What is ai testing
ai testing is a test for machine learning, recommendation systems, image recognition, and natural language processing tests in these four aspects.
The most widely used artificial intelligence at present are these four types.
What to test
Generally, what should these projects be tested for, and what types of tests should be performed.
1. Model evaluation test
Model evaluation is mainly to test the model’s prediction ability for unknown new data, that is, its generalization ability.
The stronger the generalization ability, the better the model’s predictive ability. The evaluation index to measure the generalization ability of the model is the performance measure. Performance metrics generally include error rate, accuracy, precision, recall, etc.
2. Stability/robustness test
Stability/robustness is mainly to test the stability of the algorithm for multiple runs; and the algorithm finds when the input value Output changes for smaller changes.
If the algorithm produces a huge output change when the input value changes slightly, it can be said that the algorithm is unstable.
3. System testing
takes the entire code based on the algorithm model as a whole and compares it with the system’s requirement definition to find that the software does not conform to the system definition or A place that contradicts it.
System testing mainly includes the following three aspects:
1. The overall business process of the project
2. Real user usage scenarios
3. Data Flow and correct
4. Interface testing
Interface testing is a test that tests the interfaces between system components. Interface testing is mainly used to detect interaction points between external systems and systems and between internal subsystems. The focus of testing is to check the exchange of data, transmission and control management processes, as well as the mutual logical dependencies between systems, etc.
5. Document testing
Document testing is to test the completeness, correctness, consistency, understandability, and ease of browsing of user documents.
During the entire life cycle of the project, a lot of documents will be obtained. At each stage, documents are used as the reflection of the results of the previous stage of work and the basis for the work of the later stage. In order to avoid defects discovered during the testing process being caused by inaccurate understanding of the document, differences in understanding, or changes in the document, document testing also requires sufficient attention.
6. Performance testing
7. White box testing – code static inspection
8. Competitive products Comparative testing
If relevant, you can do a comparative test on competing products to clarify the advantages and disadvantages. For example, AI smart speaker products.
9. Security testing
After release, online model monitoring
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