Patent classifications
G06F8/24
Aggregation of connected objects
A method and device for aggregating connected objects of a communications network. The connected objects have at least one basic feature. The method includes the following steps implemented on an aggregation device, in order to obtain a group avatar suitable for representing the connected objects: obtaining at least one basic feature; obtaining at least one feature of the group object, linked to a basic feature; and creating the group avatar including: a structure having a basic feature; a structure having a group feature; a structure for linking the group feature to at least one basic feature; and a group proxy structure having an association between an address of the group avatar and an address of the connected objects.
System and Method for Fast Application Initialization with Deferred Injection
A method, computer program product, and computing system for defining, a plurality of dependency groups for one or more objects of an application, wherein at least two dependency groups of the plurality of dependency groups include one or more common objects. One or more injectors associated with the one or more common objects may be identified. A first dependency group with at least one common object of the one or more common objects may be processed. For each common object of the first dependency group, a reference to an injector associated with the respective common object from a different dependency group may be generated for deferred processing of the respective common object.
Methods and systems for programmatic creation of an interactive demonstration presentation for an envisioned software product
A demonstration serving system and associated methods are provided for creating an interactive demonstration presentation for an envisioned software product. The interactive demonstration presentation for the envisioned software product is a digital artifact that is presented during a presentation to present and demonstrate features of the envisioned software product and how the envisioned software product is to function and operate in response to user interaction with a graphical user interface (GUI) such that the interactive demonstration presentation mimics features, look, and feel of the envisioned software product once it is fully developed without creating custom-made Hypertext Markup Language (HTML), JavaScript and Cascading Style Sheets (CSS) of a real software product.
Distributed and redundant machine learning quality management
Provided is a process including: writing modelling-object classes using object-oriented modelling of the modelling methods, the modelling-object classes being members of a set of class libraries; writing quality-management classes using object-oriented modelling of quality management, the quality-management classes being members of the set of class libraries; scanning modelling-object classes in the set of class libraries to determine modelling-object class definition information; scanning quality-management classes in the set of class libraries to determine quality-management class definition information; using the modelling-object class definition information and the quality-management class definition information to produce object manipulation functions that allow a quality management system to access methods and attributes of modelling-object classes to manipulate objects of the modelling-object classes; and using the modelling-object class definition information and the quality-management class definition information to produce access to the object manipulation functions.
Generation of application based on declarative specification
An application development environment generates applications from declarative specification for the application. The declarative specification describes one or more object types and references to objects of each object type. The application development environment generates instructions (or code) from the declarative specification to generate an initial version of the application. The application development environment iteratively builds the application based on user interactions that modify the declarative specification. The application development environment modifies the instructions for the application to match the modified declarative specification. The final version of the application may be deployed on a production system.
MACHINE LEARNING PIPELINE OPTIMIZATION
Provided is a process of modeling methods organized in racks of a machine learning pipeline to facilitate optimization of performance using modelling methods for implementation of machine learning design in an object-oriented modeling (OOM) framework, the process including: writing classes using object-oriented modelling of optimization methods, modelling methods, and modelling racks; writing parameters and hyper-parameters of the modeling methods as attributes as the modeling methods; scanning modelling racks classes to determine first class definition information; selecting a collection of rack and selecting modeling method objects; scanning modelling method classes to determine second class definition information; assigning racks and locations within the racks to modeling method objects; and invoking the class definition information to produce object manipulation functions that allow access the methods and attributes of at least some of the modeling method objects, the manipulation functions being configured to effectuate writing locations within racks and attributes of racks.
GENERIC FACTORY CLASS
Systems and methods provide a generic factory class to determine one or more classes implementing an interface and/or derived from a base class in response to a call from an application factory class by retrieving a list of the one or more classes implementing the interface or derived from the based class, determining properties of each of the one or more classes, and return, based on the properties, a name of each of one or more of the one or more classes.
Dynamic validation framework extension
A programming language framework may be enhanced to provide for dynamic validation. Dynamic validation allows the validator function for any variable to be selected at runtime rather than statically declared at programming-time. Instead of annotating a variable with an annotation that refers to a specific validator function or constraint type, programmers can annotate a variable with an annotation that indicates that the validator function will be selected dynamically at runtime. When a runtime instance of the variable is created, the programming language framework may identify the dynamic validation annotation on the variable, and then use the runtime values in the variable to determine which validator function(s) should be used.
SIMPLIFYING CREATION AND PUBLISHING OF SCHEMAS WHILE BUILDING APPLICATIONS
A system includes a memory and a processor, where the processor is in communication with the memory. The processor is configured to receive a request to build an application, where the application is associated with source code. The source code is analyzed to detect whether a first interface is implemented within the application. The source code is parsed to determine an invocation of the first interface. Inputs and outputs (I/Os) from the first interface are determined based on the invocation of the first interface. A model is generated based on the I/Os associated with the first interface, where the model includes a structure of each of the I/Os. The model is published to a registry.
Interrupt-Driven System Verification Method Based on Interrupt Sequence Diagram
An interrupt-driven system verification method based on interrupt sequence diagrams includes the steps of: establishing an interrupt-driven system model based on an interrupt sequence diagram, dividing interaction fragments in the obtained interrupt sequence diagram into basic interaction fragments and composite interaction fragments and sequentially converting the basic interaction fragments and the composite interaction fragments into the corresponding automaton models, combining the automaton models into one automaton model, adding the constraints in the interrupt sequence diagram to the converted automaton model, adding the verification attribute information as a constraint to the converted automaton model, describing an automaton as an input format acceptable to the automaton verification tool, and verifying the model with the automaton verification tool.