Systems and methods for code generation are described. The method may include accessing an application programming interface (API) specification written in a first computer programming language. The method may also include processing the API specification in the first computer programming language with a code generation tool. Furthermore, the method may include generating, from the API specification, code in each of a plurality of different computer programming languages different from the first computer programming language and different from each other.

Systems and methods include reception of a first request to check code associated with a first service for compliance with one or more criteria, determination of a plurality of code components associated with the first service, execution of a code check of each of the plurality of code components, generation of a first service compliance statement associated with the first service based on results of the executed code checks, determination of a definition of the first product from a product repository, the definition listing a plurality of services on which the product depends, the plurality of services including the first service, identification of a compliance statement associated with each of the plurality services, and determination of a product compliance statement based on each of the identified compliance statements.

Systems and methods include reception of a first request to check code associated with a first service for compliance with one or more criteria, determination of a plurality of code components associated with the first service, execution of a code check of each of the plurality of code components, generation of a first service compliance statement associated with the first service based on results of the executed code checks, determination of a definition of the first product from a product repository, the definition listing a plurality of services on which the product depends, the plurality of services including the first service, identification of a compliance statement associated with each of the plurality services, and determination of a product compliance statement based on each of the identified compliance statements.

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.

A system is disclosed for automatic retrieval and analysis of PLC code including at least one code disassembler configured to receive, via one or more passive or active scanners connected to an automation network, compiled code configured for execution on one or more devices of the automation network, the at least one code disassembler automatically disassembling the compiled code into program code. The system including an analyzing component configured to receive the program code from the code disassembler and to automatically analyze the program code for errors. The system including an alerting component configured to receive one or more detected errors from the analyzing component and to communicate or store the one or more detected errors.

A system is disclosed for automatic retrieval and analysis of PLC code including at least one code disassembler configured to receive, via one or more passive or active scanners connected to an automation network, compiled code configured for execution on one or more devices of the automation network, the at least one code disassembler automatically disassembling the compiled code into program code. The system including an analyzing component configured to receive the program code from the code disassembler and to automatically analyze the program code for errors. The system including an alerting component configured to receive one or more detected errors from the analyzing component and to communicate or store the one or more detected errors.

Aspects of the present disclosure provide systems, methods, and computer-readable storage media that support automatic compliance validation using a dynamically generated set of validation code. The compliance validation process may begin by extracting requirements from a compliance specification. Once extracted, the requirements may be tokenized and vectorized to produce vectorized data. The vectorized data may be labeled using a multi-label classifier to produce a set of labeled data (e.g., labeled vectors representing the requirements extracted from the compliance specification). The set of labeled data may be fed to a machine learning model configured to map the labeled data to pieces of code stored in one or more code libraries. A set of validation code is generated based on the pieces of code mapped to the labeled data and the set of validation code may be applied to a deliverable to evaluate compliance of the deliverable with the requirements.

Aspects of the present disclosure provide systems, methods, and computer-readable storage media that support automatic compliance validation using a dynamically generated set of validation code. The compliance validation process may begin by extracting requirements from a compliance specification. Once extracted, the requirements may be tokenized and vectorized to produce vectorized data. The vectorized data may be labeled using a multi-label classifier to produce a set of labeled data (e.g., labeled vectors representing the requirements extracted from the compliance specification). The set of labeled data may be fed to a machine learning model configured to map the labeled data to pieces of code stored in one or more code libraries. A set of validation code is generated based on the pieces of code mapped to the labeled data and the set of validation code may be applied to a deliverable to evaluate compliance of the deliverable with the requirements.

An automated parameterized modeling and scoring intelligence system includes a parameterized score estimation software tool and a parameterized score optimization software tool. The parameterized score estimation software tool processes design metrics associated with a current project according to historical project data selected based on a similarity with at least some of the design metrics to determine a score estimation for the current project. The parameterized score optimization software tool processes the score estimation based on external application data retrieved from an external application to determine an expected yield for the current project. A user of the system may iterate against the score estimation or the expected yield by changing one or more of the parameters used to determine same. The iteration may result in a score estimation or expected yield different from the initial versions thereof, such as to identify an optimal design for the current project.

A business flow creation support device 1 includes a generation unit 11 that receives an effect and a sentence indicating what is desired to be realized, which are input by a user, and generates a flow including a plurality of clauses obtained by morphologically analyzing the sentence, a presentation unit 12 that acquires scores indicating to which fields the effect and words included in the clauses are close, respectively, and presents, to the user, a template of a business flow in a field having a high total score, and a creation support unit 14 that support creation of the business flow corresponding to the effect and the sentence.