Parsedriven

Parsedriven is a software design approach in which the parsing of input data is the central driver of program flow. In a parsedriven system, parsed data determines routing, transformation, and decisions, rather than relying primarily on pre-coded sequences or event triggers.

Core ideas include treating parsers as first-class components, using schemas to validate and categorize parsed data, and employing a dispatcher or rule engine that maps data patterns to processing branches.

Architectures often deploy streaming pipelines where each stage consumes parsed data, applies transformations, and forwards enriched results to downstream components.

Applications include data ingestion and ETL that support multiple input formats, log and event analysis, configuration-driven automation, and natural language interfaces that convert user input into commands.

Benefits include modularity, easier testing of parsers, and adaptability to new input formats; drawbacks include parsing overhead, potential latency, complexity in action mapping, and security risks from processing untrusted input.

Parsedriven relates to data-driven programming, event-driven architectures, and parser combinators, and is often used alongside traditional architectures in data-centric domains. See also data-driven programming, event-driven architecture, ETL, and parser combinators.