Abstract: System and methods for IoT event detector correctness verification. Detector models (e.g., state-based models including variables, states, transitions and actions) take IoT device data as input and detect, based on the data, events that triggers actions. To verify a correctness of the models prior to deploying the models at scale, an event detector model correctness checker obtains a representation of a definition of the model, verifies, based on analysis of the model definition, whether the model complies with correctness properties, and generates a report indicating whether the model complies. Example correctness properties include a reachability correctness property that indicates that respective states or actions are reachable according to the definition of the event detector model. The analysis may be accessed via an interface element and may result in generation of a report that identifies a location of non-compliance within the model definition.

Abstract: System and methods for IoT event detector correctness verification. Detector models (e.g., state-based models including variables, states, transitions and actions) take IoT device data as input and detect, based on the data, events that triggers actions. To verify a correctness of the models prior to deploying the models at scale, an event detector model correctness checker obtains a representation of a definition of the model, verifies, based on analysis of the model definition, whether the model complies with correctness properties, and generates a report indicating whether the model complies. Example correctness properties include a reachability correctness property that indicates that respective states or actions are reachable according to the definition of the event detector model. The analysis may be accessed via an interface element and may result in generation of a report that identifies a location of non-compliance within the model definition.

Abstract: System and methods for IoT event detector correctness verification. Detector models (e.g., state-based models including variables, states, transitions and actions) take IoT device data as input and detect, based on the data, events that triggers actions. To verify a correctness of the models prior to deploying the models at scale, an event detector model correctness checker obtains a representation of a definition of the model, verifies, based on analysis of the model definition, whether the model complies with correctness properties, and generates a report indicating whether the model complies. Example correctness properties include a reachability correctness property that indicates that respective states or actions are reachable according to the definition of the event detector model. The analysis may be accessed via an interface element and may result in generation of a report that identifies a location of non-compliance within the model definition.

Abstract: Techniques for comparing documents may be provided. For example, a comparison between layouts of the documents may be performed. The comparison may include segmenting the documents into blocks, where an arrangement of blocks of a document represents a layout of the document. Once segmented, similarity metrics, such as distances, between blocks of one document and blocks of the other document may be computed. The similarity metrics may be used to match the blocks between the documents. Further, the similarity metrics between the matched blocks may be added to determine an overall similarity metric between the documents. This overall similarity metric may indicate how similar the documents may be.

Abstract: Techniques for comparing documents may be provided. For example, a comparison between layouts of the documents may be performed. The comparison may include segmenting the documents into blocks, where an arrangement of blocks of a document represents a layout of the document. Once segmented, similarity metrics, such as distances, between blocks of one document and blocks of the other document may be computed. The similarity metrics may be used to match the blocks between the documents. Further, the similarity metrics between the matched blocks may be added to determine an overall similarity metric between the documents. This overall similarity metric may indicate how similar the documents may be.