Compiler-Based Data Processing for Platform-Independent Serialization
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Solution Overview
Problem
Existing methods for processing data associated with computer programs, such as those in vehicles, are invasive and require meta-models, leading to increased effort and inefficiencies in serialization and transmission.
Innovation Solution
A non-invasive method using compiler operators and macros to determine and encode information about data elements, such as size and alignment, without requiring meta-models, enabling efficient serialization and transmission across platforms.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If conventional methods are used for data serialization, then data can be transmitted and stored, but the process requires meta-models and code modifications which increase complexity and effort
Solution Approach 1:
The system uses self-descriptive data structures where the data carries its own type information and formatting requirements inherently, eliminating the need for external meta-models. The serialization process automatically determines how to handle data based on embedded type descriptors within the data structures themselves.
Solution Approach 2:
Type descriptors act as intermediaries between the data and the serialization process, providing all necessary information about data structure, size, and formatting requirements without requiring separate meta-models or code modifications. These descriptors enable the serialization system to adapt to different data types automatically.
2Adaptability or versatility
If meta-models are used to interpret data elements, then data can be processed across platforms, but the effort and overhead increase significantly
Solution Approach 1:
All necessary information for cross-platform data interpretation is prepared in advance and embedded within the type descriptors during data structure definition. This preliminary encoding of size, alignment, and formatting information eliminates the need for runtime meta-model interpretation, enabling fast platform-independent processing.
Solution Approach 2:
The essential type information is extracted from complex meta-models and condensed into compact type descriptors that contain only the necessary information for serialization and interpretation. This extraction reduces processing overhead while maintaining platform independence.
3Measurement precision
If data structures are serialized with full type information, then accuracy is maintained, but data transmission size increases
Solution Approach 1:
The type descriptors are designed as lightweight, minimal-structure objects that contain only the essential information needed for data interpretation. Rather than using comprehensive meta-models, the system employs these compact descriptors that are sufficient for accurate reconstruction of data structures during deserialization.
Data Source
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AI summary
Method for processing data associated with a data element for a computer program, for example for a product such as a vehicle, comprising: determining first information characterizing at least one of the following elements: a) size of at least one data type associated with the data element, for example atomic, or b) orientation of at least one data type associated with the data element, for example atomic, providing the first information.