 code audit is essential for managing technical debt, improving security, and preparing for M&A.
AI adoption curves at the speed of compliance
Here's how software testing and quality practices can keep AI moving without losing control.
Quality at scale: The next phase of GenAI in software testing
When evaluating AI for testing, prioritize approaches that keep teams in control and maintain end-to-end testing connectivity.
The new QA playbook: Leveraging AI to amplify expertise, not replace it
Discover how to build AI literacy and effective governance to ensure your products are faster and more reliable.
Long live the human tester: QA in a post-AI world
Today's coding trends promise speed, but bring new risks: hidden flaws, unpredictable behaviors, and edge cases that automation alone can’t catch.
Are we sacrificing security for velocity with AI?
Empowered by AI, developers are producing code at a rate that traditional security checks cannot match.
Closing the QA talent gap: Test management tools as a solution
Given the constraints of the current labor market, optimizing software testing and quality processes has become essential for businesses.
SmartBear Acquires QMetry, Extending AI and Test Management Solutions
Acquisition further empowers development teams to accelerate feature delivery and strengthen SmartBear Test Hub offering.
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