Target Language Code Generation for Low-Latency Cross-Platform Apps
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Solution Overview
Problem
Developing cross-platform applications requires significant time and computing resources, and existing methods often result in high latency and inefficiencies due to the need for different files, coding languages, and user expertise across various platforms.
Innovation Solution
A system generates cross-platform applications by processing user code to create target language code for multiple platforms, including configuration, build, and interface files, utilizing a transpiler, build system, and platform building engine to optimize for device-specific execution, reducing latency and resource consumption.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If cross-platform applications are developed using different files and coding languages for each platform, then platform-specific functionality is achieved, but development time and computing resource consumption increase significantly
Solution Approach 1:
The patent applies universality by creating a single source code base that can be compiled and executed across multiple platforms. The system generates platform-specific code from a universal source code, allowing the same application logic to function on different operating systems and devices without requiring separate development for each platform.
Solution Approach 2:
The patent introduces an intermediary compilation system that acts as a mediator between the high-level source code and platform-specific executables. This intermediary system translates the universal source code into platform-appropriate code, eliminating the need for developers to write separate code for each platform while still achieving platform-specific optimization.
2Adaptability or versatility
If cross-platform applications are developed using different files and coding languages for each platform, then platform-specific functionality is achieved, but computing resource consumption increases
Solution Approach 1:
The system uses a universal source code base that can be compiled for multiple platforms, reducing the total amount of code that needs to be developed, maintained, and processed. This universality reduces computing resource consumption by eliminating redundant development efforts across different platforms.
Solution Approach 2:
The compilation system changes parameters such as target platform, optimization level, and code generation settings to produce platform-specific binaries from the same source code. This allows the system to optimize resource usage for each platform without requiring separate development processes, thereby reducing overall computing resource consumption.
3Device complexity
If server-side processing model is used for application functionality, then centralized control is achieved, but latency for user interactions increases
Solution Approach 1:
The patent segments the application into client-side and server-side components, with intelligent processing distributed between them. By generating platform-specific code that can execute locally on user devices, the system reduces dependency on continuous server-side processing for every user interaction, thereby reducing latency while maintaining centralized control for critical operations.
Solution Approach 2:
The system performs preliminary compilation and optimization of code for specific platforms before deployment. This preliminary action enables the generated applications to execute efficiently on user devices with minimal runtime processing requirements, reducing the need for real-time server communication and thereby reducing interaction latency.
4Manufacturing precision
If user expertise in user interfaces and machine level code is required for cross-platform development, then platform-specific optimization is achieved, but ease of operation decreases
Solution Approach 1:
The system provides self-service by automatically generating platform-specific optimized code from high-level source code without requiring user intervention or expertise in platform-specific details. The compilation system handles platform-specific optimizations, interface adaptations, and code generation automatically, making the process accessible to users regardless of their expertise level while still achieving platform-specific optimization.
Data Source
AI summary
Methods, systems, and apparatus, including computer programs encoded on computer storage media, for generating a set of target language code from a set of source language code. One of the methods includes obtaining input data that represents a set of source language code; and processing the input data to generate a set of target language code.


