Automated Software Test Input Data Generation via Constraint Syntax
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Solution Overview
Problem
Current software testing methods require significant resources and time for manual creation of test input data, often resulting in incomplete and error-prone test scenarios due to the lack of comprehensive data types and properties for software input variables.
Innovation Solution
A method and apparatus that extract attributes from software requirements specifications, apply machine-readable constraint representation syntax to generate constraints, and use these constraints to automatically produce exhaustive software test input data, reducing the need for manual effort and improving data comprehensiveness.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual creation of test input data is used, then test data can be generated with human judgment and experience, but it requires significant resources and time and is susceptible to error
Solution Approach 1:
The system performs self-service by automatically generating test input data without human intervention. The test data generation apparatus extracts attributes from requirements specifications, applies constraint representation syntax, and produces comprehensive test data sets autonomously, eliminating the need for manual creation while maintaining high accuracy through systematic constraint satisfaction
Solution Approach 2:
The patent replaces the mechanical manual process of test data creation with an automated computational system. The mechanical effort of manually designing and creating test data is substituted by a computer-based system that uses constraint representation syntax and automated generation algorithms to produce test data, significantly reducing time and human resources while maintaining or improving accuracy
2Reliability
If manual creation of test input data is used, then human expertise can guide test scenario design, but the process is expensive and resource-intensive
Solution Approach 1:
The system achieves self-service by autonomously generating comprehensive test data sets that satisfy all extracted constraints without requiring human resources. The apparatus automatically extracts attributes from requirements specifications, formulates constraints using machine-readable syntax, and generates test data that achieves complete coverage, eliminating the need for expensive manual processes while maintaining high reliability
Solution Approach 2:
The patent transforms the parameters of test data generation by changing from manual human-driven processes to automated computational processes. The system uses constraint representation syntax to systematically define and satisfy all data type and property requirements, ensuring complete coverage while dramatically reducing resource consumption through automated generation rather than manual creation
3Productivity
If current techniques are used to generate test input data, then some test data can be produced quickly, but the data is not comprehensive with respect to data types and properties
Solution Approach 1:
The system performs preliminary action by extracting all attributes from requirements specifications and formulating complete constraint representations before generating test data. This preliminary constraint formulation ensures that all data types and properties are accounted for before the actual test data generation occurs, guaranteeing comprehensiveness while maintaining productivity through automated processing
Solution Approach 2:
The patent replaces inadequate automated techniques with a sophisticated constraint-based system. The new system uses machine-readable constraint representation syntax to systematically capture all data type and property requirements, then generates comprehensive test data that satisfies all constraints. This substitution maintains high generation speed through automation while achieving complete comprehensiveness that previous techniques failed to deliver
Data Source
AI summary
A method, non-transitory computer readable medium, and apparatus that extracts a plurality of attributes from a software requirements specification wherein each attribute is associated with a data type and one or more properties. Constraint representation syntax is applied to the extracted attributes based on the data type and the one or more properties associated with each attribute to generate a plurality of constraints, wherein the constraint representation syntax is a machine readable format. Each of the plurality of constraints is output and optionally associated with one or more nodes of a specification requirements model.