Automated Test Case Generation via Linked Graph Analysis
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Solution Overview
Problem
Existing methods for generating test cases for complex applications are manual, costly, and prone to errors, making exhaustive coverage of navigation paths impractical and inefficient, especially when dealing with enterprise rules and predicates.
Innovation Solution
An automated system and method that receives business requirements and scenarios as input, generating test cases without human intervention by constructing link graphs and using backtracking algorithms to explore candidate paths, reuse paths, and generate necessary test data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual methods are used to generate test cases, then test case quality can be maintained, but human time cost and error risk increase significantly
Solution Approach 1:
The system enables automated self-generation of test cases through algorithms that automatically analyze business rules, identify test scenarios, and produce test scripts without human intervention, thereby reducing time cost while maintaining quality through systematic rule-based approaches
Solution Approach 2:
Manual mechanical processes of test case creation are replaced with automated computational systems that use algorithms to analyze business rules and generate test cases, substituting human effort with machine-based automated generation while maintaining systematic quality
2Reliability
If exhaustive coverage of navigation paths is pursued, then complete testing is achieved, but testing becomes prohibitively expensive and wasteful
Solution Approach 1:
The system extracts and focuses testing efforts on the most critical and meaningful navigation paths by analyzing business rules to identify high-value test scenarios, eliminating wasteful testing of irrelevant paths while maintaining adequate coverage of essential functionality
Solution Approach 2:
Instead of pursuing complete exhaustive coverage, the system applies partial action by targeting specific high-priority navigation paths and test scenarios that provide the most value, achieving sufficient testing coverage without the prohibitive cost of exhaustive path coverage
3Productivity
If automated test generation from business rules is implemented, then productivity and coverage improve, but system complexity increases
Solution Approach 1:
The system introduces an intermediary layer of business rule analysis and algorithmic processing that bridges the gap between business requirements and test case generation, automating the translation process while managing complexity through structured intermediate representations
Data Source
AI summary
Techniques, an apparatus and computer program product for generating test cases for covering enterprise rules and predicates are disclosed by receiving data associated with at least one of a business requirement and a business scenario as input, wherein the data comprise at least one of a set of predefined rules; based on the data, generating at least one or more test cases as output without any human intervention, wherein the output comprises a test script for the business requirement or the business scenario, and wherein the data associated with the at least one of a business requirement and a business scenario comprise at least one of a business rule, business requirement and predicate, the data associated with the at least one of business requirement and business scenario are stored as a linked graph in a repository, and wherein each node of the linked graph is mapped to previously stored data in the repository, wherein the repository comprises either one of a structured or unstructured data, and the data are obtained from the requirement specifications.