Device Configuration Parsing with Unified Data Models

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Solution Overview

Problem

Existing systems face challenges in parsing device configurations from diverse vendors due to varying API formats, requiring specialized parsing logic, complex batch processing, and maintaining feature parity, with tools like Antlr and Jolt having limitations in scalability and efficiency.

Innovation Solution

A simplified datamodel-based approach using REST API responses for parsing device configurations, involving a processor-implemented method that transforms vendor-specific formats into a common domain object model, enhances data with metadata and unique identifiers, and implements back-off strategies to improve performance and flexibility.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Ease of manufacture

If Antlr is used for configuration parsing, then parsing capability is provided, but system complexity and learning curve increase

Engineering Contradiction:
Improveparsing capabilityVSAvoidsystem complexity
Core Design Contradiction:
Ease of manufactureVSDevice complexity

Solution Approach 1:

The patent introduces an intermediary layer (the parsing system with standardized data models and configuration files) between the diverse vendor APIs and the target application. This intermediary handles the complexity of multiple API formats, allowing applications to interact with a unified interface rather than dealing with each vendor's proprietary format directly.

Inventive Principle:
Principle #24Intermediary (Mediator)

Solution Approach 2:

The system implements universal data models and standardized configuration formats that can handle multiple vendor-specific APIs through a single unified interface. The parsing system serves multiple functions: parsing different vendor formats, validating configurations, and providing a consistent data structure to applications, thereby reducing the need for vendor-specific parsing logic.

Inventive Principle:
Principle #6Universality (Multi-functionality)

2Ease of manufacture

If Jolt library is used for JSON transformation, then transformation capability is provided, but handling complex data structures requires custom logic increasing development effort

Engineering Contradiction:
Improvetransformation capabilityVSAvoiddevelopment effort
Core Design Contradiction:
Ease of manufactureVSDevice complexity

Solution Approach 1:

The patent segments the configuration parsing process into distinct, manageable components: data model definition, configuration file parsing, validation rules, and transformation logic. Each component is independently configurable and can be developed, tested, and maintained separately, reducing the complexity of handling complex data structures.

Inventive Principle:
Principle #1Segmentation

Solution Approach 2:

The system uses configurable parameters and metadata in the data models to automatically handle complex transformations. By defining field types, relationships, and validation rules as configurable parameters, the system adapts to different data structures without requiring custom logic for each case, thereby reducing development effort.

Inventive Principle:
Principle #35Parameter changes

3Measurement precision

If specialized parsing logic is developed for each vendor's API format, then accurate parsing is achieved, but development time and maintenance burden increase

Engineering Contradiction:
Improveparsing accuracyVSAvoiddevelopment time
Core Design Contradiction:
Measurement precisionVSLoss of time

Solution Approach 1:

The patent implements universal data models and standardized parsing mechanisms that can accurately parse multiple vendor-specific API formats through a single unified system. The data models are designed to be vendor-agnostic while maintaining the ability to represent vendor-specific features, thereby achieving parsing accuracy without requiring separate development for each vendor.

Inventive Principle:
Principle #6Universality (Multi-functionality)

Solution Approach 2:

The system employs dynamic configuration loading and adaptive parsing logic that can automatically adjust to different vendor formats based on runtime configuration. This dynamic approach allows the system to maintain high parsing accuracy for various vendors while using a single codebase, significantly reducing development time and maintenance burden compared to static vendor-specific implementations.

Inventive Principle:
Principle #15Dynamics

4Reliability

If batch processing and pagination handling are implemented for large datasets, then data completeness is improved, but system complexity and development timeline extend

Engineering Contradiction:
Improvedata completenessVSAvoidsystem complexity
Core Design Contradiction:
ReliabilityVSDevice complexity

Solution Approach 1:

The patent segments large datasets into manageable batches with proper pagination handling. The system processes data in discrete units (pages or batches) with clear start and end points, allowing complete data retrieval without overwhelming system resources. This segmentation approach ensures data completeness while maintaining manageable system complexity through standardized batch processing interfaces.

Inventive Principle:
Principle #1Segmentation

Data Source

PatentEP4708031A1System and method for parsing device configuration
Publication Date: 2026.03.11 APPVIEWX INC
  • EP4708031A1 patent drawingFigure 1
  • EP4708031A1 patent drawingFigure 2
  • EP4708031A1 patent drawingFigure 3

AI summary

An embodiment herein provides a method and a system for parsing device configurations using a simplified datamodel-based approach. The method includes (i) receiving a parse request from one or more sources, (ii) retrieving one or more data models and respective one or more configurations from a resource, (iii) executing communications with a user device using commands retrieved from a command repository by analyzing the retrieved one or more data models, (iv) transforming a response into parsed data by analyzing grammar configuration, (v) enhancing the parsed data by analyzing enricher configuration, and (vi) framing the enhanced data into an output response, thereby parsing device configurations.