NLP Pre-Compiler for Test Script Validation
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Solution Overview
Problem
Existing test automation pipelines face inefficiencies due to the lack of pre-compilation of test scripts, leading to detection of issues only during execution, which results in degraded compiler performance and inefficiencies in application development.
Innovation Solution
A system that uses AI-based natural language processing (NLP) for pre-compilation of test scripts, evaluating their validity and predicting next steps before compilation, and encrypting or mocking sensitive data, to identify and rectify errors before integration into the pipeline.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If test scripts are compiled only during execution phase, then the compilation process is simpler, but issues are detected late causing degraded compiler performance and development inefficiency
Solution Approach 1:
The patent applies preliminary action by performing pre-compilation of test scripts before they are executed. The pre-compiler validates test script syntax, semantics, and structure in advance, detecting errors during a pre-processing phase rather than during execution. This early validation improves compiler performance by ensuring only valid scripts reach the execution phase, while also reducing detection time by identifying issues before they propagate through the execution pipeline.
2Measurement precision
If pre-compilation with AI-based NLP validation is implemented, then error detection capability is improved, but system complexity increases
Solution Approach 1:
The patent introduces an intermediary AI-based NLP validation layer between test script submission and compilation. This intermediary module uses natural language processing to understand and validate the semantic correctness of test scripts, going beyond simple syntax checking. The NLP-based validator acts as a mediator that enhances error detection precision by catching logical errors and semantic issues, while managing system complexity through modular integration into the existing compilation pipeline.
3Object-affected harmful factors
If sensitive data in test scripts is encrypted or mocked during pre-compilation, then data security is improved, but processing time increases
Solution Approach 1:
The patent applies preliminary action by performing encryption or mocking of sensitive data during the pre-compilation phase, before test scripts are executed or stored. This early protection of sensitive information (such as credentials, personal data, or proprietary algorithms) improves data security by ensuring sensitive values are masked before they can be exposed or misused. The processing time increase is managed by performing these operations during the pre-processing phase rather than adding overhead during execution.
Data Source
AI summary
Various aspects of the disclosure relate to test automation systems with pre-compilers to validate various steps associated with a test script. An artificial intelligence (AI)-based pre-compiler may use natural language processing (NLP) to validate various steps associated with a test script associated with an application. Other aspects of this disclosure relate to automated encryption and mocking of test input data associated with test scripts.