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Identifying domain axioms using binary decision diagrams

机译:使用二进制决策图识别领域公理

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摘要

Statically analyzing requirements specifications to assure that they possess desirable properties is a useful activity in any rigorous software development project. The analysis is performed on an abstraction of the original requirements specification. The abstractions in the model may lead to spurious errors in the analysis output. Spurious errors are errors that are reported to occur under certain conditions, but information abstracted from the model precludes the conditions from being satisfied in the original model. A high ratio of spurious errors to true errors in the analysis output makes it difficult, error-prone, and time consuming to find and correct the true errors. In this paper we describe a technique that uses binary decision diagrams to help the analyst identify the abstractions that are lending to excessive spurious errors in the analysis output. Information about these abstractions can then be incorporated into the analysis to eliminate the corresponding spurious error reports.
机译:在任何严格的软件开发项目中,静态分析需求规范以确保它们具有所需的属性是一项有用的活动。分析是对原始需求规范的抽象。模型中的抽象可能会导致分析输出中出现虚假错误。虚假错误是指在某些情况下会发生的错误,但是从模型中提取的信息会阻止条件在原始模型中得到满足。分析输出中的虚假错误与真实错误的比率很高,这使得查找和校正真实错误变得困难,容易出错且耗时。在本文中,我们描述了一种使用二进制决策图来帮助分析人员确定导致分析输出中出现过多虚假错误的抽象的技术。然后可以将有关这些抽象的信息合并到分析中,以消除相应的虚假错误报告。

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