Optimal Test Case Selection for User Equipment
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Solution Overview
Problem
Existing methods for selecting optimal test cases for cellular communication protocol software/hardware are inadequate, as they fail to consider location-specific user density, channel conditions, and Radio Access Technologies (RATs), leading to inefficient and error-prone testing processes.
Innovation Solution
An electronic testing device determines optimal test cases by analyzing location, time, number of iterations, and type of test equipment, using profiling parameters, code coverage metrics, and debug logs to ensure comprehensive testing across various cellular network scenarios.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual selection of test cases is performed, then domain knowledge and expertise can be applied, but human errors increase and time consumption increases
Solution Approach 1:
The system performs self-service by automatically selecting optimal test cases through AI/ML algorithms without human intervention. The electronic testing device autonomously analyzes test case repositories, evaluates test contexts, and selects optimal test cases based on learned patterns from historical testing data, eliminating the need for manual domain expertise while maintaining high accuracy.
Solution Approach 2:
The patent replaces the mechanical human decision-making process with an automated electronic system using AI/ML algorithms. The electronic testing device substitutes human testers with intelligent software that processes test case data, evaluates contexts, and makes selection decisions through computational algorithms, thereby eliminating human errors and reducing time consumption.
2Reliability
If all test cases are executed to ensure thorough testing, then testing completeness is improved, but testing time and resource consumption increase
Solution Approach 1:
The system dynamically changes parameters such as test case selection criteria, execution priorities, and iteration counts based on test context analysis. By adjusting these parameters according to the specific testing scenario, the system achieves thorough testing of critical areas while avoiding unnecessary execution of redundant test cases, thereby improving both completeness and efficiency.
Solution Approach 2:
The patent applies partial action by selecting and executing only the optimal subset of test cases needed for the specific testing context rather than executing all available test cases. The AI/ML algorithm determines the minimum necessary test case set that provides sufficient coverage based on the test context, achieving adequate testing completeness with reduced time and resource consumption.
3Productivity
If automated test case identification systems are used, then time consumption is reduced, but the ability to ensure optimal test cases for cellular communication protocol software/hardware is insufficient
Solution Approach 1:
The system implements feedback mechanisms where test results and outcomes are fed back into the AI/ML model to continuously improve test case selection accuracy. The electronic testing device learns from historical testing data, success patterns, and failure modes specific to cellular communication protocols, progressively refining its ability to identify optimal test cases while maintaining high testing speed.
Solution Approach 2:
The patent employs parameter changes by dynamically adjusting test case selection criteria based on the specific cellular communication protocol being tested. The system modifies evaluation parameters such as protocol version, network conditions, device types, and test scenario priorities to ensure optimal test case selection tailored to each testing context, thereby achieving both speed and reliability.
Data Source
AI summary
A method is provided. The method includes determining, in a determination by an electronic testing device, one or more locations in a cellular network where a test case is to be executed, a time at which the test case is to be executed at the one or more locations, a number of times the test case is to be executed at the one or more locations, or a type of a test equipment on which the test case is to be executed. A test context for testing a user equipment is determined based on a result of the determination. An optimal test case is determined from a test case repository, based on the test context, and the optimal test case is executed.