Declarative Content Engine for Cross-Platform Asset Adaptation
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Solution Overview
Problem
Developing a method for computing device platforms to efficiently support diverse user experiences across various heterogeneous platforms without requiring extensive re-design of computer applications and to leverage platform-specific hardware capabilities, while minimizing the need for multiple application code bases and programming efforts.
Innovation Solution
A system and method for storage retrieval that utilizes a content repository and declarative content engine to partition application content into assets, score and select assets based on variability tags, and transmit optimized content to computing devices, enabling a common declarative content expression across platforms and dynamic user experience adaptation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a software vendor creates separate application code bases for each platform, then the application can be optimized for each platform's hardware capabilities, but the development and maintenance complexity increases significantly
Solution Approach 1:
The patent segments the application into a platform-independent core logic layer and platform-specific asset layers. The core logic remains unified across platforms, while platform-specific hardware capabilities are accessed through separate asset modules that can be independently developed and maintained. This segmentation allows optimization for each platform without requiring complete separate code bases.
Solution Approach 2:
The patent introduces an intermediary execution environment layer that sits between the application logic and platform hardware. This intermediary provides standardized interfaces that allow the application to access platform-specific capabilities without direct platform-dependent code, thereby maintaining code reusability while enabling hardware optimization.
2Ease of manufacture
If a software vendor uses a single application version with an execution environment layer, then the development effort is reduced, but the application cannot leverage platform-specific hardware capabilities
Solution Approach 1:
The patent divides the application into universal core functionality that runs on any platform and platform-specific asset modules that contain hardware capability definitions. This segmentation enables a single code base to be maintained while still allowing access to platform-specific features through the modular asset structure.
Solution Approach 2:
The patent implements dynamic asset selection where the execution environment automatically selects appropriate platform-specific assets based on the detected hardware configuration. This dynamic adaptation allows the single application version to leverage platform-specific capabilities without requiring manual configuration or separate code paths.
3Ease of operation
If platform-specific optimization is implemented, then user experience is improved for each platform, but the number of application versions and maintenance burden increases
Solution Approach 1:
The patent creates a universal application framework that can serve multiple platforms through a single code base. The framework includes standardized interfaces and asset management capabilities that work across different platforms, allowing one application version to provide optimized user experiences on each platform without requiring separate maintenance cycles.
Solution Approach 2:
The patent uses asset templates and copying mechanisms where platform-specific optimizations are defined once as reusable asset modules. These assets can be copied and adapted across different platforms without modifying the core application logic, thereby reducing maintenance effort while preserving platform-specific user experience optimizations.
Data Source
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AI summary
A method for storage retrieval, including receiving a request for application content. The request includes a first field identifier. The method further includes submitting a query to a content repository, for each asset including the first field identifier, receiving a first asset including the first field identifier and a second asset including the first field identifier, and extracting a first variability tag from the first asset and a second variability tag from the second asset based on the first asset having a matching asset property value to the second asset. The first asset and second asset are scored based at least on the first variability tag and at least on the second variability tag to obtain a first and second score, respectively. The method further includes selecting the first asset based on the first score and the second score, and transmitting the first asset as the application content.