Abstract: A method and system for generating and optimizing test cases for an engineering program based on a constraint satisfaction problem is provided. In one embodiment, the method includes generating a plurality of tripartite graphs for the engineering program. Each of the generated plurality of tripartite graphs include a constraint satisfaction problem associated with a specific code statement of the plurality of code statements. Furthermore, the method includes generating a plurality of test cases for the engineering program based on the plurality of tripartite graphs such that the generated plurality of test cases are limited by the generated test case constraints. Moreover, the method includes optimizing the generated plurality of test cases based on an analysis of the engineering program.

Abstract: A system and method for data management is provided. The method includes obtaining a dataset from a data source by a processing unit. The dataset includes a plurality of datapoints, and each of the datapoints belongs to a column among a plurality of columns. Further, an ontology label for at least one column in the dataset is predicted using a machine learning model. The predicted ontology label is associated with an ontology comprising a plurality of ontology labels. Further, a mapping between the dataset and the ontology is generated based on the relation between the predicted ontology label and the column. Furthermore, the datapoints are classified with respect to the ontology labels based on the mapping generated. The classified datasets are outputted on a user interface.

Abstract: A method and system for generating and optimizing an engineering program with a given specification from another engineering program is provided. The method includes receiving, by a processing unit, a request to generate a first engineering program, with a first specification, from a second engineering program, with a second specification. The method further includes generating, by the processing unit, a first ontology schema comprising information associated with a plurality of data flow and control flow interrelationships between a plurality of code statements in the second engineering program. The further includes generating, by the processing unit, a second ontology schema based on an application of a machine learning algorithm on the first sequential representation of the first ontology schema. The method includes generating, by the processing unit, the first engineering program from the second engineering program, based on an analysis of the second ontology schema.

Abstract: A system, apparatus and method for determining operational configuration of asset are provided. The method includes receiving a set of operating parameters associated with the asset, identifying data associated with the asset based on the received set of operating parameters, configuring a second digital twin of the asset based on the data identified from first knowledge database, simulating a behavior of the asset based on the configured second digital twin in a simulation environment, and determining an operational configuration associated with the variant of the asset based on results of the simulation.