基于状态跟踪的RTL验证搜索启发式

Ziyue Zheng, Yangdi Lyu
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引用次数: 0

摘要

分支覆盖在注册-转移级(RTL)模型的功能验证中非常重要。虽然随机测试可以覆盖大多数易于触及的分支,但在当今的工业设计中仍有许多难以激活的分支。这些剩余的分支通常是bug和硬件木马的来源。使用形式化方法的定向测试生成方法可以有效地激活特定分支,但受状态爆炸问题的限制。半形式化的方法,如concolic测试,通过一次探索一条路径来提高可伸缩性。本文提出了一种基于状态跟踪的搜索启发式算法(STSearch)的角分支测试框架。该方法基于一种新的启发式指标来评估当前状态和目标分支条件之间的距离,启发式地生成和评估输入序列。启发式指标的设计既利用了设计的静态结构特性,又利用了动态仿真的状态。现有的圆锥测试方法通过求解路径约束每轮生成一条完整的新路径,与之相比,本文方法中基于循环的启发式搜索更为有效。实验结果表明,我们的方法在运行时间和内存使用方面都明显优于最先进的方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
STSearch: State Tracing-based Search Heuristics for RTL Validation
Branch coverage is important in the functional val-idation of Register-Transfer-Level (RTL) models. While random tests can cover the majority of easy-to-reach branches, there are still many hard-to-activate branches in today's industrial designs. These remaining corner branches are typically the source of bugs and hardware trojans. Directed test generation approaches using formal methods effectively activate a specific branch but are limited by the state explosion problem. Semi-formal methods, such as concolic testing, improve the scalability by exploring one path at a time. This paper presents a novel concolic testing framework to exercise the corner branches through state tracing-based search heuristics (STSearch). The proposed approach heuristically gen-erates and evaluates input sequences based on a novel heuristic indicator that evaluates the distance between the current state and the target branch condition. The heuristic indicator is designed to utilize both the static structural property of the design and the state from dynamic simulation. Compared to the existing concolic testing approaches, where a full new path is generated in each round by solving path constraints, the cycle-based heuristic search in the proposed approach is more effective and efficient. Experimental results show that our approach significantly outperforms the state-of-the-art approaches in both running time and memory usage.
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