Abstract
This article examines current testing techniques for the quality assurance of artificial intelligence and machine learning systems. It organizes them based on the granularity of testing level and explores design tactics using these techniques.
Original language | English (US) |
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Pages | 101-105 |
Number of pages | 5 |
Volume | 55 |
No | 3 |
Specialist publication | Computer |
DOIs | |
State | Published - Mar 1 2022 |
All Science Journal Classification (ASJC) codes
- General Computer Science