Model Artifact Validation With Dynamic Component Checks
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Solution Overview
Problem
The generation of model artifacts is error-prone due to inclusion of incorrect components, missing files, syntax errors, and non-conformance to standards, leading to deployment failures and inefficiencies, and manual validation is inadequate for complex models.
Innovation Solution
A model validation system that automatically validates model artifacts and components using introspection to dynamically determine validation checks based on metadata, generating a report with results and suggested actions, and optionally performing corrective actions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual validation is performed on model artifacts, then validation can be done for simple models, but it becomes inadequate and error-prone for complex models
Solution Approach 1:
The patent replaces manual validation (mechanical human inspection) with an automated validation system that uses software agents to extract metadata, determine validation checks, and execute validation routines. This substitution enables reliable validation of complex models that cannot be manually validated, while maintaining high reliability through systematic automated checking of artifact components, files, and configurations.
2Reliability
If comprehensive validation checks are performed on model artifacts, then deployment reliability improves, but validation time and complexity increase
Solution Approach 1:
The validation system performs preliminary extraction of metadata from model artifacts before executing validation checks. By预先 extracting and analyzing artifact information, the system can determine which specific validation checks are needed, avoiding unnecessary validation steps and reducing overall validation time while maintaining comprehensive coverage of critical deployment requirements.
Solution Approach 2:
The validation system dynamically determines validation checks based on the extracted metadata and specific characteristics of each model artifact. Rather than applying a static, one-size-fits-all validation approach, the system adapts the validation routine to the particular artifact being validated, performing comprehensive checks where needed and skipping unnecessary checks to optimize validation time.
3Productivity
If automated validation systems are implemented, then validation scalability improves, but system complexity increases
Solution Approach 1:
The validation system is segmented into distinct functional components: a metadata extraction agent that extracts artifact information, a validation check determination module that selects appropriate checks based on metadata, and a validation execution module that performs the actual validation. This segmentation enables the system to handle complex validation tasks through coordinated simple components, improving scalability while managing system complexity through modular design.
Solution Approach 2:
The patent introduces metadata as an intermediary layer between the model artifact and the validation checks. The metadata extraction agent transforms the artifact into structured metadata that the validation system can process, acting as a mediator that simplifies the interaction between diverse artifacts and the validation mechanism, thereby improving scalability without proportionally increasing system complexity.
Data Source
AI summary
A model validation system is described that is configured to automatically validate model artifacts corresponding to models. For a model artifact being validated, the model validation system is configured to dynamically determine the validation checks to be performed for the model artifact, where the validation checks include various validation checks to be performed at the model artifact level and also for individual components included in the model artifact. The checks to be performed are dynamically determined based upon the attributes of the model artifact and of the components within the model artifact. The system is configured to generate a validation report that comprises information regarding the checks performed and the results generated from performing the various validation checks. The validation report may also include information suggesting actions for passing checks that result in a failed check, or for improving the scores of certain validation checks.