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Constructing a Safety Case forAutomatically Generated Code from Formal Program Verification Information

机译:从正式的节目验证信息构建安全案例,以外地生成代码

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Formal methods can in principle provide the highest levels of assurance of code safety by providing formal proofs as explicit evidence for the assurance claims. However, the proofs are often complex and difficult to relate to the code, in particular if it has been generated automatically. They may also be based on assumptions and reasoning principles that are not justified. This causes concerns about the trustworthiness of the proofs and thus the assurance claims. Here we present an approach to systematically construct safety cases from information collected during a formal verification of the code, in particular from the construction of the logical annotations necessary for a formal, Hoare-style safety certification. Our approach combines a generic argument that is instantiated with respect to the certified safety property (i.e., safety claims) with a detailed, program-specific argument that can be derived systematically because its structure directly follows the course the annotation construction takes through the code. The resulting safety cases make explicit the formal and informal reasoning principles, and reveal the top-level assumptions and external dependencies that must be taken into account. However, the evidence still comes from the formal safety proofs. Our approach is independent of the given safety property and program, and consequently also independent of the underlying code generator. Here, we illustrate it for the AutoFilter system developed at NASA Ames.
机译:正式方法原则上可以通过提供正式证据作为保证索赔的明确证据提供代码安全的最高水平。然而,证据通常很复杂,并且难以涉及代码,特别是如果它已经自动生成。他们也可以基于假设和不理解的原则。这导致对证据可靠性以及保证索赔的担忧。在这里,我们提出了一种方法来系统地构建安全案例,从代码正式核实期间收集的信息,特别是从正式,HOARE风格安全认证所需的逻辑注释的构建。我们的方法将在经过认证的安全性(即安全索赔)上实例化的通用参数,其中包含可以系统地从系统上派生的详细的,程序特定的参数,因为它的结构直接遵循课程,注释构造通过代码。由此产生的安全案件明确了正式和非正式的推理原则,并揭示了必须考虑到的顶级假设和外部依赖性。但是,证据仍然来自正式的安全证据。我们的方法独立于给定的安全性和计划,因此也独立于底层代码发生器。在这里,我们说明了在NASA AMES开发的自动滤波器系统。

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