A computer-implemented method for managing a release of a software product includes obtaining a request for the release, the request including workflow action parameter data to define a release pipeline involving a plurality of software engineering systems configured to process data indicative of the software product, and executing, with a processor, a workflow to implement the release pipeline in accordance with the workflow action parameter data. Executing the workflow includes sending a series of instructions to the plurality of software engineering systems. A successive instruction in the series of instructions is sent based on whether a gating rule for the release is met.

The embodiments of the present disclosure provide a method, an apparatus, a device and a medium for processing topological relation of tasks. The method includes: extracting at least one execution element from each of processing tasks based on a topological relation recognition rule; determining a dependency relation among the processing tasks according to content of the execution element of each processing task; and determining a topological relation among the processing tasks according to the dependency relation among the processing tasks.

This disclosure relates to blockchain smart contract-based data processing. In one aspect, a method includes obtaining, by a node in a blockchain network in which a service smart contract is deployed, a service initiation transaction. The service initiation transaction is broadcast to other nodes. While executing the service initiation transaction, the service smart contract is invoked using a blockchain virtual machine that includes a first instruction set comprising a data exchange instruction and processing logic corresponding to the data exchange instruction. The node triggers execution of the processing logic based on the data exchange instruction in the service smart contract using the blockchain virtual machine, thereby performing a data exchange processing operation on data to be processed. A second instruction set of a smart contract compiler includes the data exchange instruction. The service smart contract is compiled using the smart contract compiler and includes the data exchange instruction.

Provided are an apparatus and a method for providing screen setting data of a plurality of devices. The apparatus includes at least: a communication unit that transmits and receives data; a storage unit that stores the data; and a controller operatively connected to the communication unit and the storage unit. The controller receives screen configuration data determined by a manufacturer in association with a specific device selected by the manufacturer of a first user device from the first user device, stores screen setting data based on the received screen configuration data and screen characteristic data for a predetermined standard screen of the specific device in the storage unit, receives a screen setting request for the specific device from a second user device, and transmits screen setting data stored so as to correspond to the specific device in accordance with the screen setting request to the specific device.

An apparatus comprises processing circuitry to issue load operations to load data from memory. In response to a plural-register-load instruction specifying at least two destination registers to be loaded with data from respective target addresses, the processing circuitry permits issuing of separate load operations corresponding to the plural-register-load instruction. Load tracking circuitry maintains tracking information for one or more issued load operations. When the plural-register-load instruction is subject to an atomicity requirement and the plurality of load operations are issued separately, the load tracking circuitry detects, based on the tracking information, whether a loss-of-atomicity condition has occurred for the load operations corresponding to the plural-register-load instruction, and requests re-processing of the plural-register-load instruction when the loss-of-atomicity condition is detected.

A system and method receive a plurality of crypto profiles that include customizable rules for different cryptocurrencies and operating state information that initialize containerized lending applications. The system and method ink the crypto profiles to a matching engine before the containerized lending applications and the matching engine match a plurality of borrower requests for a debt or an equity denominated in a cryptocurrency to lending requests. The system and method collect cryptocurrency payments in response to the use of the debt or the equity by the borrower. Each containerized lending application include executable software, runtime code, system tools, and system libraries that enable the containerized applications to run on two or more computing environments without modification.

A generation device extracts elements from tree-structured data in which each element includes the content of an operation of an object device and an execution condition of the operation, in order from top to bottom. The generation device determines whether the operation is executed by referring to the state of the object device and determining whether the execution condition is satisfied, for an element including the execution condition, of the extracted elements. The generation device adds, to a list, information about the operation determined to be executed.

In some embodiments, a service platform that facilitates artificial intelligence model and data collection and collection may be provided. Input/output information derived from machine learning models may be obtained via the service platform. The input/output information may indicate (i) first items provided as input to at least one model of the machine learning models, (ii) first prediction outputs derived from the at least one model's processing of the first items, (iii) second items provided as input to at least another model of the machine learning models, (iv) second prediction outputs derived from the at least one other model's processing of the second items, and (v) other inputs and outputs. The input/output information may be provided via the service platform to update a first machine learning model. The first machine learning model may be updated based on the input/output information being provided as input to the first machine learning model.

In some embodiments, a service platform that facilitates artificial intelligence model and data collection and collection may be provided. Input/output information derived from machine learning models may be obtained via the service platform. The input/output information may indicate (i) first items provided as input to at least one model of the machine learning models, (ii) first prediction outputs derived from the at least one model's processing of the first items, (iii) second items provided as input to at least another model of the machine learning models, (iv) second prediction outputs derived from the at least one other model's processing of the second items, and (v) other inputs and outputs. The input/output information may be provided via the service platform to update a first machine learning model. The first machine learning model may be updated based on the input/output information being provided as input to the first machine learning model.

Systems and methods for altering tablature via geographical interfaces are disclosed. A system may include at least one processor configured to output a first signal for rendering a table, including a plurality of items, columns, and values in cells, wherein one of the columns may retain geographic location values, wherein a subgroup of the items may share a common geographic location value. The processor may output a second signal to render a common map, including markers associated with the geographically dispersed items, enable an interaction with the common map, output a third signal to render column values associated with the plurality of items of the subgroup, receive a fourth signal to update a column value for a particular item, receive a fifth signal to re-render the table, and output a sixth signal to re-render the table, wherein the sixth signal includes the updated value for the particular item.