AI Web Script Testing Across Multi-Device Render Permutations
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Solution Overview
Problem
Existing script testing procedures for multi-device and platform interfaces are inefficient and time-consuming, particularly when new updates or bug fixes require repetitive testing across various permutations, leading to errors that may not be consistently detected.
Innovation Solution
A computing platform utilizing AI image/video processing and comparison engines to generate expected renderings and performance scores, and an AI script fixing engine to automatically modify scripts to address discrepancies, ensuring compliance with performance thresholds.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional script testing procedures are used to test across multiple device and platform permutations, then testing coverage is provided, but testing efficiency and time consumption are poor
Solution Approach 1:
The patent uses image capturing tools to create visual snapshots of interface renderings across different devices and platforms. These captured images serve as test cases that can be efficiently compared and validated without manually testing each permutation, thus maintaining comprehensive coverage while improving testing efficiency through automated image-based verification.
Solution Approach 2:
The patent replaces traditional manual or automated script-based interface testing with an AI-powered image comparison system. The AI engine analyzes captured interface images and compares them against expected renderings, substituting complex mechanical testing procedures with intelligent image processing that is both more efficient and more reliable across multiple permutations.
2Measurement precision
If comprehensive testing across all permutations is performed to ensure interface accuracy, then error detection capability is improved, but time consumption increases
Solution Approach 1:
The patent performs preliminary image capturing and AI-based comparison for all device and platform permutations before final validation. By pre-processing and pre-comparing interface renderings across all permutations using the AI engine, the system identifies potential errors early in the testing workflow, maintaining high error detection capability while reducing overall time consumption through efficient preliminary analysis.
3Measurement precision
If manual script validation is used to check interface rendering accuracy, then detailed error analysis is possible, but automation level and efficiency are reduced
Solution Approach 1:
The patent implements an AI-powered self-service validation system that automatically captures interface images, compares them against expected renderings, and validates rendering accuracy across all device and platform permutations without human intervention. The AI engine autonomously performs detailed error analysis by comparing image features, maintaining high measurement precision while achieving complete automation of the validation process.
Data Source
AI summary
A computing platform may receive a script for a web page, which may be configured to render the web page according to a plurality of different permutations based on system parameters. The computing platform may execute the script to produce the plurality of different permutations of the web page. The computing platform may compare the plurality of different permutations of the web page to corresponding expected renderings of the web page to produce performance scores. The computing platform may compare the performance scores to a performance threshold. Based on identifying that a performance score fails to meet the performance threshold, the computing platform may input the script into an AI script fixing engine to produce a script modification to address performance discrepancies produced by the script. The computing platform may update the script based on the script modification, and may send, to a script repository system, the updated script.