Adaptive data collections may include various type of data arrays, sets, bags, maps, and other data structures. A simple interface for each adaptive collection may provide access via a unified API to adaptive implementations of the collection. A single adaptive data collection may include multiple, different adaptive implementations. A system configured to implement adaptive data collections may include the ability to adaptively select between various implementations, either manually or automatically, and to map a given workload to differing hardware configurations. Additionally, hardware resource needs of different configurations may be predicted from a small number of workload measurements. Adaptive data collections may provide language interoperability, such as by leveraging runtime compilation to build adaptive data collections and to compile and optimize implementation code and user code together. Adaptive data collections may also provide language-independent such that implementation code may be written once and subsequently used from multiple programming languages.

Implementations of the present disclosure include receiving, by a parser, a view source file and an extension source file, the view source file defining a view on data stored in a database, the extension source file defining an extension to the view, parsing, by the parser, the view source file to provide a view abstract syntax tree (AST) and the extension source file to provide an extension AST, providing, by the parser, a merged AST based on the view AST and the extension AST, generating a mixed runtime data object using the merged AST, and providing the mixed runtime data object for consumption by at least one runtime component.

A type restriction contextually modifies an existing type descriptor. The type restriction is imposed on a data structure to restrict the values that are assumable by the data structure. The type restriction does not cancel or otherwise override the effect of the existing type descriptor on the data structure. Rather the type restriction may declare that a value of the data structure's type is forbidden for the data structure. Additionally or alternatively, the type restriction may declare that an element count allowable for a data structure's type is forbidden for the data structure. Type restriction allows optionality (where only a singleton value for a data structure is allowed), empty sets (where no value for a data structure is allowed), and multiplicity (where only a limited element count for a data structure) to be injected into a code set independent of data type. Type restriction allows certain optimizations to be performed.

A method of generating a user interface for presentation to a user. The method comprises executing a first application computer program to provide a user interface, executing agent computer program code to interrogate and modify said user interface during execution of said first application computer program, and presenting said modified user interface. The first application computer program may be run on a server, while the modified user interface may be presented to a user at a client connected to said server.

Methods, systems, and apparatus for executing a smart contract by a blockchain node of a blockchain. An example method includes receiving bytecode of a smart contract; deploying the smart contract, comprising storing the bytecode of the smart contract on the blockchain; compiling, through Just-In-Time (JIT) compilation, the bytecode of the smart contract into machine code; locally storing the machine code in a memory of the blockchain node; and executing the smart contract deployed on the blockchain, comprising determining whether the machine code corresponding to the bytecode of the smart contract is locally stored in the memory of the blockchain node, and interpreting and executing the bytecode of the smart contract if the machine code corresponding to the bytecode of the smart contract is not locally stored.

This application provides a program code execution behavior monitoring method. A computer device executes, in a virtual execution environment, first code corresponding to first program code, where the first code belongs to external code, the external code is code, other than internal code, invoked in the first program code, the external code includes system code provided by an operating system of the computer device, and the internal code is code of a process generated by the first program code. In a process of executing the first code, if second code belongs to the internal code, before execution of the second code is completed, the computer device switches an execution environment of the first program code to a simulated execution environment, where the second code is to-be-executed code. The computer device executes the second code in the simulated execution environment.

A method of generating a user interface for presentation to a user. The method comprises executing a first application computer program to provide a user interface, executing agent computer program code to interrogate and modify said user interface during execution of said first application computer program, and presenting said modified user interface. The first application computer program may be run on a server, while the modified user interface may be presented to a user at a client connected to said server.

Embodiments of the present disclosure provide a method and apparatus for generating a chip-based computing function, a device, and a storage medium. The method includes: acquiring an input parameter value associated with a computing function supported by a chip; determining, based on the input parameter value, at least one candidate computing function template corresponding to the computing function, the candidate computing function template having a configurable parameter associated with performance of the candidate computing function template, and the configurable parameter having at least one candidate value; and determining, according to the input parameter value and candidate values of the configurable parameter of the candidate computing function template, a target computing function template and a target value of a configurable parameter of the target computing function template.

Disclosed herein are methods, systems, and processes to perform self-dependent upgrades of Java Runtime Environments (JREs). A request to update a plugin to a new version with a new configuration that includes a location to download a new upgrader-executable is received from a platform computing device at an endpoint computing device. The plugin is uploaded to the new version. The new upgrader-executable that includes an executable with an executable table executed by the plugin is downloaded from the location. The executable is used to halt execution of a JRE application (e.g., a Collector) and download JRE files required for the upgrade. The JRE application (e.g., the Collector) is then re-started with the new configuration, which can be rolled back if the upgrade is unsuccessful.

Methods, systems, and apparatus, including instructions encoded on storage media, for performing reduction of gradient vectors and similarly structured data that are generated in parallel, for example, on nodes organized in a mesh or torus topology defined by connections in at least two dimension between the nodes. The methods provide parallel computation and communication between nodes in the topology.