A method and system for generating engineering diagrams in an engineering system includes receiving specification of one or more physical components. Further, the method includes obtaining, from a data source, a first engineering diagram representing a portion of a technical installation. The method further includes identifying a deviation in the one or more physical components, physical connections and the parameter values in the first engineering diagram based on the specification of the one or more physical components. Furthermore, the method includes generating an engineering diagram analytics model for the first engineering diagram based on the identified deviation in the one or more physical components, the physical connections and the parameter values in the first engineering diagram. Also, the method includes generating a second engineering diagram representing the upgraded portion of the technical installation based on the generated engineering diagram analytics model.

A system and method for automatically generating scenario patterns are disclosed. The system includes a processor; and a memory operatively connected to the processor via a communication interface. The processor receives a request to create new features in connection with development and/or testing of one or more applications; automatically generates scenario patterns corresponding to the new features by utilizing an automatic scenario patterns generating tool; outputs the scenario patterns in a predefined file format providing an end-2-end (E2E) view spanning multiple applications, state models and events; uploads the scenario patterns in the predefined file format onto a system different from the automatic scenario patterns generating tool; deploys corresponding application programming interface (API) on a private cloud to request the scenario patterns in the predefined file format from the system; and implements the requested scenario patterns to create the new features.

A system and method for automatically generating scenario patterns are disclosed. The system includes a processor; and a memory operatively connected to the processor via a communication interface. The processor receives a request to create new features in connection with development and/or testing of one or more applications; automatically generates scenario patterns corresponding to the new features by utilizing an automatic scenario patterns generating tool; outputs the scenario patterns in a predefined file format providing an end-2-end (E2E) view spanning multiple applications, state models and events; uploads the scenario patterns in the predefined file format onto a system different from the automatic scenario patterns generating tool; deploys corresponding application programming interface (API) on a private cloud to request the scenario patterns in the predefined file format from the system; and implements the requested scenario patterns to create the new features.

A solution to the problems caused by manual computer programming is provided. A Pseudo-code Design Platform (PDP) reduces the amount of technical skill, length of time, and cost required to create and maintain computer applications. The Pseudo-code Compiler performs as a true Integrated Design Environment. All of the software development steps are performed automatically 100% of the time, within the Pseudo-code Design Platform, just in the opposite order of the conventional process.

A solution to the problems caused by manual computer programming is provided. A Pseudo-code Design Platform (PDP) reduces the amount of technical skill, length of time, and cost required to create and maintain computer applications. The Pseudo-code Compiler performs as a true Integrated Design Environment. All of the software development steps are performed automatically 100% of the time, within the Pseudo-code Design Platform, just in the opposite order of the conventional process.

A computer-implemented method for merging architecture data that are exchanged between an architecture definition tool and a behavior modeling tool includes: opening a first file with first architecture data and a second file with second architecture data in a comparison tool; comparing the first architecture data with the second architecture data to obtain a first list of differences; retrieving at least one combination rule, wherein the at least one combination rule comprises an identification rule for identifying a difference and a change to be applied to the identified difference; ascertaining a second list of differences that fulfill the identification rule and removing the differences of the second list from the first list; and applying the change defined in the at least one combination rule to each difference in the second list.

Methods and systems are described herein for integrating model development control systems and model validation platforms. For example, the methods and systems discussed herein recite the creation and use of a model validation platform. This platform operates outside of the environment of the independently validated models as well as the native platform into which the independently validated models may be incorporated. The model validation platform may itself include a model that systematically validates other independently validated models. The model validation platform may then provide users substantive analysis of a model and its performance through one or more user interface tools such as side-by-side comparisons, recommended adjustments, and/or a plurality of adjustable model attributes for use in validating an inputted model.

Methods and systems are described herein for integrating model development control systems and model validation platforms. For example, the methods and systems discussed herein recite the creation and use of a model validation platform. This platform operates outside of the environment of the independently validated models as well as the native platform into which the independently validated models may be incorporated. The model validation platform may itself include a model that systematically validates other independently validated models. The model validation platform may then provide users substantive analysis of a model and its performance through one or more user interface tools such as side-by-side comparisons, recommended adjustments, and/or a plurality of adjustable model attributes for use in validating an inputted model.

The present disclosure discloses a model-based architecture design method for an unmanned aerial vehicle (UAV) system, which aims to deal with challenges of changeable operational requirements, shortened design period, and decreased technical risks in a current UAS design process. A data-driven architecture development method is used. By establishing an architecture development framework of the UAS, a framework modeling process oriented to different viewpoints is designed, and modeling and simulation specifications based on SysML and Modelica are defined, such that design of the UAS starts from conception and confirmation of an operational concept. The method focuses on forward analysis and design of a system framework, and concept verification and metric closed-loop are carried out at an early stage of the design of the UAS by virtue of logic modeling and system simulation.

Methods, apparatus, systems, and articles of manufacture are disclosed to facilitate content generation for cloud computing platforms. An example apparatus includes model definition circuitry to generate model definitions representative of one or more undefined target system objects in a target system, and generate instructions that cause a developer environment to provide the model definitions during a generation of content files, generation order circuitry to generate a processing order of the content files, the content files having one or more defined model objects, and object processing circuitry to convert the one or more defined model objects to defined target system objects for deployment and execution at the target system.