ISO/IEC TR 29119-11:2020 软件和系统工程 软件测试 第11部分：基于人工智能的系统的测试指南

标准编号：ISO/IEC TR 29119-11:2020

中文名称：软件和系统工程 软件测试 第11部分：基于人工智能的系统的测试指南

英文名称：Software and systems engineering — Software testing — Part 11: Guidelines on the testing of AI-based systems

发布日期：2020-11

标准范围

本文档介绍了基于人工智能的系统。这些系统通常很复杂（例如深度神经网络），有时基于大数据，可能很少指定，并且可能是非确定性的，这为测试它们带来了新的挑战和机遇。本文件解释了基于人工智能的系统特有的特征，并解释了为此类系统指定验收标准的相应困难。本文档介绍了测试基于人工智能的系统的挑战，主要挑战是测试预言机问题，测试人员发现很难确定测试的预期结果，因此很难确定测试是通过还是失败。它涵盖了这些系统在整个生命周期中的测试，并给出了如何使用black-box方法并介绍了专门针对神经网络的白盒测试。它描述了用于测试基于人工智能的系统的测试环境和测试场景的选项。在本文档中，基于AI的系统是包括至少一个AI组件的系统。

This document provides an introduction to AI-based systems. These systems are typically complex (e.g. deep neural nets), are sometimes based on big data, can be poorly specified and can be non-deterministic, which creates new challenges and opportunities for testing them.
This document explains those characteristics which are specific to AI-based systems and explains the corresponding difficulties of specifying the acceptance criteria for such systems.
This document presents the challenges of testing AI-based systems, the main challenge being the test oracle problem, whereby testers find it difficult to determine expected results for testing and therefore whether tests have passed or failed. It covers testing of these systems across the life cycle and gives guidelines on how AI-based systems in general can be tested using black-box approaches and introduces white-box testing specifically for neural networks. It describes options for the test environments and test scenarios used for testing AI-based systems.
In this document an AI-based system is a system that includes at least one AI component.

标准预览图