Various example embodiments for providing device application support are presented. In at least some example embodiments, device application support may be configured to support device programmability. In at least some example embodiments, device application support may be configured to support device programmability for enabling a customer that operates a device to develop a customer application for the device and to run the customer application on the device. In at least some example embodiments, device application support may be provided in a manner for enabling a customer to develop and run a customer application for a device without a need for the customer to use a software development kit (SDK) to develop the customer application.

A smart assistant is disclosed that provides for interfaces to capture requirements for a technical assistance request and then execute actions responsive to the technical assistance request. Example embodiments relate to parsing natural language input defining a technical assistance request to determine a series of instructions responsive to the technical assistance request. The smart assistant may also automatically detect a condition and generate a technical assistance request responsive to the condition. One or more driver applications may control or command one or more computing systems to respond to the technical assistance request.

Markup language documents including server side scripting code using PHP syntax are executed efficiently in response to requests received by a server. The processing of the markup language document results in generation of a transformed markup language document that is returned in response to the request. The server side script code is input to a compiler that generates C++ code (or code in any object-based language based on C language) implementing the functionality of the server side script code. The C++ code is compiled to generated object code which is executed in order to process the markup language document. The generated C++ code includes functionality supported by PHP language including redeclaration of functions, dynamic variables, global variables, and the like. The generated C++ code invokes memory allocation code that allocates and deallocates objects obtained by instantiating the generated C++ classes.

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.

This application discloses a stream computing job processing method, a stream computing system and an electronic device, and the method includes: obtaining a stream computing job; running the stream computing job in a process-based manner, where the stream computing job includes at least one process.

Refactoring a monolithic computer application can include transforming textual input into context-aware tokens represented by machine-processable data structures, the textual input acquired from text associated with a computer application having a monolithic architecture for implementing one or more application processes. Based on co-occurrence frequencies among the context aware tokens, one or more groupings of context-aware tokens can be determined. An association between each grouping and a code construct can be determined. Invocation sequences based on time series analyses of computer-generated usage data generated in response to execution of the one or more application processes can be generated, each invocation sequence linking two or more code constructs based on a time series analysis linking groupings that correspond to the linked code constructs. A recommendation for refactoring the computer application into a plurality of microservices can be generated, each microservice corresponding to one or more invocation sequences.

A method includes: determining, by a computing device, transactions of a monolithic application; ranking, by the computing device, the transactions using predefined rules; selecting, by the computing device, a candidate transaction from the ranked list; determining, by the computing device, lines of application code of the monolithic application associated with the candidate transaction; mapping, by the computing device, respective ones of the determined lines of application code to a first operation and a second operation, wherein the first operation and the second operation are different types of operation; and defining, by the computing device, a target state design based on CQRS (Command Query Responsibility Segregation), the target state design including a first microservice that performs the first operation and a second microservice that performs the second operation.

According to one embodiment, a method that supports queries deploying operators based on multiple programming languages is described. A sequence of operators associated with a query is identified, where the sequence of operators includes at least two neighboring operators including a first operator based on a first programming language and a second operator based on a second programming language that is different from the first programming language. Thereafter, a schema associated with the first operator and a schema associated with the second operator is determined along with the compatibility between the schema of the first operator and the schema of the second operator. A query error message is generated in response to incompatibility between the first operator schema and the second operator schema. Compatibility is determined when an output generated by execution of the first operator provides machine data needed as input for execution of the second operator.

To improve the technological process of programming a computer using a dynamic programming language, generate a first portion of training data which maps types in the dynamic programming language to corresponding functions and methods by performing information retrieval on documentation libraries in the dynamic programming language and/or generate a second portion of training data which maps program variables to the corresponding functions and methods by performing data flow analysis on a plurality of pre-existing programs written in the dynamic programming language. Train a neural network on the first and/or second portions of training data to infer unknown types in the dynamic programming language. Carry out inference with the trained neural network to infer the unknown types. Facilitate programming in the dynamic programming language based on the inferred unknown types. Optionally, execute a resulting program.

The present disclosure relates to a computer language and code for software application development, data compression, and use with conventional, optical, hybrid electro-optical and quantum computers.