Abstract: A system of one or more computers that are configured to generate documentation for microservice-based applications is disclosed. In at least one embodiment, usage information relating to actual usage by one or more users of a plurality of microservices, features extracted from user story information in a backlog tracker, and a call-context graph including information identifying calling functions and called functions in the plurality of microservices are used to generate data that is provided to a natural language generator, which uses the information to automatically generate documentation for the microservice based application.

Abstract: In some examples, a computing device may implement a method that includes receiving microservice profile information at a microservice profiler, performing lexical analysis of the microservice profile information (where the lexical analysis produces tokenized information), generating microservice modification information by performing machine learning analysis of one or more inputs (where the one or more inputs comprise the tokenized information), and outputting the microservice modification information from the microservice profiler. The microservice profile information describes one or more characteristics of a microservice. The lexical analysis is performed by a lexical analysis engine of the microservice profiler, and the machine learning analysis is performed by a machine learning system of the microservice profiler.

Abstract: An apparatus includes at least one processing device including a processor coupled to a memory. The at least one processing device is configured to perform the step of monitoring a level of connectivity, of the at least one processing device, for one or more wireless data networks. The at least one processing device is also configured to perform the step of, responsive to determining that the monitored level of connectivity is at or below a designated threshold level of connectivity, utilizing a messaging protocol of one or more cellular voice networks to transfer web content. The at least one processing device is further configured to perform the step of, responsive to determining that the monitored level of connectivity is above the designated threshold level of connectivity, utilizing the one or more wireless data networks to transfer the web content.

Abstract: A method includes receiving code for computer programming, analyzing the code and extracting a plurality of configuration properties from the code. In the method, one or more configuration files are generated from the extracted plurality of configuration properties, and microservice code is generated from the one or more configuration files. The microservice code is configured for deployment on one or more cloud computing platforms.

Abstract: A method includes identifying an application to be converted into a set of microservices, analyzing software code of the application to identify a plurality of functions as candidates for combination with one another into the set of microservices, monitoring a running instance of the application to generate a calling-context tree identifying interactions among the plurality of functions, and determining a recommended design for the set of microservices based at least in part on the identified interactions among the plurality of functions. The method also includes modifying the recommended design for the set of microservices responsive to activation of user interface features of a graphical user interface providing a visualization of the generated calling-context tree, and generating the set of microservices based at least in part on the modified design.

Abstract: A method includes identifying an application to be converted into a set of microservices, analyzing software code of the application to identify a plurality of functions as candidates for combination with one another into the set of microservices, monitoring a running instance of the application to generate a calling-context tree identifying interactions among the plurality of functions, and determining a recommended design for the set of microservices based at least in part on the identified interactions among the plurality of functions. The method also includes modifying the recommended design for the set of microservices responsive to activation of user interface features of a graphical user interface providing a visualization of the generated calling-context tree, and generating the set of microservices based at least in part on the modified design.

Abstract: A system and method provide an interactive augmented reality experience customized for providing instant employee recognition in the workplace. A client electronic device streams camera image data to an instant recognition system. When the image includes a face, the system automatically identifies the imaged individual. The system then aggregates information about the individual from a variety of sources for transmission to the client electronic device for simultaneous display with the camera image. The system also may automatically generate a video of a person speaking about the individual using a generative adversarial network for streaming to the device in response to user activity. The system further may allow a user of the client electronic device to personalize the augmented reality experience by modifying or annotating the individual's face or body with amusing images using an interactive canvas.

Abstract: A system and method automatically refactor mature program code having interdependent features to remove instructions pertaining to features that are no longer used. To facilitate reduction of the number of feature dependencies to test, instrumentation data are analyzed to determine which of the available features are in actual use. A graph of feature dependencies is built based on the program configuration, and the program code is simulated, according to existing testing protocols, with various combinations of features disabled to determine whether the program continues to function without error. When features are found that can be safely removed, the codebase is automatically refactored to eliminate the implementing code corresponding to the features. The refactored code then may be further automatically retested and deployed into the production environment.

Abstract: Methods, apparatus, and processor-readable storage media for autonomous creation of new microservices and modification of existing microservices are provided herein. An example computer-implemented method includes generating and outputting, to a user via at least one graphical user interface, one or more prompts for user input pertaining to a target microservice; automatically configuring, for the target microservice, one or more microservice components based at least in part on the user input received in response to the one or more prompts; building the target microservice based at least in part on the one or more automatically configured microservice components; and outputting the built target microservice to at least one of a user and one or more cloud platforms.

