Scoring Function API for Domain-Specific Language Integration
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Solution Overview
Problem
The existing method of reimplementing scoring functions in general-purpose languages from domain-specific languages is time-consuming, difficult to test, and prone to errors, leading to inaccurate results and increased costs due to lack of shared context and common testing infrastructure across different applications.
Innovation Solution
A multipartite system with a presentation layer and a scoring layer that communicate through a prescribed API, allowing the scoring function to run in its original domain-specific language, reducing the need for reimplementation and enabling easier debugging and sharing of knowledge among teams.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If scoring functions are reimplemented in general-purpose languages from domain-specific languages, then the scoring function can be integrated into larger systems, but the deployment time increases and accuracy may be compromised
Solution Approach 1:
The patent introduces an intermediary layer that allows domain-specific language scoring functions to communicate with general-purpose systems without requiring reimplementation. This mediator enables integration while preserving the original scoring logic and reducing deployment time.
Solution Approach 2:
The system is divided into separate components: the domain-specific scoring function module and the general-purpose system interface. This segmentation allows each to operate independently with well-defined interfaces, enabling integration without forcing reimplementation of the entire scoring function.
2Adaptability or versatility
If scoring functions are reimplemented in general-purpose languages, then integration with larger systems is enabled, but testing difficulty increases
Solution Approach 1:
The patent creates a copy of the scoring function interface that works natively in the general-purpose language, allowing tests to be written in the same language as the production code. This eliminates the need to reimplement tests in domain-specific languages while maintaining testing simplicity.
3Measurement precision
If domain-specific algorithms are included in general-purpose languages, then scoring accuracy is improved, but it becomes impossible to guarantee result consistency
Solution Approach 1:
Instead of trying to embed domain-specific algorithms within general-purpose language implementations, the patent inverts the approach by allowing the domain-specific language to remain the primary implementation language and providing interfaces that work with general-purpose systems. This ensures algorithmic accuracy is preserved while enabling system integration.
4Adaptability or versatility
If scoring functions are rebuilt from scratch in each application, then customization is achieved, but costs increase due to lack of shared context
Solution Approach 1:
The patent creates a universal scoring function interface that can be used across multiple applications and domains. This single implementation serves multiple purposes, allowing customization through configuration rather than reimplementation, thereby reducing development costs while maintaining adaptability.
Data Source
AI summary
This technology relates generally to data assembly and analytics, as can be used in the personal finance and banking field, and more particularly to the field of lending and credit notification methods and systems. Embodiments of this technology provide systems and methods for creating objects which can be used in multiple implementations to generate scores.