63 results about "Code editor" patented technology

An integrated development environment (IDE) leverages a generative AI model to generate industrial control code in accordance with specified functional requirements, which can be provided to the industrial IDE system as intuitive natural language spoken or written text. The industrial IDE can also analyze written code in response to natural language prompts submitted against the code, generate answers to user-submitted questions about the code, and offer recommendations for improving the code in response to specific questions or requests submitted by the user.

Aspects of the disclosed technology include computer-implemented systems and methods for integrating machine-learned generative models with code editing tools. A code editor is configured to execute computer-executable code within code cells of a code editor interface including a first interface portion and a second interface portion. The interface portion is configured to receive user input for defining and editing a set of code cells within the first interface portion. Each code cell of the set of code cells is independently executable by the code editor application. The second interface portion is configured to receive user input for defining and submitting user queries to a machine-learned generative model. The code editor is configured to modify at least one code cell of the set of cells based at least in part on an output of the machine-learned generative model in response to a user query.

The invention discloses an intelligent completion code optimization method based on texture pre-rendering and multi-level cache, which comprises the following steps of: pre-establishing a grammar rule set and a GPU cache characteristic database, storing a grammar style sheet when a code editor is started, generating a font image set and loading current GPU cache parameters; after a candidate code segment list pops up through intelligent completion, dividing candidate code segments into data blocks, analyzing syntax types, determining character styles, and generating candidate code segment textures through instantiation rendering and a fragment shader; according to the current GPU cache parameter, the selected priority of the candidate code segment and the compressed volume, the texture is distributed to a first-level buffer, a second-level buffer or a global video memory according to a rule, and metadata is recorded and added into a global texture cache table; and after the user selects the candidate code segment, reading texture data from the corresponding GPU buffer, calculating a display coordinate by combining a cursor row and column index, an editor basic style parameter and a DPI scaling, completing texture rendering and drawing, and realizing optimized display of the intelligent completion code.

Systems and methods for a threat-hunting development environment are disclosed herein. The systems and methods can include: executing a networked, assisted, threat-hunting environment that, via a dedicated user interface, is configured to establish data transfer pipelines between the threat-hunting environment and the at least one tenant network, the data transfer pipelines maintaining a connection between the threat-hunting environment and the at least one tenant network during an active session, via the at least one SIEM server, to allow continuous data communication; query the at least one tenant network with a query developed via an integrated code editor; receive the query result data from the at least one tenant network: analyze, the result data for a detected threat in the at least one tenant network; and based on the analyzed result data, push a subsequent query to the at least one tenant network to respond to detected threat.

A computer system provides a context for a source code document to an artificial intelligence (AI) model and obtains a first suggested edit at a first source code location. At a code editor user interface (UI), the computer system presents a first chat indicator at the first source code location. Based on user interaction with the first chat indicator, the computer system presents the first suggested edit and receives a user response. The computer system provides an updated context to the AI model. The updated context comprises the context and the user response. The computer system obtains a second suggested edit at a second source code location. At the code editor UI, the computer system presents a second chat indicator at the second source code location. Based on user interaction with the second chat indicator, the computer system presents the second suggested edit.

Techniques for visual software development are disclosed, including: (a) generating, by a visual code editor, (1) a data model of a plurality of code elements in a set of source code and (2) a kernel for execution of the set of source code; (b) based on a subset of the set of source code, the data model, and the kernel, generating an adjustable graphical user interface (GUI) form control; (c) presenting the adjustable GUI form control in alignment with the set of source code in a GUI of the visual code editor; and (d) responsive to user input in the GUI to adjust the adjustable GUI form control: (1) modifying the subset of source code and the data model according to the user input; (2) updating the presentation of the set of source code in the GUI to reflect the modified subset of source code; and (3) executing the modified set of source code, thereby updating variable values within the kernel.

An integrated development environment (IDE) leverages a generative AI model to generate industrial control code in accordance with specified functional requirements, which can be provided to the industrial IDE system as intuitive natural language spoken or written text. The industrial IDE can also analyze written code in response to natural language prompts submitted against the code, generate answers to user-submitted questions about the code, and offer recommendations for improving the code in response to specific questions or requests submitted by the user.

An integrated development environment (IDE) leverages a generative AI model to generate industrial control code in accordance with specified functional requirements, which can be provided to the industrial IDE system as intuitive natural language spoken or written text. The industrial IDE can also analyze written code in response to natural language prompts submitted against the code, generate answers to user-submitted questions about the code, and offer recommendations for improving the code in response to specific questions or requests submitted by the user.

