A method of implementing software architecture for common use of a Wayland protocol in a graphics module, including an application layer, an application programming interface (API) layer, a GDBus layer, a layout service layer, a Wayland protocol layer, a Weston layer, and a kernel layer, is provided. The method includes integrating the GDBus layer, relaying communication between the API layer and the layout service layer, into the Wayland protocol layer relaying communication between the layout service layer and the Weston layer and changing the layout service layer, providing a service determining and managing an application which is to be displayed on a screen, to a WindowManagerService module performing a function based on a policy of Window.

Provided herein are systems and methods for resilience testing using a DEW. A system includes at least one hardware processor coupled to a memory and configured to decode a workflow to obtain a plurality of workflow steps. Each workflow step of the plurality of workflow steps includes a runtime engine identifier and a script identifier. A script for a workflow step of the plurality of workflow steps is retrieved based on the script identifier. The script specifies a plurality of tasks. One or more containers are configured with a runtime engine based on the runtime engine identifier. The script executes against the one or more containers using the runtime engine, to perform the plurality of tasks.

Provided is a method for facilitating for facilitating monitoring of development of software products. The actions/activities executed during the stages of a product development for a software product are tracked. Further, each activity log associated with a corresponding activity is tagged to indicate an association of a corresponding activity log with one of the stages. The activities are further classified into one of a value-added activity or a non-value added activity, based on each activity log. The development of the software product is thus monitored by way of a value stream map that is generated based on the classification of each activity. The value stream map is indicative of an efficiency score for each of the stages.

Provided herein are systems and methods for processing a script file generated using a declarative engine for workloads (DEW). A system includes at least one hardware processor coupled to a memory and configured to retrieve a script file. The script file specifies a plurality of tasks forming a plan and an order of execution for the plurality of tasks. The script file is compiled to generate compiled code. The compiled code is executed to generate an in-memory representation of the plan. The in-memory representation of the plan is converted into a graph such as a directed acyclic graph (DAG). The graph includes the plurality of tasks. The plurality of tasks in the graph are executed according to the order of execution.

The type system of a functional programming language, such as DataWeave and/or the like, may be extended to add valuable semantic information to data types (e.g., attributes of data that inform a compiler/interpreter how the data should be used, etc.) that is automatically generated and/or hidden from a developer/programmer. For example, the type system may be configured for flow typing, based on a graph of type dependencies between expressions, without modifying an existing implementation, except at places where extra information can be obtained. Different parts of the type system implementation may be modified, for example, based on one or more injected retyper nodes, to provide more and better type inference.

Decentralized development and deployment of applications is described. An application may be defined as being composed of multiple code libraries, each independently developed and deployed. Packagers of individual code libraries may deploy various versions of respective code libraries in multiple code cells and may further define cell selection criteria for the libraries. An application manifest may be constructed identifying the component code libraries with optional version selection criteria for the libraries. Upon receiving a request for the application for a particular client, a refined manifest for the application may be generated for that client, the refined manifest including identifiers of particular cells for the respective component code libraries. The application may then be generated according to the refined manifest and provided to the client. Subsequent requests for the application for the same client may be serviced according to the refined manifest.

In an example embodiment, a data model infrastructure is implemented as a service rather than as an always-running server. Specifically, one of the technical issues with past implementations is that the data models are deployed onto a server that is intended to be “always running”, even if there are no requests to the server. This utilizes memory and processing power. While it may be useful to have an always running server for commonly used applications, for applications that are infrequently used (e.g., 10 times a month), it can mean that memory and processing power is wasted. Thus, by implementing the data model infrastructure as a service rather than an always-running server, the service can be launched only when actually needed, saving both memory and processing power.

A system, method, and apparatus for creating and managing smart contracts on a blockchain is provided. A method includes detecting, by the computing system, a code language of the smart contract code, wherein each of a plurality of code languages is associated with at least one of a plurality of blockchain platforms; determining, by the computing system, based at least partially on the code language of the smart contract code, an optimal blockchain platform to deploy the smart contract onto, the optimal blockchain platform being one of the plurality of blockchain platforms associated with the detected code language, the smart contract code capable of being deployed onto two or more blockchain platforms; compiling, by the computing system, the smart contract code based on the determination of the optimal blockchain platform so as to generate smart contract byte code and metadata; and deploying, by the computing system, the smart contract byte code to the optimal blockchain platform.

Systems, computer program products, and methods are described herein for continuous cognitive code logic detection and prediction using machine learning techniques. The present invention is configured to receive, from a user input device, source code scripts and target code scripts for functional code logic components of a full stack, wherein the source code scripts and the target code scripts are associated with one or more tiers; generate a training dataset based on at least the source code scripts, the target code scripts, and the functional code logic components of the full stack; train, using a machine learning algorithm, a machine learning model using the training dataset; determine a prediction accuracy associated with the machine learning model; determine that the prediction accuracy is greater than a predetermined threshold; and deploy the machine learning model on unseen source code scripts.

Aspects of the subject disclosure may include, for example, a non-transitory machine-readable medium comprising executable instructions that, when executed by a processing system including a processor, facilitate performance of operations, the operations comprising: receiving by a selected one of a plurality of containers incoming traffic from a legacy application, the legacy application having been associated with a migrated application prior to the migrated application having been installed on a Software as a Service (SaaS) cloud infrastructure, the incoming traffic comprising a first instruction to perform a first legacy operation; mapping the first legacy operation of the legacy application to a replacement instruction for the migrated application by receiving data from the selected container and assigning the replacement instruction to replace the first instruction; and communicating with the migrated application on the SaaS cloud infrastructure, the communicating comprising sending to the migrated application on the SaaS cloud infrastructure the replacement instruction. Other embodiments are disclosed.