Sentiment Analysis Error Repair Tool for Software Applications
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Solution Overview
Problem
Conventional software development processes are inefficient in addressing user-reported errors, often taking months or years to fix bugs, and may introduce additional errors or lose critical knowledge, while neglecting the emotional impact on users, leading to user dissatisfaction or abandonment of software applications.
Innovation Solution
An error repair tool utilizing sentiment analysis to automatically identify and fix software bugs by analyzing user videos, determining emotional intensity, and applying previous solutions to source code changes, with the ability to alert developers for non-emotionally distressing issues.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional manual error fixing process is used, then developers can fix bugs in software applications, but the process takes months or years and may introduce additional errors
Solution Approach 1:
The system enables automatic error fixing by having the software system itself analyze and repair bugs without human intervention. The automated error repair tool processes user reports, analyzes source code, generates fixes, and implements corrections autonomously, eliminating the need for manual developer intervention in the actual fixing process.
Solution Approach 2:
The patent replaces the mechanical manual process of error fixing with an automated computational system. Instead of developers manually analyzing and fixing bugs, the system uses natural language processing, sentiment analysis, and code analysis algorithms to automatically detect, diagnose, and repair errors in the software.
2Reliability
If developers manually fix errors, then bugs can be resolved, but knowledge is lost when developers change jobs resulting in nonuniform fixing approaches
Solution Approach 1:
The system creates a digital copy of the error fixing process by analyzing the relationship between errors and their solutions. It builds a knowledge base that captures fixing patterns and applies them consistently across different scenarios, ensuring uniformity regardless of which developer is working on the issue.
Solution Approach 2:
The system implements feedback loops where error reports, analysis results, and fix outcomes are continuously processed to improve the automated fixing capability. The system learns from each error case and refines its approach, maintaining consistent and improving performance over time.
3Reliability
If conventional error fixing without sentiment analysis is used, then developers can fix bugs, but user emotional impact is neglected leading to user dissatisfaction
Solution Approach 1:
The system introduces sentiment analysis as an intermediary between user error reports and the error fixing process. By analyzing the emotional tone and urgency in user reports, the system prioritizes errors based on their impact on user experience, ensuring that emotionally distressing bugs are addressed first.
Solution Approach 2:
The system changes the prioritization parameter from purely technical error severity to include user emotional impact. By incorporating sentiment analysis results into the prioritization logic, the system dynamically adjusts which errors are fixed first based on user distress levels rather than just technical implications.
Data Source
AI summary
An apparatus includes a memory and a hardware processor. The memory stores a plurality of previous software errors and a plurality of solutions to the plurality of previous software errors. The processor receives a video of a user describing an error in a software application and tracks a facial feature of the user to determine an emotional intensity. The processor converts an audio portion of the video to a text file and analyzes the text file to determine the error. In response to the emotional intensity exceeding a threshold, the processor determines, based on the plurality of previous software errors, a series of steps that, when performed, replicate the error, determines, based on the series of steps and the plurality of solutions, a change to the source code of the application that fixes the error, and implements the change to the software code.