AI is reshaping software development, shifting work from coding to orchestration, governance, and skills evolution while ...

The purpose of tracking and monitoring software engineering metrics is to assess the current product or process performance, enhance it, and anticipate the quality after the software development ...

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

Software development and deployment cycles keep accelerating, thanks in large part to artificial intelligence (AI), which can generate code and make suggestions. Even with such hyper-productivity, IT ...

Software quality often slips not because of major flaws, but because of small cracks in the software development lifecycle ...

Last year, I wrote about the 10 ways generative AI would transform software development, including early use cases in code generation, code validation, and other improvements in the software ...

Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with content, and download exclusive resources. Traditional caching fails to stop "thundering ...

Large language models (LLMs) are ushering in a revolutionary era with their remarkable capabilities. From enhancing everyday applications to transforming complex systems, generative AI is becoming an ...

How much more productive are developers using AI coding tools? Recently, there has been a lot of speculation that AI makes developers 2x, 3x, or even 5x more productive. One report predicts a tenfold ...

Railway’s engineering team published a comprehensive guide to observability, explaining how developers and SRE teams can use logs, metrics, traces, and alerts together to understand and diagnose ...