Multi-Stage Code Generation With Built-In Test Validation
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Solution Overview
Problem
Existing computer code generation systems are inefficient and unreliable, leading to increased computational demands, data mishandling, and poor system performance due to ineffective code design, making timely detection of low-quality code challenging.
Innovation Solution
An ML-based system that automatically generates and validates test cases and computer code solutions, reducing computational resources and improving energy efficiency by using generative pretrained transformer models and large language models to ensure code validity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If automated code generation systems are used, then code production speed is improved, but code reliability deteriorates
Solution Approach 1:
The patent implements automated testing and validation systems that provide feedback loops to verify generated code quality. Test cases are automatically executed against generated code, and validation metrics are computed to ensure reliability standards are met before code deployment, resolving the contradiction between fast automated generation and reliable output.
Solution Approach 2:
The system performs preliminary validation and testing actions during the code generation process itself, rather than as separate post-processing steps. By integrating test case generation and validation into the code creation workflow, the system ensures reliability is built-in from the start, maintaining both speed and quality.
2Reliability
If code validation and testing are performed, then code quality is improved, but computational resource consumption increases
Solution Approach 1:
The patent implements a multi-stage validation approach where not all generated code undergoes full validation. Instead, the system applies targeted testing based on code criticality, using lighter validation for non-critical code paths and reserving comprehensive testing for critical sections. This partial action approach maintains code quality while reducing overall computational resource consumption.
Data Source
AI summary
Technical solutions are directed to creation and deployment of multi-stage test problems. A processor can provide, to a client, a first data structure for a first stage of a multi-stage test problem including a description for generation of a client solution for the first stage and a test case to evaluate the client solution. The processor can receive, from the client, a client data structure comprising the client solution including a client computer code generated at the client for the first stage. The processor can determine, by evaluating the client solution using an input value and an output value of the test case, that the output of the client solution satisfies a validity condition of the output value. The processor can provide, to the client, based on satisfying the validity condition, a second data structures for a second stage of the multi-stage test problem.