Website Error Correction via Decision Engine
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Solution Overview
Problem
Existing websites often struggle with accessibility, leading to denial of equal access to information for individuals with disabilities, and the process of making websites compliant with the ADA can be costly and time-consuming.
Innovation Solution
A system and method that utilize a decision engine with a processor to detect and correct errors associated with user actions on a website in real-time, by comparing event data with expected result data and applying pre-determined fixes stored in a database.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual processes are used to make websites compliant with ADA, then compliance can be achieved, but it is expensive and time-consuming
Solution Approach 1:
The system implements self-service by automatically detecting accessibility errors and applying corrections without requiring manual human intervention. The decision engine continuously monitors user actions, identifies compliance issues, and applies fixes autonomously, allowing the website to maintain itself and reducing dependency on external compliance services.
Solution Approach 2:
The system performs preliminary action by proactively identifying and correcting accessibility errors before they become formal compliance issues. The decision engine continuously monitors and detects potential ADA violations in real-time, applying fixes before users or regulatory bodies can identify them as problems, thus preventing rather than merely responding to compliance failures.
2Reliability
If manual processes are used to make websites compliant with ADA, then compliance can be achieved, but it is expensive
Solution Approach 1:
The system implements self-service by automatically detecting accessibility errors and applying corrections without requiring manual human intervention. The decision engine continuously monitors user actions, identifies compliance issues, and applies fixes autonomously, allowing the website to maintain itself and reducing dependency on external compliance services.
Solution Approach 2:
The system employs automated scripts and algorithms that can be deployed and updated inexpensively compared to manual compliance processes. The decision engine uses cost-effective automated detection and correction mechanisms rather than expensive human expert services, making compliance maintenance economically sustainable.
3Productivity
If automated decision engine is used to detect and correct errors in real-time, then accessibility is improved and turnaround time is reduced, but system complexity increases
Solution Approach 1:
The decision engine serves multiple functions within a single integrated system: it detects user actions, identifies accessibility errors, selects appropriate fixes from a database, and applies corrections automatically. This multi-functionality consolidates what could be separate complex systems into one unified component, improving productivity while managing overall system complexity.
Solution Approach 2:
The system performs preliminary action by pre-populating a database of fixes for common accessibility errors. Before errors occur, the system has predetermined correction strategies ready, which streamlines the real-time correction process and reduces the computational complexity during actual error handling, as the system only needs to retrieve and apply pre-prepared solutions.
Data Source
AI summary
A method for correcting errors associated with user actions on a website is disclosed. The method includes communicating between a decision engine and a website to receive event data associated with the user action and formatting information from the website. The method includes comparing the event data to expected result data. The method includes identifying an error associated with the user action based on the comparison of the event data to the expected result data. The method includes retrieving a pre-determined fix to correct the error associated with the user action from pre-determined fixes stored in a database. The method includes applying the pre-determined fix to the formatting information of the website.