论文标题
使用规则学习和亚组发现技术加速系统级调试
Accelerating System-Level Debug Using Rule Learning and Subgroup Discovery Techniques
论文作者
论文摘要
我们提出了一种使用基于规则的技术加速系统级调试的根源的程序。我们描述了该过程及其如何提供高质量的调试提示，以减少调试工作。这包括来自许多测试日志的工程功能的启发式方法，以及用于生成强大调试提示的数据分析技术。作为案例研究，我们将这些技术用于电源管理（PM）设计功能软件包C8的根源失败，并显示了它们的有效性。此外，我们提出了一种挖掘引起根源的经验和结果的方法，以加速未来的调试活动并减少对验证专家的依赖。我们认为，这些技术也对不同级别的抽象级别的其他验证活动也有益，对于复杂的硬件，软件和固件系统，包括前硅和后硅。
We propose a root-causing procedure for accelerating system-level debug using rule-based techniques. We describe the procedure and how it provides high quality debug hints for reducing the debug effort. This includes the heuristics for engineering features from logs of many tests, and the data analytics techniques for generating powerful debug hints. As a case study, we used these techniques for root-causing failures of the Power Management (PM) design feature Package-C8 and showed their effectiveness. Furthermore, we propose an approach for mining the root-causing experience and results for reuse, to accelerate future debug activities and reduce dependency on validation experts. We believe that these techniques are beneficial also for other validation activities at different levels of abstraction, for complex hardware, software and firmware systems, both pre-silicon and post-silicon.
