Category
Description
Language elements have a large influence on understanding of data pipeline code. General-purpose programming languages such as Python must by necessity also provide general-purpose language elements while domain-specific languages can express domain concepts directly as language elements.
The blocks and pipe structure that aligns closely with how users visualize data pipelines can be directly found in the language elements provided by Jayvee, making it easier to understand data pipelines.
Other language elements such as missing import statements due to no library use or no variables in Jayvee show mixed effects on understanding.
Content
- PL6.1 - Advanced programming concepts like map are hard to understand
- PL6.2 - Domain-specific language elements like blocks make Jayvee easy to understand
- PL6.3 - Jayvee language elements (blocks, value types, constraints) are unusual and need to be learned
- PL6.4 - Meta infos (e.g., imports, library names) obscure the logic of the pipeline
- PL6.5 - Mixed effects of no variables in Jayvee