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, ensuring immediate feedback and error detection before integration into the pipeline.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If test scripts are compiled only during execution phase, then the test automation pipeline can maintain simplicity, but compiler performance degrades and issue detection is delayed
Solution Approach 1:
The patent implements a pre-compiler that performs compilation and validation of test scripts before they are executed. This preliminary action allows issues to be detected early in the development cycle rather than waiting until execution phase, improving reliability while the compilation time is amortized across the development lifecycle
Solution Approach 2:
The compilation process is segmented into two distinct phases: pre-compilation (performed before execution) and runtime compilation (performed during execution). This segmentation allows the system to benefit from both early issue detection and efficient runtime performance, resolving the contradiction between reliability and time loss
2Productivity
If pre-compilation is implemented to detect issues early, then compiler performance improves, but the system complexity increases
Solution Approach 1:
The patent introduces an AI-based natural language processing module as an intermediary between the test script and the validation system. This NLP module translates test scripts into structured representations that are easier to validate, improving productivity while managing system complexity through intelligent abstraction
Solution Approach 2:
The pre-compiler performs self-validation of test scripts using automated rule-based checking and AI-based analysis. This self-service capability reduces the need for manual review and complex validation infrastructure, improving productivity without proportionally increasing system complexity
3Measurement precision
If AI-based NLP evaluation is used for pre-compilation, then test script validity is improved, but processing time increases
Solution Approach 1:
The patent implements a two-level validation approach where rule-based checks (faster, less accurate) are performed first, and AI-based NLP evaluation (slower, more accurate) is applied selectively to cases that pass initial screening or require deeper analysis. This partial application of AI evaluation maintains measurement precision while reducing overall processing time
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.