SYNCHRONIZATION SYSTEM FOR APPLICATION LIFECYCLE MANAGEMENT

    公开(公告)号:US20250123840A1

    公开(公告)日:2025-04-17

    申请号:US18378924

    申请日:2023-10-11

    Abstract: Methods, apparatus, and processor-readable storage media for implementing synchronization systems for ALM are provided herein. An example computer-implemented method includes identifying ALM tools in conjunction with at least one software application development task; establishing a connection between at least a first and at least a second of the ALM tools using one or more APIs associated with the at least a first ALM tool and the at least a second ALM tool; determining data mapping rules and data transformation rules associated with the at least a first ALM tool and the at least a second ALM tool; and synchronizing data, related to the at least one software application development task, from the at least a first to the at least a second ALM tool, via the connection and in accordance with at least a portion of the data mapping rule(s) and the data transformation rule(s).

    Multi-level console interface for computing devices

    公开(公告)号:US12190127B2

    公开(公告)日:2025-01-07

    申请号:US18114470

    申请日:2023-02-27

    Abstract: An apparatus comprises a processing device configured to detect a user login to access a console of a computing device implementing a multi-level console interface comprising two or more levels each associated with a set of criteria, goals to be achieved, and actions relevant for achieving the goals. The processing device is also configured to determine a current state of the computing device, and to select a given level of the multi-level console interface based at least in part on mapping the current state to a given set of criteria associated with the given level. The processing device is further configured to provide, via the console of the computing device, an interface screen corresponding to the given level, the interface screen displaying the actions relevant for achieving the goals of the given level to facilitate transitioning of the computing device from the current state to a desired state.

    Determining differences between web elements of different versions of a web application

    公开(公告)号:US11971866B2

    公开(公告)日:2024-04-30

    申请号:US17956967

    申请日:2022-09-30

    CPC classification number: G06F16/219 G06F16/2246 G06F16/81

    Abstract: An apparatus comprises a processing device configured to select first and second versions of at least a given portion of a web application, to obtain first and second document object model structures of the first and second versions of the given portion of the web application, and to generate, based at least in part on the first and second document object model structures, first and second tree structures, the first and second tree structures comprising nodes representing web elements of the given portion of the web application. The processing device is also configured to identify node differences between the first and second tree structures, to generate information characterizing differences between web elements in the given portion of the first and second versions of the web application, and to initiate automated action based at least in part on the generated information.

    PRIORITY-DRIVEN MIGRATION OPTIMIZATION SYSTEM

    公开(公告)号:US20250138865A1

    公开(公告)日:2025-05-01

    申请号:US18384931

    申请日:2023-10-30

    Abstract: Methods, system, and non-transitory processor-readable storage medium for a component development migration system are provided herein. An example method includes a reverse proxy server that receives a Hypertext Transfer Protocol (HTTP) request from a client system. The reverse proxy server intercepts the HTTP request between the client system and a server. A listener module receives a digital footprint of the HTTP request, where the digital footprint identifies a feature associated with an enterprise application. The method determines a feature score associated with the feature, and an overall feature score using a weighted feature score and a weighted feature priority score. The method then migrates development of a component of the enterprise application to a second enterprise application according to the overall feature score.

    CLASSIFICATION AS-A-SERVICE FOR ENTERPRISE RESOURCE PLANNING SYSTEMS

    公开(公告)号:US20250111330A1

    公开(公告)日:2025-04-03

    申请号:US18479186

    申请日:2023-10-02

    Abstract: The technology described herein is directed towards product classification across multiple contexts within an enterprise environment, e.g., based on stock keeping unit (SKU-) related data. Relevant SKU attributes and patterns for each context are used to train machine learning-based classification models, which are then used to classify descriptive data of a product, such as one or more modules of a SKU. In one implementation, natural language processing and vectorization of input data are described to provide appropriate input to the trained classifier. Context-specific rules derived from domain knowledge and regulatory guidelines can be integrated to refine the classifications made by the model. The system incorporates integration with enterprise resource planning (ERP) systems, enabling efficient data management and classification within an existing infrastructure.

