AI Test Manager for Software Performance Test-Case Generation
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Solution Overview
Problem
Conventional software testing processes require significant manual effort and time to determine and describe test-cases, which is tedious and lacks a way to prioritize them effectively.
Innovation Solution
A test manager software platform utilizing artificial intelligence (AI) to automatically define, generate, and prioritize test-cases across the software development lifecycle, leveraging machine learning models to streamline the testing process.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If test-cases are manually determined and described, then testing coverage can be achieved, but significant time and effort are required
Solution Approach 1:
The system enables self-service test-case generation by automatically determining test-cases from software requirements without manual intervention. The automated test-case determination engine processes requirements and generates comprehensive test-cases independently, eliminating the need for testers to manually write and describe each test-case while maintaining complete testing coverage.
Solution Approach 2:
The patent replaces the mechanical manual process of test-case creation with an automated computational system. The test-case determination engine uses algorithmic processing to analyze requirements and generate test-cases, substituting the manual mechanical work of testers with an automated system that processes requirements and produces test-cases efficiently.
2Reliability
If all possible test-cases are manually written to cover all risks, then comprehensive testing is achieved, but the process becomes extremely difficult and costly
Solution Approach 1:
The system automatically determines comprehensive test-cases by processing software requirements through the test-case determination engine. The engine independently analyzes requirements and generates all necessary test-cases to cover complete testing scenarios, eliminating the complexity of manual test-case management while ensuring comprehensive testing coverage.
Solution Approach 2:
The test-case determination engine acts as an intermediary between software requirements and test execution. It processes requirements and automatically generates appropriate test-cases, serving as a mediator that translates requirement specifications into comprehensive test scenarios without requiring manual intervention, thereby reducing complexity while maintaining completeness.
3Loss of information
If test-cases are manually described in written form, then detailed test procedures are documented, but the task becomes time-consuming and tedious
Solution Approach 1:
The system replaces the manual mechanical process of writing and documenting test-procedures with automated computational processing. The test-case determination engine automatically generates detailed test-procedure documentation from requirements, eliminating the time-consuming manual writing task while preserving complete test-procedure information.
Solution Approach 2:
The automated system performs self-service documentation by automatically generating detailed test-procedure descriptions from software requirements. The test-case determination engine independently produces comprehensive test-procedure documentation without requiring manual writing, maintaining complete information while eliminating the tedious documentation task.
4Reliability
If conventional testing methods are used, then testing can be performed, but there is no way to prioritize test-cases
Solution Approach 1:
The test-case determination engine serves as an intermediary that not only generates test-cases but also automatically prioritizes them based on risk analysis and requirement criticality. This intermediary function adds prioritization capability to the testing process, making test-case management easier while maintaining full testing capability.
Data Source
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AI summary
A method is provided. The method is executed by an test manager engine implemented as a computer program within a computing system. The test manager engine provides artificial intelligence (AI) powered continuous testing operations for a software under development (SUD) across an entire testing life cycle. The method includes defining, by the test manager engine, requirements including a textual description or narrative describing acceptance criteria or goals of the SUD. The method includes generating, by the test manager engine, test-cases utilizing an Al application programable interface (API) to connect with machine learning/artificial intelligence (ML/AI) models to generate test-case definitions corresponding to the one requirements and produce the test-cases from the test-case definitions.