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- W3153343958 abstract "The use of structured natural languages to capture requirements provides a reasonable trade-off between ambiguous natural language and unintuitive formal notations. There are two major challenges in making structured natural language amenable to formal analysis: (1) formalizing requirements as formulas that can be processed by analysis tools and (2) ensuring that the formulas conform to the semantics of the structured natural language. fretish is a structured natural language that incorporates features from existing research and from NASA applications. Even though fretish is quite expressive, its underlying semantics is determined by the types of four fields: scope, condition, timing, and response. Each combination of field types defines a template with Real-Time Graphical Interval Logic (RTGIL) semantics. We have developed a framework that constructs temporal logic formulas for each template compositionally, from its fields. The compositional nature of our algorithms facilitates maintenance and extensibility. Our goal is to be inclusive not only in terms of language expressivity, but also in terms of requirements analysis tools that we can interface with. For this reason we generate metric-temporal logic formulas with (1) exclusively future-time operators, over both finite and infinite traces, and (2) exclusively past-time operators. To establish trust in the produced formalizations for each template, our framework: (1) extensively tests the generated formulas against the template semantics and (2) proves equivalence between its past-time and future-time formulas. Our approach is available through the open-source tool fret and has been used to capture and analyze requirements for a Lockheed Martin Cyber–Physical System challenge." @default.
- W3153343958 created "2021-04-26" @default.
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- W3153343958 date "2021-09-01" @default.
- W3153343958 modified "2023-10-16" @default.
- W3153343958 title "Automated formalization of structured natural language requirements" @default.
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- W3153343958 doi "https://doi.org/10.1016/j.infsof.2021.106590" @default.
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