Source Code Parameter Validation via Metadata Extraction
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Solution Overview
Problem
Software developers face challenges in debugging source code due to limited capabilities of existing debugging tools, which fail to validate parameter values for external actions effectively, leading to time-consuming and error-prone debugging processes.
Innovation Solution
A system that automatically validates parameter values in source code before execution by extracting metadata from associated files, modifying definition data, and incorporating validation functions to flag invalid values and provide recommendations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If existing debugging tools are used to validate parameter values, then the debugging process can be simplified, but the validation capability for external actions is insufficient and leads to time-consuming debugging
Solution Approach 1:
The system performs parameter validation before the external action is executed by extracting metadata from the action file and automatically validating selected parameter values against the metadata definitions. This preliminary validation catches errors before execution, reducing debugging time and improving reliability.
Solution Approach 2:
The system introduces an intermediary validation layer between the source code parameter selection and the external action execution. This intermediary component extracts metadata, validates parameters automatically, and provides feedback to the developer, thereby improving both ease of operation and validation reliability.
2Reliability
If parameter validation is performed manually, then the validation process can be controlled, but it increases debugging time and effort
Solution Approach 1:
The system enables self-service validation by automatically extracting metadata from the action file and validating parameter values without requiring manual intervention. The validation process is autonomous, comparing selected parameters against extracted metadata definitions and providing automatic feedback, thereby reducing debugging time while maintaining high reliability.
Solution Approach 2:
The patent replaces manual validation mechanisms with an automated computational system. Instead of relying on developer manual checking, the system uses computer-based metadata extraction and validation algorithms to automatically verify parameter values, significantly reducing debugging time while improving validation consistency and reliability.
3Reliability
If parameter values are validated before execution, then errors can be caught early, but the validation process becomes more complex
Solution Approach 1:
The validation process is segmented into distinct modular steps: extracting metadata from the action file, retrieving metadata definitions, validating selected parameter values against the definitions, and providing feedback. This segmentation makes the complex validation process manageable and systematic, improving error detection reliability while organizing complexity into clear stages.
Solution Approach 2:
The system introduces an intermediary validation layer that sits between the source code and execution. This intermediary component handles the complexity of metadata extraction, parameter validation, and error feedback, isolating the complexity from the main execution flow and improving overall system reliability without overwhelming the developer.
Data Source
AI summary
Parameter values in source code can be automatically validated using the techniques described herein. For example, a system can receive source code that includes a call to an action. The action can have a parameter that is set to a selected value in the source code. The parameter can be defined in definition data. The system can also receive a file that separate from the source code and includes metadata for the parameter. The system can extract the metadata from the file and modify the definition data to include the metadata. The system can then execute a validation process on the selected value for the parameter. The validation process can involve retrieving the metadata from the modified definition data, evaluating the selected value using the metadata to determine whether the selected value is invalid, and if it is invalid, outputting an error notification indicating that the selected value is invalid.


