Adaptive Webpage Component Validation via Clustering
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Solution Overview
Problem
Enterprise organizations face challenges in validating webpages in real-time while optimizing resource and bandwidth utilization, as traditional automated testing tools struggle to adapt to changes in business priorities and technical implementations, leading to longer test cycles and debugging times.
Innovation Solution
An automated and adaptive validation system that extracts webpage components, determines attributes and rules, clusters components, retrieves a master test script, generates a test script based on attributes and rules, and runs it to validate the webpage, with the option to update the script if it fails, using a virtual assistant to identify causes and improve validation efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional automated testing tools are used to validate webpages, then validation coverage is achieved, but test cycles become longer and debugging time increases due to inability to adapt to changes
Solution Approach 1:
The system dynamically adapts test scripts based on detected changes in webpage components. The validation system continuously monitors webpage attributes and automatically updates test parameters, making the testing process flexible and responsive to changes rather than static and rigid.
Solution Approach 2:
The system performs self-updating of test scripts by automatically detecting changes in webpage components and adjusting test parameters without human intervention. This self-service capability allows the validation system to maintain accuracy while reducing manual debugging time.
2Loss of time
If real-time validation is performed on webpages, then validation timeliness is improved, but resource utilization and bandwidth consumption increase
Solution Approach 1:
The system extracts and validates only the specific components of the webpage that have changed or are relevant to current business priorities, rather than validating the entire webpage. This selective extraction approach reduces resource consumption while maintaining real-time validation capability.
Solution Approach 2:
The system performs partial validation by focusing on critical components and attributes based on clustered categories and priority levels. This partial action approach achieves timely validation without the overhead of complete webpage validation, optimizing resource utilization.
3Measurement precision
If comprehensive webpage validation is performed, then validation accuracy is improved, but complexity of the validation system increases
Solution Approach 1:
The validation system segments webpage components into clustered categories based on attributes and business priorities. This segmentation allows the system to manage complexity by organizing validation into manageable groups while maintaining comprehensive coverage through systematic processing of each cluster.
Solution Approach 2:
The system uses universal clustering algorithms and standardized validation processes that can be applied across different webpage types and components. This multi-functional approach maintains validation accuracy while reducing system complexity by reusing the same validation framework for diverse webpage elements.
Data Source
AI summary
Aspects of the disclosure relate to an automated and adaptive validation of a user interface. A computing platform may extract, from a webpage, one or more components of the webpage. Subsequently, the computing platform may determine, for a component, one or more attributes and one or more rules. Then, the computing platform may associate, by applying a clustering algorithm and based on the one or more attributes and the one or more rules, the component with a cluster of a plurality of clusters. Then, the computing platform may retrieve, from a database and for the cluster, a master test script. Subsequently, the computing platform may generate, from the master script, a test script for execution, and may run, for the webpage, the test script to validate the component. Subsequently, the computing platform may trigger one or more recommendations based on a determination whether the test script is successful.