Note
This unlinked page is a template with prompts to consider when authoring release notes before promoting to a versioned page. Remove :orphan: above if promoting this page.
Version 6.24 (2026/05/15); pre-release)
Highlight: Feature A
Enabling / Accessing: Where available and how to access
Documentation: Where to learn more
Highlight: Sensitivity Analysis Chapter
Enabling / Accessing: Available in the User Manual
Highlight: JSON-format Input Files
Dakota now accepts JSON-format input files. The schema is documented in XXX. JSON support is meant to simplify incorporation of Dakota into larger workflows, its use in agentic workflows, and and as a stepping stone toward more capable Python bindings.
The capability is experimental, and we appreciate your bug reports. To fall back to the old input file reader, run Dakota with the -parser legacy command line argument.
Enabling / Accessing: Write a JSON format input file and use the -json command line argument (e.g. dakota -json dakota_in.json).
Documentation: TODO
Improvements by Category
Interfaces, Input/Output
Models
Optimization Methods
UQ Methods
MLMF Sampling
Sensitivity Analysis
The
binnedapproach to variance-based decomposition now works with discrete variables.
Miscellaneous Enhancements and Bugfixes
Deprecated and Changed
Dakota’s NIDR (New Input Deck Reader) is being deprecated and replaced with a newly written input parser. For this release, NIDR is available as a fallback. Use the command line argument -parser legacy to use it.
Compatibility
The schema for JSON input files is defined by Pydantic models, which are located at python/dakota/spec/ in the source tree. To update Dakota’s input grammar, Python >=3.9 and Pydantic >=2.12 are required.
Other Notes and Known Issues
