AI Test Manager Platform for Faster Test-Case Definition
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Solution Overview
Problem
Conventional software testing methods 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 generate and prioritize test-cases across the software development lifecycle, leveraging AI-powered machine learning models to define requirements and execute test-cases.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual test-case generation is used, then test-case accuracy can be maintained, but time consumption and manual effort increase significantly
Solution Approach 1:
The patent replaces manual mechanical writing processes with an AI-based automated system. The AI model receives software requirements as input and automatically generates test-cases, substituting the manual cognitive and writing tasks with an automated intelligent system, thereby dramatically reducing time consumption while maintaining test quality
Solution Approach 2:
The system enables self-service test-case generation where the AI model autonomously analyzes requirements and produces test-cases without human intervention in the generation process. The automated system serves itself by processing inputs and generating outputs independently, freeing testers from tedious manual work
2Reliability
If comprehensive test-cases are generated to cover all risks, then test coverage improves, but the complexity and number of test-cases increase
Solution Approach 1:
The AI model changes the parameters of test-case generation by analyzing requirement complexity and dynamically adjusting the number and detail level of test-cases. Instead of generating a fixed comprehensive list, the system adapts the test-case parameters to match the actual risk profile and complexity of the software requirements, producing appropriate coverage without unnecessary complexity
3Ease of operation
If manual prioritization of test-cases is performed, then test-case selection can be made, but time and effort are required without systematic approach
Solution Approach 1:
The patent replaces manual prioritization with an automated AI-based prioritization system. The AI model systematically analyzes test-cases and assigns priorities based on risk assessment and requirement importance, substituting unstructured manual decision-making with a systematic automated process that eliminates time consumption while maintaining logical prioritization
Data Source
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 AI application programmable 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.