Abstract: Methods, systems, and computer-readable storage media for receiving, through a set of user interfaces (UIs), user input including job configuration information and deployment information for an application, providing a CI/CD job for the application with a CI/CD service using the job configuration information and the deployment information, and triggering, in response to a commit of changes to the application in a repository, automated build of the application, and in response, automatically: generating a development descriptor file at least partially based on the user input, providing an archive file including the development descriptor file, and processing, by the CI/CD job executed by the CI/CD service, the archive file to deploy the application within the target environment.

Abstract: Methods, systems, and computer-readable storage media for receiving, through a set of user interfaces (UIs), user input including job configuration information and deployment information for an application, providing a CI/CD job for the application with a CI/CD service using the job configuration information and the deployment information, and triggering, in response to a commit of changes to the application in a repository, automated build of the application, and in response, automatically: generating a development descriptor file at least partially based on the user input, providing an archive file including the development descriptor file, and processing, by the CI/CD job executed by the CI/CD service, the archive file to deploy the application within the target environment.

Abstract: An application development graphical user interface which includes a drag-and-drop canvas area is provided. User interface elements are configured to be dragged and dropped into the canvas area to design a client application graphical user interface including a filter or a sorter. A configuration panel of the application development user interface providing options and fields for configuring sorter or filter configuration options and for configuring machine learning service configuration options. Machine learning service metadata is generated for the client application. The client application metadata for the client application is deployed and the client application configured present recommendations based on inputs to the filter or sorter using the machine learning service.

Abstract: Methods, systems, and computer-readable storage media for retrieving, by a smart setup system, a component configuration metadata file corresponding to an application, the component configuration metadata file including component metadata representing components that the application uses during runtime, parsing, by a parser of the smart setup system, the component configuration metadata file to provide a set of data objects, each corresponding to a respective component in the set of components, providing, by an emitter of the smart setup system, a set of checking scripts and a set of installation scripts by, for each component in the set of components, providing a checking script and an installation script using a respective data object, and executing, by the smart setup system, each checking script in the set of checking scripts, and in response, receiving a set of check results, each check results indicating whether pre-requisites of a respective component are met.

Abstract: Methods, systems, and computer-readable storage media for receiving, by an application studio, user input indicating two or more artifacts of an enterprise application developed using the application studio, generating, by an enterprise application artifact composer of the application studio, an enterprise application artifact as a universal tag that provides an abstract representation of the enterprise application, and during deployment of the enterprise application: retrieving the enterprise application artifact, determining a target runtime that the enterprise application is to be deployed to, determining a set of dependencies for each artifact of the enterprise application, and for any dependency in the set of dependencies that is absent from the target runtime, retrieving binary code of the dependency from a library to deploy the dependency to the target runtime.

Abstract: Methods, systems, and computer-readable storage media for retrieving, by a smart setup system, a component configuration metadata file corresponding to an application, the component configuration metadata file including component metadata representing components that the application uses during runtime, parsing, by a parser of the smart setup system, the component configuration metadata file to provide a set of data objects, each corresponding to a respective component in the set of components, providing, by an emitter of the smart setup system, a set of checking scripts and a set of installation scripts by, for each component in the set of components, providing a checking script and an installation script using a respective data object, and executing, by the smart setup system, each checking script in the set of checking scripts, and in response, receiving a set of check results, each check results indicating whether pre-requisites of a respective component are met.

Abstract: Methods, systems, and computer-readable storage media for integrating skills into computer-executable applications using a low-code/no-code (LCNC) development platform.

Abstract: Methods, systems, and computer-readable storage media for receiving initial input from a user of the application, the initial input indicating that a UI element is to be generated for the user, receiving context data representative of a context of the application when the input is received, the context data at least partially including a data schema definition of data accessed by the application, prompting the user for input at least partially based on the context data, receiving additional input responsive to the prompting, defining dynamic metadata based on at least a portion of the initial input, at least a portion of the additional input, and at least a portion of the data schema definition, the dynamic metadata including one or more actions that can be executed on data accessed through the UI element, and processing the dynamic metadata to generate the UI element for display in the application.

Abstract: Methods, systems, and computer-readable storage media for receiving, by an application studio, user input indicating two or more artifacts of an enterprise application developed using the application studio, generating, by an enterprise application artifact composer of the application studio, an enterprise application artifact as a universal tag that provides an abstract representation of the enterprise application, and during deployment of the enterprise application: retrieving the enterprise application artifact, determining a target runtime that the enterprise application is to be deployed to, determining a set of dependencies for each artifact of the enterprise application, and for any dependency in the set of dependencies that is absent from the target runtime, retrieving binary code of the dependency from a library to deploy the dependency to the target runtime.

Abstract: Methods, systems, and computer-readable storage media for receiving data as input to a workflow task user interface (UI) provided by a workflow task application, the data being representative of a task of a workflow, and determining that a decision action has been executed in response to user input to a UI element representative of the decision action, and in response, providing, from the workflow task application through an entry application within which the workflow task application executes, an update entity request, inserting, by the entry application, a set of properties to a header of the update entity request, and transmitting the update entity request to a data service to update a data object at least partially based on the data, a workflow service updating an instance of the workflow based on the set of properties.

Abstract: Methods, systems, and computer-readable storage media for Methods, systems, and computer-readable storage media for executing a component packing function to provide an installation package executable to install an instance of an application and including an inner function executable to retrieve components in a set of components of the application, and providing a mapping table that, for each component, associates a locator to an identifier, and, receiving, by an installer within a cloud platform, the installation package, and processing, by the installer, the installation package to install a first instance of the application on a computing device of the cloud platform by determining, for at least one component in the set of components, a respective identifier based on a respective locator using the mapping table, retrieving, by the inner function, the at least one component from a component repository based on the respective identifier, and installing the at least one component on the computing device.