The invention is suitable for the technical field of computers, and provides an integrated code generation method which comprises the steps that on a low-code platform, a seed code is generated based on a data model, and the seed code comprises service metadata capable of being recognized by a development environment; analyzing a data model and a business rule on which the seed code is based, and constructing a multi-dimensional meta-knowledge graph; in a code editor, analyzing the business metadata to generate a business context; deducing a service constraint condition from the service context, and converting the service constraint condition into a code generation constraint; on the basis of the code generation constraints, code snippets are generated through an AI programming assistant in combination with the seed codes, and therefore semantic matching is carried out on data relations, service rules and the like in services and constraint conditions needed by code generation through integration of low-platform codes, a code editor and the AI programming assistant, deep semantic understanding is achieved, and the service quality is improved. And generating a corresponding code snippet.

A low code editor allows for a user to input (e.g., natural language text expressing a request to modify the visual representation). A first stage of interactions with at least one of a set of AI models is used to identify a property of a part of a data instance from which the visual representation is rendered. A second stage of interactions with at least one of the AI models is used to generate a new value for the identified property. In some implementations, these interactions include provision of some metadata regarding the identified property from a schema.

The invention discloses a real-time processing method, system and equipment for high-frequency time sequence data and a storage medium, and relates to the technical field of data processing in the steel industry, and the method comprises the steps: collecting the high-frequency time sequence data of equipment in a steel production process, and uploading the high-frequency time sequence data to a target data bus; based on a trigger signal, sequentially acquiring the high-frequency time sequence data from the target data bus; preprocessing the obtained high-frequency time sequence data to obtain a standard data stream; configuring a calculation process based on a zero code editor, and calculating the standard data stream through the calculation process to obtain calculation result data; respectively storing the calculation result data into a memory database and a disk time sequence database according to a time dimension; and outputting the calculation result data through an application program interface.

1. The name of the design product: graphical user interface of low code editor component management of electronic device. 2. The use of the design product: an electronic device. 3. The design points of the design product: the protected part of the graphical user interface in the electronic device. 4. The picture or photo that best indicates the design points: design 1 front view. 5. The electronic device of design 1-design 5 is the usual design, and other views of design 1-design 5 are omitted. 6. Design 1 is designated as the basic design. 7. The use of the graphical user interface: the product interface of design 1-design 5 is the interface for low code activity editor component management display and interaction; used for upgrading, installing, setting and displaying components in the editor installed or not installed. 8. The human-computer interaction mode of the graphical user interface: the main view interface of Design 1 is an interactive interface for entering the component management list; in the main view interface of Design 1, after clicking on the uninstalled, the Design 1 interface change state diagram 1 is displayed; in the Design 1 interface change state diagram 1 interface, after clicking on the installed in the card (for example, the fourth card), the Design 1 interface change state diagram 2 is displayed; in the Design 1 interface change state diagram 2 interface, after clicking on the selection classification column, a drop-down menu is displayed, and the Design 1 interface change state diagram 3 is displayed for selecting the installation classification of the component; in the Design 1 interface change state diagram 3 interface, after selecting the classification, the Design 1 interface change state diagram 4 is displayed; in the Design 1 interface change state diagram 4 interface, after clicking on the confirm, the Design 1 interface change state diagram 5 is displayed, the component installation is completed, and the component containing information is displayed; the main view interface of Design 2 is an interactive interface for entering the component management list; in the main view interface of Design 2, after clicking on the uninstalled, the Design 2 interface change state diagram 1 is displayed; in the Design 2 interface change state diagram 1 interface, after clicking on the installed in the card (for example, the second card), the Design 2 interface change state diagram 2 is displayed; in the Design 2 interface change state diagram 2 interface, after clicking on the add a row, the Design 2 interface change state diagram 3 is displayed; in the Design 2 interface change state diagram 3 interface, after clicking on the selection component column, a drop-down menu is displayed, and the Design 2 interface change state diagram 4 is displayed; in the Design 2 interface change state diagram 4 interface, after selecting the component and clicking on the setting classification, a drop-down menu is displayed, and the Design 2 interface change state diagram 5 is displayed; in the Design 2 interface change state diagram 5 interface, after selecting the classification, the Design 2 interface change state diagram 6 is displayed; in the Design 2 interface change state diagram 6 interface, after clicking on the confirm, the Design 2 interface change state diagram 7 is displayed, the component installation is completed, and the component containing information is displayed; the main view interface of Design 3 is an interactive interface for entering the component management list; in the main view interface of Design 3, after clicking on the “upgrade to V0.49.1” in the component that needs to be upgraded, the Design 3 interface change state diagram 1 is displayed; in the Design 3 interface change state diagram 1 interface, after clicking on the confirm, the Design 3 interface change state diagram 2 is displayed; in the Design 3 interface change state diagram 2 interface, after clicking on the confirm, the Design 3 interface change state diagram 3 is displayed; in the Design 3 interface change state diagram 3 interface, after clicking on the confirm, the Design 3 interface change state diagram 4 is displayed; in the Design 3 interface change state diagram 4 interface, after clicking on the selection classification column, a drop-down menu is displayed, and the Design 3 interface change state diagram 5 is displayed; in the Design 3 interface change state diagram 5 interface, after selecting the classification, the Design 3 interface change state diagram 6 is displayed; in the Design 3 interface change state diagram 6 interface, after clicking on the confirm, the Design 3 interface change state diagram 7 is displayed, the component installation is completed, and the component containing information is displayed; the main view interface of Design 4 is an interactive interface for entering the component management list; in the main view interface of Design 4, after clicking on the “upgrade to V0.49.1" back, display design 4 interface change state diagram 1; in the design 4 interface change state diagram 1 interface, click OK, display design 4 interface change state diagram 2; in the design 4 interface change state diagram 2 interface, click OK, display design 4 interface change state diagram 3; in the design 4 interface change state diagram 3 interface, set each component classification and click OK, display design 4 interface change state diagram 4, complete component upgrade and display component containing information; in the design 4 interface change state diagram 4 interface, slide the interface, display design 4 interface change state diagram 5; in the design 4 interface change state diagram 5 interface, slide to the bottom of the interface, display design 4 interface change state diagram 6; design 5 main view interface is the interactive interface for entering component management list; in the design 5 main view interface, click "upgrade to V0.49.1" in the component that needs to be upgraded, display design 5 interface change state diagram 1; in the design 5 interface change state diagram 1 interface, click OK, display design 5 interface change state diagram 2; in the design 5 interface change state diagram 2 interface, click OK, display design 5 interface change state diagram 3; in the design 5 interface change state diagram 3 interface, set each component classification and click OK, display design 5 interface change state diagram 4, complete component upgrade and display component containing information; in the design 5 interface change state diagram 4 interface, slide the interface, display design 5 interface change state diagram 5; in the design 5 interface change state diagram 5 interface, slide to the bottom of the interface, display design 5 interface change state diagram 6.

