Engineers who understand how to impose structure around model behavior play a critical role in turning experimental workflows ...

The first is the convergence of software and data engineering disciplines. The second is the rise of generative AI, which is accelerating both technical and organizational change. The Convergence Of ...

Today’s electronic systems are an increasingly complex combination of hardware and software components. They contain an ever-expanding range of functions, require more computing power, have to operate ...

Heavy machinery is entering a new phase where hydraulics, electronics and embedded software are engineered as one integrated system. Using model-based systems engineering (MBSE) as a framework to ...

To date, vibe coding platforms have largely relied on existing large language models (LLMs) to help write code. However, writing code is only one of many different tasks developers need to perform to ...

Formal methods represent a rigorous suite of mathematical techniques designed to specify, develop and verify system models with a high degree of reliability. In system modelling, these methods provide ...

Resolving AI agent context limits is the next aim for engineering leaders trying to guarantee better software output.

Although digital engineering has been around for years, its use within the Pentagon has been limited. The T-7A Red Hawk is one of only a handful of programs described as “radically digital." (Boeing) ...

Software that rewrites and improves its own code is emerging as one of the most consequential developments in artificial intelligence, pushing the boundaries of how digital systems are designed, ...

The so-called V-model provides many benefits for organizing the system engineering perspective by depicting the orderly progression, from requirements definition to system-level specification, ...