    SYSTEM AND METHODS FOR SELF-SERVICE TEST DATA FOR WEB APPLICATIONS

    公开(公告)号:US20250004924A1

    公开(公告)日:2025-01-02

    申请号:US18214567

    申请日:2023-06-27

    Abstract: Methods, system, and non-transitory processor-readable storage medium for a digifootprint use case capturing system are provided herein. An example method includes a listener module that receives a Hypertext Transfer Protocol (HTTP) request from a client system, where the reverse proxy server intercepts the HTTP request between the client system and a server. A listener module associated with the reverse proxy server captures a digital footprint of the HTTP request, and a transmitter module updates an automation code repository with normalized test data obtained from the digital footprint.

    CONVERTING TEXT DATA TO VIDEO DATA USING ARTIFICIAL INTELLIGENCE TECHNIQUES

    公开(公告)号:US20240378776A1

    公开(公告)日:2024-11-14

    申请号:US18196129

    申请日:2023-05-11

    Abstract: Methods, apparatus, and processor-readable storage media for converting text data to video data using artificial intelligence techniques are provided herein. An example computer-implemented method includes converting text data associated with a task into multiple action statements relating to user performance of at least a portion of the task; generating video data by processing at least a portion of the multiple action statements using one or more artificial intelligence techniques; compiling at least a portion of the generated video data into at least one video sequence corresponding to at least one action workflow for the user performance of the at least a portion of the task; and performing one or more automated actions based at least in part on the at least one video sequence.

    CONSTRUCTING AND EXECUTING SEARCH QUERIES WITH TERMS SEMANTICALLY SIMILAR TO THOSE OF A SEARCH REQUEST

    公开(公告)号:US20240289358A1

    公开(公告)日:2024-08-29

    申请号:US18114467

    申请日:2023-02-27

    CPC classification number: G06F16/3325 G06F16/3334 G06F40/247 G06F40/30

    Abstract: An apparatus comprises a processing device configured to receive and parse a search request related to a given event to identify confident terms, and to determine a first subset of the confident terms which indirectly reference the given event and a second subset of the confident terms which are not in the first subset. The processing device is also configured to identify, for a given confident term in the second subset, terms having at least a threshold level of semantic similarity with the given confident term, and to construct a primary search query comprising the first and second subsets of the confident terms and additional search queries comprising the first subset of the confident terms and the identified one or more terms having at least the threshold level of semantic similarity with the given confident term. The processing device is further configured to execute the primary and additional search queries.

    DETERMINING DIFFERENCES BETWEEN WEB ELEMENTS OF DIFFERENT VERSIONS OF A WEB APPLICATION

    公开(公告)号:US20240111740A1

    公开(公告)日:2024-04-04

    申请号:US17956967

    申请日:2022-09-30

    CPC classification number: G06F16/219 G06F16/2246 G06F16/81

    Abstract: An apparatus comprises a processing device configured to select first and second versions of at least a given portion of a web application, to obtain first and second document object model structures of the first and second versions of the given portion of the web application, and to generate, based at least in part on the first and second document object model structures, first and second tree structures, the first and second tree structures comprising nodes representing web elements of the given portion of the web application. The processing device is also configured to identify node differences between the first and second tree structures, to generate information characterizing differences between web elements in the given portion of the first and second versions of the web application, and to initiate automated action based at least in part on the generated information.

    MACHINE-LEARNING BASED GENERATION OF DATABASE CONFIGURATIONS FOR DATABASES ASSOCIATED WITH APPLICATIONS

    公开(公告)号:US20250077482A1

    公开(公告)日:2025-03-06

    申请号:US18240643

    申请日:2023-08-31

    Abstract: An apparatus comprises at least one processing device configured to obtain information characterizing a user interface (UI) of an application, the obtained information comprising an image of the UI and textual data associated with the UI. The processing device is also configured to generate, by processing the image utilizing a first machine learning model, a first data structure characterizing data fields corresponding to UI components in the UI. The processing device is further configured to generate, by processing the textual data utilizing a second machine learning model, a second data structure characterizing relationships between the data fields. The processing device is further configured to determine, based on the first and second data structures, a database 10 configuration comprising an organization of the data fields into tables for a database associated with the application. The processing device is further configured to generate the database in accordance with the determined database configuration.

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