{"id":698341,"date":"2020-10-15T16:35:40","date_gmt":"2020-10-15T23:35:40","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/?post_type=msr-research-item&p=698341"},"modified":"2024-10-08T14:40:47","modified_gmt":"2024-10-08T21:40:47","slug":"a-general-framework-for-compositional-network-modeling","status":"publish","type":"msr-research-item","link":"https:\/\/www.microsoft.com\/en-us\/research\/publication\/a-general-framework-for-compositional-network-modeling\/","title":{"rendered":"A General Framework for Compositional Network Modeling"},"content":{"rendered":"

We advocate for an approach to network modeling and analysis based on a common intermediate language. Unlike today, where each tool builds a custom model and analysis engine for its target network functionality, we argue that network functionality should be expressed in a common language. This approach makes it easier to expand formal analysis to new functionality and analyze interactions between dependent functionalities (e.g., routing and packet filtering). We demonstrate the feasibility of this approach by developing an intermediate language called Zen and three different analyses for programs in that language. For representative data plane and control plane functionalities, we find that Zen reduces the modeling effort by an order of magnitude, while providing analysis performance that matches custom tools.<\/p>\n

https:\/\/github.com\/microsoft\/Zen (opens in new tab)<\/span><\/a><\/p>\n","protected":false},"excerpt":{"rendered":"

We advocate for an approach to network modeling and analysis based on a common intermediate language. Unlike today, where each tool builds a custom model and analysis engine for its target network functionality, we argue that network functionality should be expressed in a common language. This approach makes it easier to expand formal analysis to 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