Voice-Based Software Test Case Generation Across Browsers
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Solution Overview
Problem
Current software testing processes require manual effort and are inefficient for testing browser-based applications across various devices and platforms, as they lack automation and require manual conversion of test cases, leading to redundancy and incompatibility with different browser applications.
Innovation Solution
A system that captures voice input to automatically generate and execute tool-specific test cases using natural language processing, converting voice commands into programmatic instructions and executing them across multiple browser-based applications with various automation testing tools.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual test case design and conversion processes are used, then test cases can be created based on requirements, but the process requires significant manual effort and time
Solution Approach 1:
The patent replaces the manual mechanical process of test case design and scripting with an automated voice-based system. Test engineers speak natural language requirements, and the system automatically generates executable test cases, eliminating the manual conversion process while maintaining test accuracy through voice recognition and natural language processing.
Solution Approach 2:
The system enables test engineers to self-generate test cases through voice input without requiring programming expertise or manual scripting. The automated platform translates spoken requirements into executable test cases independently, allowing test engineers to perform the entire test case creation process themselves.
2Reliability
If test cases are customized for specific browser applications, then they can be executed on particular platforms, but they cannot be easily translated to other platforms
Solution Approach 1:
The patent creates a universal test case generation platform that produces test cases applicable across multiple browser applications and platforms simultaneously. The voice-based input system generates standardized test cases that can be automatically adapted and executed on different platforms without requiring separate customization for each browser or device type.
Solution Approach 2:
The system segments the test case generation process into platform-agnostic core test logic and platform-specific execution parameters. This allows the same voice-generated test case to be divided into universal steps that can be independently executed across different browser platforms, with each platform receiving only the necessary execution-specific instructions.
3Reliability
If test engineers create test cases manually, then they can understand requirements thoroughly, but they require programming expertise to script test cases
Solution Approach 1:
The patent replaces the programming/scripting mechanical skill requirement with voice-based natural language input. Test engineers who understand requirements can speak their test scenarios in plain English without needing to learn programming languages or scripting syntax, as the system automatically translates speech into executable test cases.
Solution Approach 2:
The voice recognition and natural language processing system acts as an intermediary between the test engineer's requirements understanding and the automated test execution. This intermediary layer translates spoken requirements into programmed test cases without requiring the test engineer to directly write code, bridging the gap between domain knowledge and technical implementation.
4Reliability
If multiple automation testing tools are used, then comprehensive test coverage can be achieved, but test cases must be written in specific languages for each tool
Solution Approach 1:
The patent implements a universal voice-based test case generation system that interfaces with multiple automation testing tools through a single standardized input method. The system generates test cases in a universal format that can be automatically converted to the specific language requirements of different automation tools, allowing comprehensive multi-tool coverage without requiring test engineers to master multiple programming languages.
Solution Approach 2:
The voice recognition system serves as an intermediary layer between the test engineer and multiple automation testing tools. It translates natural language input into the appropriate tool-specific formats automatically, eliminating the need for test engineers to directly learn or write code in multiple different automation tool languages while maintaining compatibility with all connected tools.
Data Source
AI summary
Methods and apparatuses are described for automated generation and execution of computer software test cases. A digitized voice segment is captured that corresponds to speech submitted by a user of a remote device. A software automation test case is generated using one or more phrases extracted from the digitized voice segment. The software automation test case is executed against a plurality of browser-based software applications using a plurality of automation testing tools, including converting the software automation test case into a plurality of tool-and-browser specific test cases, each based upon test case requirements of a selected automation testing tool and test case requirements of a selected browser-based application. An automation execution report is generated based upon the execution of each of the plurality of tool-and-browser specific test cases.