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A Generic Static Analysis Framework for Domain-specific Languages

机译:用于域的域语言的通用静态分析框架

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Software used to monitor and control operations within an automation system is defined using domain-specific languages. Latent errors in the control code, if left undetected, can lead to unexpected system failures compromising the safety and the security of the automation system. Traditional analysis techniques are insufficient to detect such errors as they do not cater specifically to the underlying domain-specific language. However, given the diversity of different automation domains, there is no standard platform for analysis of these languages. This paper proposes a generic static analysis framework for domain-specific languages used in the automation domain. The analysis approach exhaustively detects runtime errors in control code and ensures compliance to good programming practices. These runtime errors and coding violations are checked against abstract syntax trees and control flow graphs derived from the code. Data Flow Analysis (DFA), Abstract interpretation and pattern-based matching techniques are used to identify domain specific errors and coding violations for control languages.
机译:用于监视和控制自动化系统中操作的软件使用特定于域的语言定义。控制代码中的潜在错误,如果未被发现,可能会导致意外的系统故障影响自动化系统的安全性和安全性。传统的分析技术不足以检测此类错误,因为它们不具体地迎合底层域的特定语言。然而,鉴于不同自动化域的多样性,没有用于分析这些语言的标准平台。本文提出了一种用于自动化域中使用的域特定语言的通用静态分析框架。分析方法详细地检测控制代码中的运行时误差,并确保符合良好的编程实践。这些运行时错误和编码违规是针对抽象语法树检查的,并控制从代码派生的流程图。数据流分析(DFA),抽象解释和基于模式的匹配技术用于识别控制语言的域特定错误和编码违规。

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