一种基于知识的可测试性设计

A Knowledge-based Design for Testability

本文提出了一种基于知识的可测试性设计(DFT)方法。系统在“专家”知识的指导下,实现了分类的DFT。该方法采用选择跟踪插入测试点,几乎在线性时间内实现了可测试性的较优改进。该方法具有的自学习能力大大减小了DFT的计算量。

In this paper, a knowledge-based design for testability (DFT), is presented. A classified DFT is implemented under the guidance of the 'expert' knowledge. The principle of selective tracing is also used to place test point, thereby testability is suboptimally improved in almost li near time. This method simplifies conventional DFT because of its self-learning ability.