Automated Mobile App Testing via Screen Relationship Graphs
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Solution Overview
Problem
Current automated mobile application testing systems are inflexible and inadequate for testing a wide range of mobile apps, as they are typically designed to test a single application or a small subset of applications, and do not effectively utilize artificial intelligence or predictive analytics to exercise all interactive user interface elements, leading to inefficiencies and missed bugs.
Innovation Solution
An automated mobile application testing system that analyzes display screens to identify user interface elements, generates a screen relationship graph, and creates a recommended testing sequence using artificial intelligence and predictive analytics to exhaustively test all possible interactions across various mobile apps, incorporating developer-based live testing data for improved usability analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If automated testing systems are designed to test a single application or small subset, then testing depth and precision are improved, but adaptability and versatility deteriorate
Solution Approach 1:
The testing system is designed to universally test multiple mobile applications across different categories (messaging, social media, productivity, entertainment) using a common automated testing platform. The system extracts UI elements and generates test sequences that can be applied across different apps, making the testing system versatile while maintaining thorough testing capabilities.
Solution Approach 2:
The testing system segments the testing process into distinct phases: UI element extraction, screen relationship graph generation, test sequence creation, and execution. This segmentation allows the system to maintain precision in each phase while adapting to different applications, resolving the contradiction between testing depth and versatility.
2Reliability
If manual testing methods are used to thoroughly test all aspects of an application, then testing completeness is improved, but productivity and time efficiency deteriorate
Solution Approach 1:
The system automatically extracts UI elements from application screens without requiring manual identification. The automated testing platform performs UI element extraction, screen relationship analysis, and test sequence generation autonomously, eliminating the need for manual testing while maintaining comprehensive test coverage and significantly improving testing efficiency.
Solution Approach 2:
The system replaces manual mechanical testing processes with automated computational methods. Instead of human testers manually interacting with each UI element, the system uses automated scripts to extract UI elements, generate test sequences, and execute tests, thereby maintaining testing completeness while dramatically improving productivity.
3Reliability
If rigid test programs are used to exhaustively exercise application features, then testing thoroughness is improved, but adaptability to different applications deteriorates
Solution Approach 1:
The testing system dynamically adapts to different applications by automatically extracting UI elements and generating screen relationship graphs specific to each application being tested. Rather than using fixed rigid test programs, the system creates customized test sequences based on the unique structure and characteristics of each application, maintaining thoroughness while achieving versatility across different app types.
Data Source
AI summary
A system for automated generation of mobile application testing sequences. The automated testing sequence generation system analyzes display screens to identify user interface elements, exercises one or more user interface elements to identify their functions, generates a screen relationship graph from the exercise of the one or more user interface elements and their mapped functions, and generates a recommended testing sequence for the mobile device application from the screen relationship graph.