Intelligent UI Exploration for Adaptive Automated Testing

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Solution Overview

Problem

Existing automated testing services require pre-compiled testing cases, which are time-consuming and need modification when the target application is updated, and Monkey testing lacks understanding of user interfaces, leading to incomplete and inaccurate testing.

Innovation Solution

Automated testing based on intelligent exploration uses machine learning techniques to understand user interfaces, determining actions through a combination of rule-based and model-based approaches, enabling efficient testing without pre-compiled cases and adapting to interface changes.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Manufacturing precision

If pre-compiled testing cases are used for automated testing, then testing structure and coverage are improved, but testing maintenance time and adaptability to application updates deteriorate

Engineering Contradiction:

Improvetesting coverageVSAvoidmaintenance time

Core Design Contradiction:

Manufacturing precisionVSLoss of time

Solution Approach 1:

The system performs self-service by automatically generating testing cases through intelligent exploration of the user interface. The testing agent autonomously navigates the application, discovers functions and interfaces, and creates corresponding test cases without human intervention, allowing the system to adapt automatically when the application updates.

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The testing approach transitions from static pre-compiled cases to dynamic intelligent exploration. The system continuously adapts its testing behavior based on real-time exploration of the application interface, allowing testing cases to evolve automatically with application changes rather than requiring manual updates.

Inventive Principle:

Principle #15Dynamics

2Extent of automation

If Monkey testing is used for automated testing, then testing automation extent is improved, but testing accuracy and interface understanding deteriorate

Engineering Contradiction:

Improvetesting automationVSAvoidtesting accuracy

Core Design Contradiction:

Extent of automationVSMeasurement precision

Solution Approach 1:

An intelligent exploration module acts as an intermediary between the automated testing system and the application interface. This module analyzes interface elements, understands their functions and relationships, and guides the testing agent to perform meaningful actions, bridging the gap between automation and understanding.

Inventive Principle:

Principle #24Intermediary (Mediator)

Solution Approach 2:

The system implements feedback mechanisms where the testing agent's actions and observations are continuously analyzed to improve future testing decisions. The exploration module learns from the application's responses and adjusts the testing strategy accordingly, enhancing both automation capability and testing accuracy over time.

Inventive Principle:

Principle #23Feedback

Data Source

PatentUS20250252035A1Automated Testing based on Intelligent Exploration

Publication Date: 2025.08.07 MICROSOFT TECHNOLOGY LICENSING LLC

AI summary

The present disclosure proposes a method, apparatus and computer program products for automated testing based on intelligent exploration. A user interface of a target application may be obtained. A user interface representation of the user interface may be generated. An action for the user interface may be determined based on the user interface representation. Automated testing may be performed on the target application through applying the action to the user interface to explore a next user interface.