Graphical Data Pipeline Testing With Rich Assertions
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Solution Overview
Problem
Validating data transformation processes in distributed computing environments is challenging due to the complexity of data transformations and the need to manage global variables, which is further complicated by the requirement to build tests through specific application programming interfaces.
Innovation Solution
A graphical user interface (GUI) is used to present data pipelines as graphs, allowing users to identify target pipelines, set up tests, and execute them efficiently with rich assertions, and update the pipeline or tests based on results, supporting metadata evaluations and automatic batch execution.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If tests are built through specific application programming interfaces to validate data transformation portions, then testing capability is achieved, but the complexity and difficulty of building tests increases
Solution Approach 1:
The patent introduces a visual test builder interface as an intermediary between the user and the underlying API complexity. This interface allows users to configure tests through graphical elements and visual workflows rather than directly interacting with complex programming interfaces, thereby maintaining testing capability while significantly reducing the complexity of building tests.
Solution Approach 2:
The patent replaces the mechanical system of manual API-based test construction with an automated visual interface system. The visual test builder automatically generates and manages test configurations through graphical interactions, substituting the manual, complexity-prone API programming approach with an automated system that abstracts away the underlying complexity while preserving full testing functionality.
2Reliability
If comprehensive data transformation validation is performed, then software quality is improved, but the time and resources required for testing increase
Solution Approach 1:
The patent implements preliminary action by providing templates and pre-configured test scenarios that automatically validate common data transformation patterns. This allows comprehensive validation to be performed more efficiently, as the foundational testing framework is already established and can be quickly adapted to specific validation needs without starting from scratch each time.
Solution Approach 2:
The patent applies segmentation by breaking down comprehensive data transformation validation into modular, independently configurable test units within the visual interface. Users can select and combine specific validation segments based on their needs, allowing thorough validation where required while avoiding unnecessary testing elsewhere, thus reducing overall testing time while maintaining software quality.
3Measurement precision
If detailed test configurations with rich assertions are created, then measurement precision is improved, but the complexity of test setup increases
Solution Approach 1:
The patent applies local quality by allowing users to specify detailed assertions and validation criteria only at the specific points in the data transformation pipeline where they are needed, rather than applying uniform complexity throughout. The visual interface enables precise local configuration of test parameters, assertion types, and validation rules at individual transformation steps while keeping the overall test structure simple and manageable.
Data Source
AI summary
A system for enabling testing a target data pipeline within a graphical user interface (GUI) is disclosed. The system is programmed to present a GUI. The GUI shows a data pipeline including data transforms that are related based on data dependencies as a graph. The GUI then accept user inputs to identify a target pipeline from the data pipeline and set up a test for the target pipeline. The user inputs include interacting with the graph and providing test inputs and expected outputs for the target data pipeline, including specifying in each expected output for a test output one or more assertions related to the test output. The GUI further accepts user inputs to execute the test and review test results. The GUI facilitates specifying rich assertions, determining the source of a test failure, and updating the target data pipeline or the test based on the test results.