Build reusable validators from small building blocks using the
    base pipe operator. Define runtime contracts once with 'restrict()' and
    enforce them anywhere in code. Validators compose naturally, support
    dependent rules via formulas, and produce clear, path-aware error
    messages. No DSL, no operator overloading, just idiomatic R.

Allow for easy-to-use testing or evaluating of linear equality and inequality restrictions about parameters and effects in (generalized) linear statistical models.

Allows to easily create high-performance full featured HTTP APIs from R
  functions. Provides high-level classes such as 'Request', 'Response',
  'Application', 'Middleware' in order to streamline server side
  application development. Out of the box allows to serve requests using
  'Rserve' package, but flexible enough to integrate with other HTTP servers
  such as 'httpuv'.

Allows wrapping values in success() and failure() types to capture 
    the result of operations, along with any status codes. Risky expressions can be 
    wrapped in as_result() and functions wrapped in result() to catch errors
    and assign the relevant result types. Monadic functions can be bound together 
    as pipelines or transaction scripts using then_try(), to gracefully handle 
    errors at any step.

Lightweight helpers for checking whether empirical results remain 
    substantively unchanged across code revisions, platform differences, 
    and package updates. The package supports regression-style testing of 
    derived datasets, statistical model outputs, tables, and plots, helping 
    researchers detect unintended result drift early and distinguish material 
    from non-material changes in empirical workflows.

Database data model management utilities for R packages in the Observational Health Data Sciences and
    Informatics programme. 'ResultModelManager' provides utility functions to allow package
    maintainers to migrate existing SQL database models, export and import results in consistent patterns.