Abstract: Multiple projection input devices may be permanently attached or temporarily attached to a display device. Each projection input device may project, using one or more projectors, a representation of an input device on a work surface, receive video data from one or more cameras, identify one or more fingers interacting with the representation of the input device, track a motion of the one or more fingers relative to the representation of the input device, predict, using a machine learning algorithm and based on tracking the motion of the one or more fingers relative to the representation of the input device, a particular input being provided, and transmit the particular input to a computing device. The representation of the particular input device may include a representation of one of: a keyboard, a mouse, a trackpad, a numeric keypad, a trackball, or a gaming controller.

Abstract: The disclosed embodiments provide a system for processing data. During operation, the system stores a conversation containing a series of messages exchanged among a number of participants in a first document containing metadata for the conversation; a second document containing message content for the series of messages, wherein the message content includes a fixed position gap between starting or ending positions in consecutive messages in the series of messages; and one or more additional documents storing message metadata for individual messages in the conversation. Next, the system processes a first search across the series of messages in the conversation using an index of the set of documents. The system also processes, using the index, a second search within individual messages in the series of messages as a span query with a distance that is shorter than the fixed position gap.

Abstract: Techniques for enhancing usability and electronic resource efficiency using comment relevance are disclosed herein. In some embodiments, a comment relevance system receives member feature data, including professional identity data such as professional experience or professional skill, and at least one of comment feature data and commenter feature data for comments for post on a social networking service, generates a score for each comment based on the member feature data and the comment or commenter feature data, ranks the comments based on the scores, and causes one or more of the comments to be displayed in a particular position based on the ranking. In some embodiments, the member feature data comprises professional identity data of a member of the social networking service, the comment feature data indicates at least one attribute of the comment, and the commenter feature data indicates at least one attribute of the commenter of the comment.

Abstract: Methods, apparatus, and processor-readable storage media for evaluations performed by applying machine learning and artificial intelligence techniques to multi-modal data are provided herein.

Abstract: Methods, apparatus, and processor-readable storage media for generating context-based question-answer pairs by applying artificial intelligence techniques to context-related data are provided herein.

Abstract: In some examples, a computing device may receive sensor data from a plurality of sensors and determine a location of the computing device in three-dimensions. A calendar application executing on the computing device may be accessed to determine that a first event is currently scheduled. A setting may indicate that a ringer of the computing device is unmuted to enable the ringer to be heard when the computing device receives an incoming communication (e.g., a call, a text, or a message). If the sensor data, the first event, or both satisfy a particular rule of a set of decision rules, the computing device may automatically modify the setting to mute the ringer based on the particular rule. If a user of the computing device modifies the setting to unmute the ringer, the computing device may send modification data associated with the modification to a server.

Abstract: In some examples, a computing device may receive sensor data from a plurality of sensors and determine a location of the computing device in three-dimensions. A calendar application executing on the computing device may be accessed to determine that a first event is currently scheduled. A setting may indicate that a ringer of the computing device is unmuted to enable the ringer to be heard when the computing device receives an incoming communication (e.g., a call, a text, or a message). If the sensor data, the first event, or both satisfy a particular rule of a set of decision rules, the computing device may automatically modify the setting to mute the ringer based on the particular rule. If a user of the computing device modifies the setting to unmute the ringer, the computing device may send modification data associated with the modification to a server.

Abstract: In some examples, a server may determine a browsing history associated with a user, identify activities associated with purchasing a device, and determine features of the device. Individual features may be assigned a corresponding priority based on the browsing history. A machine learning algorithm may predict a configuration of the device based on the features and the corresponding priorities. The server may create a web page that describes a specification of the device based on the configuration and includes a comparison of at least some of the features of the device with other features of similar devices. The server may send a notification with a link to the web page. The web page may enable the user to modify the configuration and modify a price of the device. The server may receive a purchase order to purchase the device and instruct a manufacturing facility to build-to-order the device.

Abstract: Methods, apparatus, and processor-readable storage media for detecting cashback and other related reimbursement frauds are provided herein.

Abstract: A method for forming at least one microservice is provided. The method includes the steps of getting a monolith application to disintegrate, scanning codes of the monolith application, finding one or more nanoservice candidates in the codes, and recommending at least one microservice to a user. Herein, the at least one microservice is a group of one or more selected nanoservice candidates sharing a common characteristic. According to an input of the user, at least one microservice selected among the at least one recommended microservice is generated.

Abstract: A method for forming at least one microservice is provided. The method includes the steps of getting a monolith application to disintegrate, scanning codes of the monolith application, finding one or more nanoservice candidates in the codes, and recommending at least one microservice to a user. Herein, the at least one microservice is a group of one or more selected nanoservice candidates sharing a common characteristic. According to an input of the user, at least one microservice selected among the at least one recommended microservice is generated.