Embodiments of the disclosed technology concern transforming a high-level quantum-computer program to one or more symbolic expressions. Because the transformations lead to symbolic expressions in the compiled code, one can extract these to arrive at symbolic resource estimates for the quantum program. In cases where these transformations do not yield closed-form solutions, they can still be evaluated many orders of magnitude faster than it was possible using other resource estimation tools. Having access to such symbolic or near-symbolic expressions not only greatly improves the performance of accuracy management and resource estimation, but also better informs quantum software developers of the bottlenecks that may be present in the quantum program. In turn, the underlying quantum-computer program can be improved as appropriate.

Apparatuses, systems, and techniques to receive, by a processor of a computer system, one or more operations for a kernel; automatically generate, by the processor, one or more operators that perform the one or more operations on elements of one or more input data structures; and automatically generate, by the processor, the kernel that comprises the one or more operators.

A method, apparatus, electronic device, storage medium and program product of code management are provided. In response to a request for building an executable file, corresponding developed code is obtained from a code library. The developed code is compiled into intermediate code to determine security of the intermediate code. In response to determining that the intermediate code is secure, an executable file is generated based on the intermediate code.

Techniques for generating a dataflow graph include generating a first dataflow graph with a plurality of first nodes representing first computer operations in processing data, with at least one of the first computer operations being a declarative operation that specifies one or more characteristics of one or more results of processing of data, and transforming the first dataflow graph into a second dataflow graph for processing data in accordance with the first computer operations, the second dataflow graph including a plurality of second nodes representing second computer operations, with at least one of the second nodes representing one or more imperative operations that implement the logic specified by the declarative operation, where the one or more imperative operations are unrepresented by the first nodes in the first dataflow graph.

A processing device used in a bus, for executing a programming language function of a central processing unit (CPU), comprises a receiving circuit, for receiving a joint command from the CPU, to assist the CPU to execute the programming language function, wherein the joint command comprises an extended read command and an extended write command; a transmitting circuit, coupled to the receiving circuit, for transmitting the extended read command to a slave device, to receive a first response message via the receiving circuit in response to the extended read command from the slave device, wherein the first response message comprises at least one data read by the slave device from a memory block; and a writing circuit, coupled to the receiving circuit and transmitting circuit, for writing the at least one data into a destination address corresponding to the programming language function according to the extended write command.

Techniques for implementing a dynamic API bot for robotic process automation are disclosed. In some embodiments, a computer system performs operations comprising: providing a data file having a predefined template comprising dedicated fields for an identification of an API, a type of call method, metadata identifying one or more objects, and data of the object(s); providing a low-code no-code (LCNC) development platform configured to enable a user to develop a bot by dragging and dropping application components of the bot; receiving, via the LCNC development platform, a configuration of the bot comprising a configuration of the application components of the bot and an identification of the data file; and running the bot, the bot being configured to generate a request using the data file, converting the data of the object(s) into a payload in a format required by the API based on the data file.

Provided is a specification document creation system including a first computer and a second computer, wherein the first computer is configured to generate, based on configuration information, display data for displaying a first display item, which is determined by the configuration information, of a BIOS on a display device, the configuration information indicating a hardware configuration of the first computer, and analyze the display data to generate first information including the first display item included in the display data, and the second computer is configured to analyze a source code of the BIOS to generate second information including a second display item, which is determined independently of the hardware configuration of the first computer, of the BIOS, and create a specification document for the BIOS in which the first display item included in the first information and the second display item included in the second information are described.

Disclosed herein are system, method, and device embodiments for implementing a customizable animation experience. A multi-tenant service may associate an animation element with a visual component of an application, and generate a markup component including an animation parameter configured to customize the animation element within the application code. Further, the multi-tenant service may receive a request for the animation from an animation manager based on execution of the application code, and send the animation information to the animation manager. In some embodiments, the animation manager is configured to set the animation parameter to the animation information and present an animation associated with the animation element based on the animation parameter.

Techniques for implementing a dynamic API bot for robotic process automation are disclosed. In some embodiments, a computer system performs operations comprising: providing a data file having a predefined template comprising dedicated fields for an identification of an API, a type of call method, metadata identifying one or more objects, and data of the object(s); providing a low-code no-code (LCNC) development platform configured to enable a user to develop a bot by dragging and dropping application components of the bot; receiving, via the LCNC development platform, a configuration of the bot comprising a configuration of the application components of the bot and an identification of the data file; and running the bot, the bot being configured to generate a request using the data file, converting the data of the object(s) into a payload in a format required by the API based on the data file.

Systems, apparatuses, methods, and computer program products are disclosed for automatically deriving data transformation criteria. An example method includes receiving, by communications circuitry, a source dataset and a target dataset and identifying, by a model generator, a target variable. The example method further includes training, by the model generator, a decision tree for the target variable using the source dataset and the target dataset such that the trained decision tree can predict a value for the target variable from new source data. The example method further includes deriving, by a derivation engine, a set of parameters and pseudocode for producing the target variable from the source dataset.