Automated GUI Modification via Component Scoring
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Solution Overview
Problem
Current methods for evaluating and modifying user interfaces are inefficient, requiring manual changes and testing, which can lead to unforeseen negative impacts, and lack effective tools for predicting user experience improvements.
Innovation Solution
A system and method for automatically modifying graphical user interfaces (GUIs) using a component classification engine, evaluation engine, and scoring component to decompose UIs into discrete components, evaluate their impact, generate potential modifications, prioritize them based on predicted outcomes, and apply multivariate testing to identify optimal modifications.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual implementation of UI changes is performed, then customization and control are improved, but time consumption and risk of unforeseen negative impacts increase
Solution Approach 1:
The system performs self-evaluation and self-modification of the UI by automatically analyzing its own components, predicting the impact of potential changes using historical data, and implementing modifications without requiring manual testing cycles. The UI system serves itself by using its own historical performance data to guide improvements.
Solution Approach 2:
The system performs preliminary evaluation and prediction of UI modification outcomes before actual implementation. By using the evaluation engine to score potential changes based on historical data and predict user experience impacts beforehand, the system avoids unforeseen negative effects and reduces the need for extensive post-modification testing.
2Reliability
If extensive testing is performed to assess UI modifications, then reliability is improved, but productivity decreases
Solution Approach 1:
The system uses historical UI data and performance metrics as feedback to continuously improve modification reliability. The evaluation engine analyzes past modification outcomes and user interactions to learn patterns, enabling more accurate prediction of future modification impacts and reducing the need for extensive testing while maintaining or improving reliability.
3Measurement precision
If manual UI evaluation and modification is performed, then precision of assessment is improved, but automation level remains low
Solution Approach 1:
The patent replaces manual mechanical evaluation processes with an automated evaluation engine that uses machine learning algorithms and historical data analysis. This substitution maintains measurement precision by using objective, data-driven metrics while achieving high levels of automation in the modification process.
4Productivity
If UI modifications are deployed in live environment without prediction, then implementation speed is improved, but risk of negative impacts increases
Solution Approach 1:
The system applies preliminary anti-action by predicting and preventing potential negative impacts before they occur. The evaluation engine scores potential modifications and predicts user experience impacts, allowing the system to filter out harmful changes before deployment, thus enabling fast deployment without the risk of unforeseen negative effects.
Data Source
AI summary
A system and method of user interface modification, and more particularly a system and method of automatically modifying a user interface to improve the quantitative evaluation of the user interface.