Look to these tools to improve your AI coding practices and the quality, security, and reliability of your AI-generated code.

Learn how to evaluate AI code quality platforms using enterprise criteria including scalability, predictive insights, and business impact.

LLVM powers the core development tools, operating systems, and most applications at Apple Computer, where it long ago ...

Most organizations know they need to govern agentic output. Far fewer have a clear, practical path to doing so. Today, Sonar, a global leader in AI code verification, governance, and efficiency is ...

Shreyansh Sharma built high-performance financial data pipelines, improving accuracy, speed, scalability, and reliability for ...

Architecture reviews often only consider the structure of the software. However, it is much more efficient and effective to ...

In just its third edition, MEWA India has established itself as a leading platform for stakeholders across the nuts and dry ...

Part of the SD Times 100 2026 series. See the full SD Times 100 2026 list for every category and honoree. For most of ...

The release includes an embedded MCP server that exposes Spring project analytics to AI coding assistants, along with first-class support for Spring AI and automated property refactoring.

When code is generated faster, quality, security and maintenance issues can also move through the pipeline more quickly, so ...

Azul’s free risk assessment for Java estates addresses the blind spot that autonomous AI exploitation tools are increasingly ...

New benchmarks show semantic code graphs helping coding agents find change locations faster and complete updates more ...