Co-author Jon Kern says AI coding tools amplify strengths and expose weaknesses Interview Twenty-five years after 17 software ...

Test automation has become a cornerstone of modern software development. As release cycles accelerate and user expectations rise, quality assurance teams must deliver reliable results at speed. Among ...

Allocating capital to autonomous security platforms outperforms traditional consultant-driven validation models.

By integrating NVIDIA’s Physical AI into DELMIA’s Virtual Twin technology, Dassault Systèmes is moving the industry from static automation to autonomous software-defined systems that “learn” the laws ...

Security is 'dangerously behind' though, as devs 'treat it as something to solve later' 25 years after the Agile Manifesto, a group of experts hosted by one its signatories met to consider the impact ...

Testing places unique demands on AI. Errors carry real business risk, and fragile tests or slow updates can quickly erode trust in results. As a result, while momentum around AI in testing is strong, ...

New delivery model applies AI across engineering, testing, DevOps, and analytics to improve speed, transparency, and ...

The TASKING toolchain has been designed with a foundation that enables OEMs to develop functionally safe and secure systems. Modern AI capabilities are supported within the toolch ...

A machine learning (ML) model might retrain or drift between quarterly operational syncs. This means that, by the time an ...

The development process improves because it is informed by real outcomes. AI learns from what happened, and the team adjusts its inputs. This creates a flywheel effect, with each phase building on the ...