Abstract: Methods, systems, and computer-readable storage media for extracting, by a multi-experience runtime engine and from a metadata file, metadata that is descriptive of an analytics UI for display on a display of a computing device, the metadata including instructions for a binding to a service providing inference using one or more ML models, in response to the binding, transmitting an inference request to the service through a predictive data adapter, the inference request including data representative of a workflow task that is to be executed in a digital workplace, receiving inference results that are responsive to the inference request, and displaying, within the analytics UI, the inference results and at least a portion of the data representative of the workflow task.

Abstract: Methods, systems, and computer-readable storage media for receiving initial input from a user of the application, the initial input indicating that a UI element is to be generated for the user, receiving context data representative of a context of the application when the input is received, the context data at least partially including a data schema definition of data accessed by the application, prompting the user for input at least partially based on the context data, receiving additional input responsive to the prompting, defining dynamic metadata based on at least a portion of the initial input, at least a portion of the additional input, and at least a portion of the data schema definition, the dynamic metadata including one or more actions that can be executed on data accessed through the UI element, and processing the dynamic metadata to generate the UI element for display in the application.

Abstract: Methods, systems, and computer-readable storage media for receiving, by an Open Data Protocol (OData) service generation platform, an image of a sketch on a physical artifact, processing the image using a set of ML models to detect depiction of two or more entities and at least one association between entities, the set of ML models including at least one layout analysis ML model to identify two or more sections within images, at least one object detection ML model to identify one or more of entities and associations in each section of the two or more sections, and at least one text recognition ML model to determine text associated with entities in sections, generating an entity data model (EDM) based on output of the ML models that includes the two or more entities and the at least one association, and providing an OData service based on the EDM.

Abstract: Methods, systems, and computer-readable storage media for receiving, by a ML service of the ML-based engagement prediction platform, static data including static operational data and static experience data as enterprise master data (EMD) from an EMD database, providing, by the ML service, a static trained ML model by training a ML model using the static data, receiving, by the ML service, dynamic data including content data, providing, by the ML service, a dynamic trained ML model by training the static trained ML model using the dynamic data, generating, by the ML service, one or more predicted engagement scores using the dynamic trained ML model, and providing, by a digital workplace of the ML-based engagement prediction platform, a UI that includes an interactive chart that is rendered and bound with the one or more engagement scores using UI metadata that enables the interactive chart to be rendered across multiple channels.

Abstract: Methods, systems, and computer-readable storage media for receiving, by a digital workplace system, action data indicating an action of a user interacting with a digital workplace, transmitting, by the digital workplace system to a ML service, a request, the ML service processing the request at least partially based on the action to provide a predictive workflow file from a ML model, receiving, by the digital workplace system, the predictive workflow file, providing, by the digital workplace system, a workflow UI control comprising visual representations of one or more predicted actions of the predictive workflow file, and displaying the workflow UI control in the digital workplace.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, employing a distributed ledger for cloud based rapid application development. In one aspect, a method for executing actions on a distributed ledger through a cloud-based ledger service instance, the method includes receiving a metadata file from a cloud-based mobile application service, establishing a connection to an instance of a cloud-based ledger service, and for each of a plurality of actions: determining an application program interface (API) call of the cloud-based ledger service instance to execute the action on the distributed ledger, dispatching the determined API call with the respective attributes for the action; and receiving a response from the cloud-based ledger service instance based on a result of the determined API call.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for a distributed ledger based management of an enterprise application lifecycle. In one aspect, a method includes receiving a notification regarding an availability of a latest version of an application; generating a transaction proposal that includes key value pairs and a unique signature; providing the transaction proposal to a plurality of peer nodes; receiving a proposal response from at least a portion of the peer nodes, each of the proposal responses including a verification of the unique signature; generating an endorsed transaction proposal based on validating the proposal responses according to an endorsement policy; providing the endorsed transaction proposal to an application management service; receiving the latest version of the application and a block of transactions, wherein the block of transactions includes the key value pairs; and storing the block of transactions to a distributed ledger.

Abstract: Generate hybrid enterprise mobile applications in cloud environment, according to one embodiment. A web application is selected in a web integrated development environment (IDE) executing in a browser. The web application may depend on various components and the dependent build components may reside on different repositories. Dependency analysis engine determines the dependent build components corresponding to the web application. The component retrieval engine retrieves the dependent build components from corresponding repositories to memory or cache of the browser where the web IDE is executing. Component build engine builds the dependent build components to a build result. Packaging engine packages the build result to a single package as an application asset package. The application asset package is received in a platform dependent build service. The application asset package is built as a hybrid mobile application in the platform dependent build service.

Abstract: Generate hybrid enterprise mobile applications in cloud environment, according to one embodiment. A web application is selected in a web integrated development environment (IDE) executing in a browser. The web application may depend on various components and the dependent build components may reside on different repositories. Dependency analysis engine determines the dependent build components corresponding to the web application. The component retrieval engine retrieves the dependent build components from corresponding repositories to memory or cache of the browser where the web IDE is executing. Component build engine builds the dependent build components to a build result. Packaging engine packages the build result to a single package as an application asset package. The application asset package is received in a platform dependent build service. The application asset package is built as a hybrid mobile application in the platform dependent build service.