Entity Generation for Testing via Templates and Value Generators
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Solution Overview
Problem
Generating entities for testing computing systems is time-consuming and may lead to insufficiently thorough testing due to the complexity and variability of the entities required.
Innovation Solution
A method and system that use entity templates and value generators to create instances of entities for testing, where at least one generated instance includes a randomly generated value, allowing for the determination of attributes and types, enabling the generation of complex entities with random, constrained random, and deterministic values.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If entities are generated manually or using simple methods, then the testing process is simpler to implement, but the testing thoroughness is insufficient due to time-consuming generation and limited variability
Solution Approach 1:
The entity generation process is segmented into multiple independent value generators, each responsible for generating specific attributes or portions of entities. This segmentation allows parallel processing of different entity attributes, significantly reducing the time required to generate complete entities while maintaining comprehensive variability through the coordinated action of multiple generators.
Solution Approach 2:
Entity templates are pre-defined with all necessary attribute structures and validation rules before testing begins. Value generators are pre-configured with appropriate data sources and generation logic. This preliminary preparation eliminates the need for manual entity creation during testing, reducing generation time while ensuring thoroughness through systematic coverage of all entity types and attribute combinations.
2Reliability
If complex entities with multiple nested attributes are generated, then the testing coverage is improved, but the generation complexity and time consumption increase significantly
Solution Approach 1:
The complex entity generation task is divided into smaller, manageable units where each value generator handles specific attributes or nested entities independently. This segmentation reduces the complexity of any single generation function while the collective action of multiple generators achieves comprehensive coverage of complex entity structures through systematic iteration and combination.
3Productivity
If deterministic values are used for all entity attributes, then the generation process is faster and more consistent, but the variability and realism of test data is reduced
Solution Approach 1:
The value generators are designed to dynamically select between different value generation strategies based on the requirements of each attribute. Some attributes may use deterministic values for consistency, while others use random or varied values for realism. This dynamic approach allows the system to maintain high generation speed through optimization while achieving the necessary data variability for comprehensive and realistic testing scenarios.
Data Source
AI summary
A system and method for inspecting a testing state includes determining one or more entities to be manipulated during execution of a test of the system, generating an instance of each of the entities using a plurality of entity templates and a plurality of value generators, and executing the test using the generated instances. At least one of the generated instances includes a first value generated randomly. The test is being executed by one or more processors of the system. In some examples, generating an instance of a first one of the entities includes identifying a first one of the entity templates corresponding to a type of the first entity, determining one or more attributes for the first entity based on the first entity template, and generating an instance of each of the attributes using the entity templates and the value generators.