Abstract: Systems, methods, and computer-readable media are disclosed for generating uniform hierarchical views of technical documents irrespective of a file format for the technical document. Metadata definitions may be received that define a technical document hierarchy for the technical document. Based on the metadata definitions, technical data element may be mapped to the technical document hierarchy. The technical document may be generated, the technical document comprising the technical data elements. Based in part on the technical document and the metadata definitions, the uniform hierarchical view may be generated. The uniform hierarchical view may be populated with at least a subset of the technical data elements from the technical document. Once generated, the uniform hierarchical view may be displayed.

Abstract: Programs, systems, and methods for generating electronic reports for electronic reporting to reporting entities. Configuration parameters may be generated comprising metadata defining attributes of the configuration parameters. The configuration parameters may be associated with the reporting entities such that the attributes of the configuration parameters map to electronic reports associated with the reporting entities. Furthermore, the configuration parameters may be associated with a plurality of reporting entities and electronic reports such that a single configuration parameter may be used to generate the plurality of electronic reports.

Abstract: User interface responsiveness is improved using batch interface calls and response processing. To do this, a selection, via a user interface, is obtained of nodes of a hierarchy corresponding to a hierarchical data structure containing information to be presented in the user interface based on the selection. A separate request is sent to a database to obtain information corresponding to each of the nodes. Responses corresponding to a particular request are received from the database. Each response is processed to obtain parsed data in separate threads such that the responses are executable in parallel. The processing of the responses outputs parsed data for the corresponding response. The parsed data is obtained and the parsed data for a particular response is incrementally presented in the user interface as it is obtained.

Abstract: User interface responsiveness is improved using batch interface calls and response processing. To do this, a selection, via a user interface, is obtained of nodes of a hierarchy corresponding to a hierarchical data structure containing information to be presented in the user interface based on the selection. A separate request is sent to a database to obtain information corresponding to each of the nodes. Responses corresponding to a particular request are received from the database. Each response is processed to obtain parsed data in separate threads such that the responses are executable in parallel. The processing of the responses outputs parsed data for the corresponding response. The parsed data is obtained and the parsed data for a particular response is incrementally presented in the user interface as it is obtained.

Abstract: Provided are a system and method that use machine learning to recommend adjustments to digital documents that are included within a report managed by a software application. The system may also provide a trend analysis as part of the recommendation. In one example, the method may include detecting a request to open a digital document from a user via a user interface, populating the user interface with content from the digital document and executing a machine learning model on values within the digital document to identify a value among the values that is to be adjusted to a different value based on previous adjustments by the user to previous reports, activating a user interface element associated with the identified value within the user interface, and in response to a selection of the user interface element, instantiating a display of the different value on the user interface.

Abstract: Provided are a system and method that use machine learning to recommend adjustments to digital documents that are included within a report managed by a software application. The system may also provide a trend analysis as part of the recommendation. In one example, the method may include detecting a request to open a digital document from a user via a user interface, populating the user interface with content from the digital document and executing a machine learning model on values within the digital document to identify a value among the values that is to be adjusted to a different value based on previous adjustments by the user to previous reports, activating a user interface element associated with the identified value within the user interface, and in response to a selection of the user interface element, instantiating a display of the different value on the user interface.

Abstract: Provided are a system and method that use machine learning to identify documents to be excluded from a report or included in a report of a software application. In one example, the method may include receiving document data of a set of documents assigned to a report, executing the machine learning model on the received document data which identifies a document assigned to the set of documents that is to be excluded from the report, displaying, via a user interface, a set of line items corresponding to the set of documents, respectively, activating a user interface element of the identified document within a line item of the identified document, and in response to detecting a selection of the activated user interface element via the user interface, accepting the exclusion of the identified document from the report and move the identified document to a different report.

Abstract: Provided are a system and method that use machine learning to identify documents to be excluded from a report or included in a report of a software application. In one example, the method may include receiving document data of a set of documents assigned to a report, executing the machine learning model on the received document data which identifies a document assigned to the set of documents that is to be excluded from the report, displaying, via a user interface, a set of line items corresponding to the set of documents, respectively, activating a user interface element of the identified document within a line item of the identified document, and in response to detecting a selection of the activated user interface element via the user interface, accepting the exclusion of the identified document from the report and move the identified document to a different report.

Abstract: Programs, systems, and methods for generating electronic reports for electronic reporting to reporting entities. Configuration parameters may be generated comprising metadata defining attributes of the configuration parameters. The configuration parameters may be associated with the reporting entities such that the attributes of the configuration parameters map to electronic reports associated with the reporting entities. Furthermore, the configuration parameters may be associated with a plurality of reporting entities and electronic reports such that a single configuration parameter may be used to generate the plurality of electronic reports.

Abstract: Systems, methods, and computer-readable media are disclosed for unified regression testing. A first set of inputs configured to test a first scenario and a second set of inputs configured to test a second scenario may be received from a user. The first set of inputs may be used to generate a first set of outputs, and the second set of inputs may be used to generate a second set of outputs. A software update may be received. The first set of outputs may be regenerated using the first set of inputs, and the second set of outputs may be regenerated using the second set of inputs. The regenerated first set of outputs may be compared against the first set of outputs, and the regenerated second set of outputs may be compared against the second set of outputs. The comparison results may then be displayed to the user.

Abstract: Systems, methods, and computer-readable media are disclosed for generating uniform hierarchical views of technical documents irrespective of a file format for the technical document. Metadata definitions may be received that define a technical document hierarchy for the technical document. Based on the metadata definitions, technical data element may be mapped to the technical document hierarchy. The technical document may be generated, the technical document comprising the technical data elements. Based in part on the technical document and the metadata definitions, the uniform hierarchical view may be generated. The uniform hierarchical view may be populated with at least a subset of the technical data elements from the technical document. Once generated, the uniform hierarchical view may be displayed.

Abstract: Systems, methods, and computer-readable media are disclosed for unified regression testing. A first set of inputs configured to test a first scenario and a second set of inputs configured to test a second scenario may be received from a user. The first set of inputs may be used to generate a first set of outputs, and the second set of inputs may be used to generate a second set of outputs. A software update may be received. The first set of outputs may be regenerated using the first set of inputs, and the second set of outputs may be regenerated using the second set of inputs. The regenerated first set of outputs may be compared against the first set of outputs, and the regenerated second set of outputs may be compared against the second set of outputs. The comparison results may then be displayed to the user.