Test Automation Feasibility Scoring for Resource-Efficient QA
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Solution Overview
Problem
Existing methods for determining test automation feasibility are time-consuming, prone to bias, and lack a reliable framework for deciding between manual and automated testing, which varies by company and test case.
Innovation Solution
A method and system that calculates test automation feasibility indices using a questionnaire with weighted questions about ease and impact of automation, processed through AI models to provide quantitative indices and recommendations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If automated testing is implemented, then testing speed and accuracy are improved, but resource consumption increases
Solution Approach 1:
The patent changes the parameters for decision-making by introducing a feasibility index calculation that weighs multiple factors (ease of automation, impact, resource requirements) to determine the optimal testing approach for each test case, allowing resource-efficient automation selection
2Measurement precision
If manual assessment of automation feasibility is performed for every test case, then assessment accuracy is improved, but time consumption increases
Solution Approach 1:
The system enables self-service assessment by allowing users to input responses to standardized questionnaire items about test cases, which are then automatically processed through weighted calculations to generate feasibility indices, eliminating the need for time-consuming manual expert assessment while maintaining accuracy
Solution Approach 2:
The patent transforms the assessment process by changing from subjective manual evaluation to objective quantitative scoring using weighted questionnaire parameters, enabling rapid and consistent feasibility determination across all test cases
3Productivity
If automated testing is applied without systematic assessment, then testing efficiency is improved, but decision reliability decreases due to bias and error
Solution Approach 1:
The patent implements feedback mechanisms through standardized questionnaires that capture user responses about test case characteristics, which are then processed through weighted calculations to generate actionable feasibility indices, ensuring reliable and bias-free automation decisions
Solution Approach 2:
The system changes the decision-making parameters by introducing a structured scoring model that objectively evaluates automation feasibility based on multiple weighted factors, replacing subjective judgment with quantitative analysis for reliable automation decisions
Data Source
AI summary
This disclosure relates to method and system for calculation of test automation feasibility indices. The method includes receiving input data comprising user responses to a questionnaire associated with a test case. The questionnaire includes a first set of questions associated with an ease of test case automation, and a second set of questions associated with an impact of test case automation, and each of the plurality of questions comprises a corresponding weightage. The method further includes computing an ease of automation index based on the user responses and a first set of weightages corresponding to the first set of questions, and an impact of automation index based on the user responses and a second set of weightages corresponding to the second set of questions.