Software Quality Tracking via User Review Analysis
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Solution Overview
Problem
The complexity of tracking and monitoring the quality of multiple software applications on mobile devices has increased due to the large number of apps, making it difficult for companies and developers to effectively assess specific quality attributes beyond general star ratings.
Innovation Solution
A computer-implemented method and system that aggregates user reviews, classifies them into quality attributes, determines scores for each attribute, and presents them, using machine learning and natural language processing to analyze user feedback from various sources, including app stores and social media, and applies weights based on category-specific importance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If general star ratings are used to assess app quality, then the assessment process is simple and quick, but the quality measurement lacks precision and detail
Solution Approach 1:
The patent segments the overall app quality assessment into multiple discrete quality attributes (e.g., performance, usability, design, content quality). Each attribute is evaluated separately through automated analysis of user reviews, allowing precise measurement of specific quality dimensions while managing complexity through modular processing of different attribute types.
Solution Approach 2:
The system introduces an intermediary automated analysis layer that processes user reviews and generates structured quality attribute scores. This intermediary component translates unstructured user feedback into quantifiable quality metrics, enabling precise measurement without requiring direct complex manual assessment of each review.
2Loss of information
If multiple quality attributes are tracked for each app, then comprehensive quality insights are obtained, but the data processing and analysis complexity increases
Solution Approach 1:
The system implements a universal automated analysis framework that handles multiple quality attributes through a single integrated process. The same computational infrastructure processes different attribute types (performance, usability, design, content) using consistent methodologies, enabling comprehensive quality information capture while avoiding the need for separate complex processing systems for each attribute.
Solution Approach 2:
The system transforms unstructured user review text into structured quality attribute parameters through automated analysis. By converting qualitative feedback into quantitative scores for multiple attributes, the system maintains complete quality information while enabling efficient computational processing through standardized parameter formats.
3Productivity
If automated analysis of user reviews is implemented, then detailed quality scores are generated efficiently, but the complexity of implementing and maintaining the analysis system increases
Solution Approach 1:
The system employs self-service automated analysis that processes user reviews without requiring manual intervention for quality assessment. The automated framework independently collects, analyzes, and generates quality attribute scores from user feedback, achieving high productivity while reducing the operational complexity of manual quality monitoring processes.
Solution Approach 2:
The patent replaces manual quality assessment mechanics with automated computational analysis. Instead of human reviewers manually evaluating each app quality attribute, the system uses automated text analysis algorithms to process user reviews and generate quality scores, dramatically increasing assessment speed while the complexity is managed through software-based rather than human-based processing.
Data Source
AI summary
A computer-implemented method and system for quantifying and tracking software application quality based on aggregated user reviews.