Techniques for determining anomalous user behavior in connection with an online application are disclosed. In one embodiment, a method is disclosed comprising obtaining user behavior data in connection with a user of an application, generating feature data using the obtained user behavior data, obtaining one or more user behavior anomaly predictions from one or more anomaly prediction models trained to output a user behavior anomaly prediction in response to the feature data. Each user behavior anomaly prediction indicates a probability that the user behavior is anomalous. A user behavior anomaly determination is made using the user behavior anomaly prediction(s).

A software robot is designed to carry out an activity (e.g., a mouse click, a text input, etc.) on a target element (e.g., a button, an input field, etc.) of a user interface. The robot's code specification is configured to include an on-screen image of the target element and a text displayed by the target element. The robot is configured to automatically identify the target element at runtime according to an element ID specified in the source-code of the user interface, and when such identification fails, to identify the target element according to the text and image stored in the robot's code.

Provided is an authentication system that improves user convenience. This authentication system includes at least one first terminal, a plurality of second terminals, and a server device. The first terminal is capable of providing services using a biometric authentication function or non-biometric authentication function. Each of the second terminals is capable of switching between a biometric authentication function and a non-biometric authentication function and capable of providing services using the biometric authentication function or non-biometric authentication function. The server device is connected to the first terminal and the plurality of second terminals. The server device calculates the rate of usage of a biometric authentication function by the at least one first terminal. The server device determines an operation mode for at least one of the plurality of second terminals on the basis of the calculated rate of usage.

Embodiments are disclosed for providing workout recommendations based on monitored user inputs with a digital design system. In particular, in one or more embodiments, the disclosed systems and methods comprise receiving a series of inputs performed by a user with an application, categorizing each input in the series of inputs into a user interaction type, where each of the plurality of user interaction types is associated with a counter maintaining a detected user input count, determining that a first counter associated with a first user interaction type has exceeded a threshold amount, identifying a first action associated with the first user interaction type, and providing a notification message including information associated with the first action.

Systems, methods, and computer-readable media are disclosed for an improved database. The systems, methods, and computer-readable media described herein may enhance the response time of databases and improve user experiences. In an example method described herein, a database monitoring system may receive instructions to perform one or more data monitoring operations comprising counting an occurrence of a first value within at least a portion of items stored in a database. The method may include determining a length of a first window of time and fetching, from a first location of a data store of the database, data indicative of a total count of the occurrence of the first value at a time associated with the beginning of the first window of time. In turn, the monitoring system may store data representing the first count in the first memory.

A system detects a user's mood and in response establishes computer settings including computer game settings, recommends social network interactions, advises other users, alters task scheduling, and in general enhances collective group mood, collective productivity, social interaction, and engagement.

A method by a network device for dynamically detecting emotional states of a user operating a client end station to interact with an application. The method includes receiving information regarding user inputs received by the client end station from the user while the user interacted with the application during a particular time period and determining an emotional state of the user based on analyzing the information and information regarding user inputs received by the client end station from the user while the user interacted with the application during one or more previous time periods that together with the particular time period form a time window.

Disclosed herein are systems and method for customizing a user workspace environment using user action sequence analysis. In one exemplary aspect, a method may comprise detecting user actions in a user workspace environment that provides access to a plurality of workspace elements further comprising a plurality of files and a plurality of applications and identifying a plurality of user action sequences based on each timestamp of a respective user action. The method may comprise generating action sequence groups, each comprising a unique subset of the user action sequences and sequence trigger. In response to detecting a particular sequence trigger, the method may comprise executing a corresponding customization action that alters the user workspace environment such that an amount of steps and/or processing time to perform in the user workspace environment to access workspace elements associated with the associated action sequence group is reduced.

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for evaluating interactions with a user interface of an application are disclosed. In one aspect, a method includes, for each of a plurality of different user sessions of a native application, accessing frame bundles that each include data representing content presented by a frame of a user interface of the native application at a given time. Each frame bundle includes at least a portion of a view tree of the native application used to generate the user interface at the given time and data specifying content presented by each view of the portion of the view tree. Based on the frame bundles, playback data are generated that present visual changes of the user interface corresponding to changes to the view trees.

A computer-implemented method includes downloading respective instances of an enterprise mobile application to a plurality of mobile devices. The instances of the enterprise mobile applications, while executing on respective mobile devices, capture, for each session, a session log that includes indications of ordered user actions occurring during the session, and optionally time intervals between user actions and/or user attributes. Captured session logs stored at and are mined by one or more servers to discover a particular pattern or sequence of user actions that occurred across multiple, different user sessions. If the number and/or rate of occurrences of the particular pattern is greater than a threshold, a new test case corresponding to the pattern is automatically generated and added to a suite of test cases for the UI functionality of the enterprise mobile application. The updated test suite may be automatically executed on a test version of the enterprise mobile application.