jmeter-correlation-naming

Standardize JMeter correlation variable names by translating correlation_spec.json data into descriptive, snake_case variables. The engine auto-generates names from source fields, URLs, and step context to ensure scripts remain readable and reliable.

Prevent variable name collisions in JMeter parameterization by enforcing strict uniqueness and naming conventions. The engine processes correlation specifications to ensure every generated variable name is unique and adheres to a standardized format.

Generate a correlation_naming.json file by running the naming engine on your existing correlation_spec.json. This produces the structured naming output required for consistent parameterization in automated performance-testing pipelines.

Yes, you can apply custom naming mappings for JMeter correlations by defining them in correlation_config.yaml. The engine respects these custom_mappings while enforcing naming conventions and handling both found and orphan correlations.

Handle orphan correlations during JMeter network analysis by running the naming engine's review scenarios. It identifies orphaned correlations alongside found ones, enforcing unique snake_case names and providing guidance for validation and reuse.

Yes, this correlation naming approach works without external dependencies. It directly processes correlation_spec.json files and applies custom mappings from correlation_config.yaml to generate standardized variable names for your JMeter scripts.