Abstract: To support adding functionality to applications at a layer of abstraction above language-specific implementations of AOP, a language for implementing AOP facilitates runtime monitoring and analysis of an application independent of the language of the application. Aspects can be created for applications written in any supported language. Program code underlying implementations of aspects can be executed based on detecting triggering events during execution of the application. Routines written with the AOP language comprise event-based aspect code triggers that indicate an event which may occur during execution of the application and the associated aspect code to be executed. An agent deployed to a runtime engine to monitor the application detects events and evaluates contextual information about the detected events against the aspect triggers to determine if aspect code should be executed to perform further monitoring and analysis of the executing application.

Abstract: To facilitate runtime monitoring and analysis of an application without modifying the actual application code, an agent monitors and analyzes an application through detection and evaluation of invocations of an API of a runtime engine provided for execution of the application. The agent registers to receive events which are generated upon invocation of target functions of the runtime engine API based on its load. Once loaded, the agent initially determines the language and language version number of the runtime engine. The agent determines associations of events for which to monitor and corresponding analysis code to execute upon detection of the invocations based on the language and version number information. When the agent detects an event during execution of the application based on invocations of the runtime engine API, the agent can monitor and analyze execution of the application based on execution of analysis code corresponding to the detected event.

Abstract: Representations of hierarchical structures identified by source and target file storage directories are displayed on a display device. Inconsistencies are identified between the hierarchical structures identified by the source and target file storage directories. Graphical interconnections are displayed that extend at least partially between locations of at least some of the identified inconsistencies. Refactoring action indicia are displayed that are user selectable and are associated with defined actions performed by a file directory controller to modify the hierarchical structure identified by the target file storage directory to resolve at least some of the inconsistencies identified between the hierarchical structures identified by the source and target file storage directories.

Abstract: Techniques are disclosed relating to building a graph data structure based on information associated with a plurality of services available over a network. The information may include datasets associated with a plurality of software services available to the set of users. The datasets may be analyzed, wherein the analyzing comprises determining, using one or more machine learning algorithms, a plurality of objects, including objects representing ones of the set of users and a plurality of computing activities. A graph data structure may be formed, comprising the plurality of objects, that indicates relationships between the plurality of objects. The graph data structure may be updated in response to detecting additional computing activities of one or more of the set of users. A plot of a subset of the plurality of objects in the graph data structure may be generated in response to a request. The plot may be caused to be displayed on a display.

Abstract: Techniques are disclosed relating to training a model based a graph data structure. A graph data structure comprising a plurality of objects may be accessed, wherein plurality of objects include objects that represent ones of a set of users and a plurality of computing activities of the set of users within a computing domain. A subset of the plurality of objects that are associated with one or more particular criteria may be identified. A model may be trained using data associated with the subset, wherein the model generates predictive assessments of respective objects within the subset with respect to the one or more particular criteria. A request may be received for a first predictive assessment of a first object in the graph data structure. The first predictive assessment of the first object may be generated using the model.

Abstract: Representations of hierarchical structures identified by source and target file storage directories are displayed on a display device. Inconsistencies are identified between the hierarchical structures identified by the source and target file storage directories. Graphical interconnections are displayed that extend at least partially between locations of at least some of the identified inconsistencies. Refactoring action indicia are displayed that are user selectable and are associated with defined actions performed by a file directory controller to modify the hierarchical structure identified by the target file storage directory to resolve at least some of the inconsistencies identified between the hierarchical structures identified by the source and target file storage directories.