论文标题
基于信号的时间属性的跟踪诊断
Trace Diagnostics for Signal-based Temporal Properties
论文作者
论文摘要
大多数痕量检查工具只会产生布尔判决。但是,当痕量侵犯财产时,工程师通常会检查痕迹以了解违规原因。这种手动诊断时间耗时且容易出错。现有的方法与诊断能力相辅相成,要么产生低级解释,这些解释几乎无法由工程师理解,要么不支持基于复杂的信号的时间属性。在本文中,我们提出了TD-SB-TEMPSY,这是一种使用SB-Tempsy-DSL表达的属性的痕量诊断方法。鉴于违反财产的财产和痕迹,TD-SB-Tempsy确定了违反财产的根本原因。 TD-SB-TEMPSY依赖于违规原因的概念,该原因是系统的行为之一,可能导致违反财产的行为和诊断,这些行为与违规原因相关,并提供其他信息来帮助工程师了解违规原因。作为TD-SB-Tempsy的一部分,我们提出了一种语言敏捷方法来定义违规原因和诊断。在我们的背景下,它的应用导致了34起违规原因的目录,每种违规原因与一个诊断相关,该诊断是针对SB-Tempsy-DSL表达的属性量身定制的。我们评估了TD-SB-TEMPSY在两个数据集上的适用性,其中包括一个基于复杂的工业案例研究。结果表明,TD-SB-TEMPSY可以在1分钟内完成约83.66%的痕量质量组合,占工业数据集中的痕量特性组合,在这些病例中诊断为诊断为99.84%的诊断。此外,它还针对其他数据集中所有痕量特性组合都产生了诊断。这些结果表明,在大多数情况下,我们的工具适用且有效。
Most of the trace-checking tools only yield a Boolean verdict. However, when a property is violated by a trace, engineers usually inspect the trace to understand the cause of the violation; such manual diagnostic is time-consuming and error-prone. Existing approaches that complement trace-checking tools with diagnostic capabilities either produce low-level explanations that are hardly comprehensible by engineers or do not support complex signal-based temporal properties. In this paper, we propose TD-SB-TemPsy, a trace-diagnostic approach for properties expressed using SB-TemPsy-DSL. Given a property and a trace that violates the property, TD-SB-TemPsy determines the root cause of the property violation. TD-SB-TemPsy relies on the concepts of violation cause, which characterizes one of the behaviors of the system that may lead to a property violation, and diagnoses, which are associated with violation causes and provide additional information to help engineers understand the violation cause. As part of TD-SB-TemPsy, we propose a language-agnostic methodology to define violation causes and diagnoses. In our context, its application resulted in a catalog of 34 violation causes, each associated with one diagnosis, tailored to properties expressed in SB-TemPsy-DSL. We assessed the applicability of TD-SB-TemPsy on two datasets, including one based on a complex industrial case study.The results show that TD-SB-TemPsy could finish within a timeout of 1 min for ~83.66% of the trace-property combinations in the industrial dataset, yielding a diagnosis in ~99.84% of these cases. Moreover, it also yielded a diagnosis for all the trace-property combinations in the other dataset. These results suggest that our tool is applicable and efficient in most cases.