Software Testing Environment Segmentation for Non-Programmers
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Software testing environments are confusing and inefficient for individuals who design test cases and evaluate test results, as they require knowledge of the testing code and environment, making it difficult for non-programmers to develop and analyze automated tests.
Innovation Solution
Separating the environments of test designers and analysts, allowing test designers to create high-level actions without programming knowledge and test analysts to review results without understanding the automation details, using independent tools for both roles.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a unified software testing environment is used for both test automation code generation and test result analysis, then the system can maintain a consistent testing framework, but the environment becomes confusing and inefficient for individuals without programming knowledge
Solution Approach 1:
The patent divides the testing system into two distinct environments: a test automation environment for code generation and a test analysis environment for result evaluation. This segmentation allows each environment to be optimized for its specific purpose, with the analysis environment presenting simplified, role-based interfaces that hide implementation details while maintaining framework consistency through shared testing criteria and result data structures.
Solution Approach 2:
The patent introduces an intermediary layer that translates between the automation environment and analysis environment. This intermediary handles the conversion of automated test results into analyst-friendly formats, allowing non-programmers to interact with test outcomes without needing to understand the underlying automation code or environment complexities.
2Loss of information
If test analysts require knowledge of automation code and environment, then they can deeply understand testing implementation, but this creates a barrier for non-programmers to perform test analysis
Solution Approach 1:
The patent segments the system so that implementation knowledge is concentrated in the automation environment while the analysis environment focuses on outcome evaluation. This allows analysts to perform their functions without requiring programming knowledge, as the analysis environment presents results in terms of testing criteria and outcomes rather than code implementation details.
Solution Approach 2:
The patent creates simplified representations of test results that copy only the essential information needed for analysis. The analysis environment presents curated views of test outcomes that replicate the necessary testing information without exposing the complexity of the automation environment, enabling non-programmers to effectively evaluate test results.
3Ease of manufacture
If the testing system provides detailed automation environment interfaces, then programmers can effectively create and modify tests, but this increases complexity and confusion for users who only need to evaluate results
Solution Approach 1:
The patent segments the user interface complexity by creating distinct environments with different interface requirements. The automation environment provides detailed interfaces for programmers who need to create and modify tests, while the analysis environment provides simplified interfaces tailored to analysts who only need to evaluate results, thereby reducing overall system complexity for each user role.
Solution Approach 2:
The patent applies local quality by providing different levels of interface detail in different parts of the system. The automation environment offers comprehensive, detailed interfaces where needed, while the analysis environment provides simplified, role-appropriate interfaces. This allows each part of the system to have the appropriate level of complexity for its specific function and user audience.
Data Source
AI summary
Systems and methods for evaluating the testing of a computer program wherein a test automator generates code to test the computer program with respect to predetermined testing criteria. A test results analyst reviews test results generated by applying the code to test the computer program. The environments of a test automator and a test analyst are separated, thereby relieving a test results analyst from being required to have knowledge of the code that was used to test the computer program.