Test Plan Inspection Platform for Crowd-Sourced Testing Risks
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Solution Overview
Problem
Conventional software testing methods do not adequately account for factors relevant to crowd-sourced testing, such as test diversity, specialization, and risk assessment, leading to inefficiencies and increased risks in implementing test plans.
Innovation Solution
An inspection platform that analyzes test plans using a test plan inspection model, including rules for identifying crowd-sourcing issues, and generates recommendations to address these issues, thereby improving the accuracy and utility of software testing results while reducing risks and resource waste.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If crowd-sourced testing is implemented without specialized inspection, then testing coverage and diversity are improved, but risks and issues related to test plan implementation increase
Solution Approach 1:
The system performs preliminary analysis of test plans before crowd-sourced testing execution by identifying potential issues, conflicts, and gaps in the test plan documentation. This advance inspection allows risks to be detected and addressed before they manifest during actual testing, thereby maintaining reliability while preserving the adaptability benefits of crowd-sourced testing.
Solution Approach 2:
The patent introduces an intermediary inspection system that acts as a mediator between test plan creation and crowd-sourced testing execution. This intermediary layer analyzes test plans for consistency, completeness, and potential conflicts, serving as a buffer that protects the overall testing process from errors while allowing the crowd-sourced component to maintain its versatility.
2Reliability
If comprehensive test plan analysis is performed to identify all potential issues, then testing reliability is improved, but time and resources required for test plan preparation increase
Solution Approach 1:
The system employs automated self-service mechanisms where computer-readable instructions automatically analyze test plans for issues, conflicts, and gaps without requiring extensive manual review. The inspection system performs self-diagnosis of test plan quality, generating reports and identifying problems autonomously, thereby improving reliability while minimizing the time investment required from human testers.
Solution Approach 2:
The patent replaces manual mechanical review processes with automated computational analysis. Instead of human reviewers manually examining test plans for potential issues, the system uses automated instruction execution to detect conflicts, gaps, and quality problems, significantly reducing the time required for test plan preparation while maintaining or improving detection accuracy.
3Measurement precision
If multiple inspection rules are applied to thoroughly analyze test plans, then issue detection accuracy is improved, but system complexity increases
Solution Approach 1:
The inspection system is segmented into multiple independent rules, each responsible for detecting specific types of issues in test plans. Rather than using one complex monolithic analysis system, the patent divides the inspection functionality into discrete, manageable rules that can be executed independently and whose results are aggregated, thereby improving detection accuracy across different issue types while keeping individual rule complexity low.
Solution Approach 2:
The inspection rules are designed with universal applicability, where a single rule framework can detect multiple types of issues (conflicts, gaps, inconsistencies) across different test plan formats and testing scenarios. This multi-functional approach allows the system to achieve high detection accuracy for diverse problems without proportionally increasing system complexity, as the same rule structure handles various issue types.
Data Source
AI summary
A device may receive test plan information, associated with a test plan for performing a test of an application, including information associated with a use case for which the application is to be tested. The device may obtain a test plan inspection model, associated with analyzing the test plan, including test plan rules. A test plan rule, of the test plan rules, may be associated with a condition for identifying a crowd-sourcing issue associated with implementing the test plan using crowd-sourced testing. The device may determine, based on the test plan information and the test plan rule, whether the condition is satisfied. The device may identify, based on whether the condition is satisfied, the crowd-sourcing issue as being associated with the test plan. The device may generate a recommendation associated with the crowd-sourcing issue. The device may provide information associated with the crowd-sourcing issue or information associated with the recommendation.