Debugging through causality and temporal pattering in a event processing system

    公开(公告)号:US11157392B2

    公开(公告)日:2021-10-26

    申请号:US16117101

    申请日:2018-08-30

    摘要: Techniques for visualizing events in a distributed system are provided. One or more recordings identifying events occurring on a software agent are received, where two of the events occurred effectively simultaneously. A visualization showing a timeline for the software agent is generated, where the visualization represents the events as icons on the timeline based on times associated with the events, and where the visualization includes a stacked icon representing the two events that occurred effectively simultaneously. A request indicating the stacked icon is received, and the stacked icon is updated to present a semi-circle arrangement of icons representing the two events that occurred effectively simultaneously. A causal chain of events related to a first event corresponding to the stacked icon is determined, and the visualization is updated based on the causal chain of events to present an ordered sequence of events.

    DEBUGGING THROUGH CAUSALITY AND TEMPORAL PATTERING IN A EVENT PROCESSING SYSTEM

    公开(公告)号:US20190004933A1

    公开(公告)日:2019-01-03

    申请号:US16117101

    申请日:2018-08-30

    IPC分类号: G06F11/36 G06F3/0481

    摘要: Techniques for visualizing events in a distributed system are provided. One or more recordings identifying events occurring on a software agent are received, where two of the events occurred effectively simultaneously. A visualization showing a timeline for the software agent is generated, where the visualization represents the events as icons on the timeline based on times associated with the events, and where the visualization includes a stacked icon representing the two events that occurred effectively simultaneously. A request indicating the stacked icon is received, and the stacked icon is updated to present a semi-circle arrangement of icons representing the two events that occurred effectively simultaneously. A causal chain of events related to a first event corresponding to the stacked icon is determined, and the visualization is updated based on the causal chain of events to present an ordered sequence of events.

    Facilitating user input by predicting target storage locations

    公开(公告)号:US11693526B2

    公开(公告)日:2023-07-04

    申请号:US17111142

    申请日:2020-12-03

    摘要: A method, computer system, and a computer program product for modifying a user interface. Attributes of a source object identified by a user in connection with a user input for storing the source object are determined. Attributes of one or more target storage locations are determined. A target storage location for storing the source object is predicted, along with a confidence value associated with the prediction. The prediction is made using a machine learning model that predicts the predicted target storage location and associated confidence value based on the determined attributes of the source object. A plurality of target storage location usage patterns are determined. The user interface is modified based on the predicted target storage location.

    FACILITATING USER INPUT BY PREDICTING TARGET STORAGE LOCATIONS

    公开(公告)号:US20220179932A1

    公开(公告)日:2022-06-09

    申请号:US17111142

    申请日:2020-12-03

    摘要: A method, computer system, and a computer program product for modifying a user interface. Attributes of a source object identified by a user in connection with a user input for storing the source object are determined. Attributes of one or more target storage locations are determined. A target storage location for storing the source object is predicted, along with a confidence value associated with the prediction. The prediction is made using a machine learning model that predicts the predicted target storage location and associated confidence value based on the determined attributes of the source object. A plurality of target storage location usage patterns are determined. The user interface is modified based on the predicted target storage location.