Real-world deployments show 40% test cycle efficiency improvement, 50% faster regression testing, and 36% infrastructure cost savings.

A technical preview promises to take on the unrewarding work in DevOps, but questions remain about controls over costs and access.

While more product executives reposition AI sandbox management as a core, centralized platform product, this evolution can be a complex and demanding transition.

Generative AI automation targets coding, debugging, documentation, and testing workflows in SDLC processes SAN JOSE, ...

Microsoft is previewing an open-source command-line tool designed to speed up Windows application development, testing, and delivery.

Modern software teams work under constant time pressure. They maintain codebases, manage infrastructure, monitor systems, and ...

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Ideally, security issues should be identified during the coding process. That is the goal of Checkmarx Developer Assist ...

Quality engineering must evolve faster than code; otherwise, agentic AI will move quickly, learn rapidly and fail expensively.

Combine AI-generated tests with intelligent test selection to manage large regression suites and speed up feedback ...

Leapwork recently released new research showing that while confidence in AI-driven software testing is growing rapidly, accuracy, stability, and ongoing manual effort remain decisive factors in how ...