The invention relates to a code editor of a low-code platform and the low-code platform. The code editor comprises a component event script writing module, a storage and storage module, an API object construction module, a user-defined API loading module and a component event execution script module. The component event script writing module provides a script writing interface for a developer to write component event scripts. And the API object construction module analyzes the configuration information when the page is loaded to generate an API object. And the user-defined API loading module obtains the module id set and stores the module id set in a cache for subsequent use. When an event is triggered, the component event execution script module reads script content, executes a script method and calls a method on an API object. The code editor is realized on the basis of an existing low-code platform project, and is used for a user to compile self-defined script event logic, so that logic definition of a complex business process is realized, a code compiling process is greatly simplified, and the code reuse capability is provided.

The application relates to the technical field of low-code development, and provides a code editing method and system based on a low-code development platform, which comprises a user end, a cloud server and an online code editor built in the cloud server; the online code editor is set in the cloud server in advance; wherein the online code editor is configured with a development component and a detection component; after the code editor receives input code of a user, the cloud server analyzes the input code, determines a class name and detection information reflected based on the class name; wherein the detection information is determined by the detection component detecting the input code, and the detection information comprises code completion prompt information, code chain error information and code variables; and a component editing recommendation interface for code revision is constructed according to the detection information.

The invention discloses a code editor cross-language function positioning method based on hierarchical context driving, which comprises the following steps: by taking an interpreted language as a source language and a compiled language as a target language, analyzing a dependency tree and an abstract syntax tree of a source language project to collect source variables in a module layer, a function layer and an instance layer to construct a source tracing table; constructing a layered mapping rule base and establishing a mapping relationship and confidence coefficient between a source variable type and a target variable type in combination with the traceability table, obtaining a file preloading context and an intermediate instruction sequence of a source language, capturing a multi-dimensional calling context during cross-language calling after incremental simulation execution, determining a polymorphic analysis priority, and performing multi-dimensional analysis on the multi-dimensional calling context; according to the method, the mapped target function is matched, then the source code path and the line number of the target function are selected in the target language source code, accurate jump of the code editor is achieved, meanwhile, the source variable type traceability chain is displayed at the target function, and the positioning accuracy and the positioning efficiency of the polymorphic function in the cross-language function are improved.

The invention provides a code assisting method and system based on cursor context perception and multi-mode AI linkage. According to the method, a cursor track of a user is tracked in a code editor in real time, n layers of AST syntax trees at a current cursor are dynamically obtained, and context feature vectors are generated by combining the track of the cursor, item dependence and other features. Furthermore, an optimal path is selected according to the complexity of a context feature vector by adopting a dynamic routing mode, a local reasoning service comprising a basic layer is selected when the complexity is low, and a cloud service comprising an enhancement layer large model is requested for assistance when the complexity is high. And for the cloud service, various characteristics encrypted and uploaded by a large number of clients are aggregated through federated learning service, and the cloud enhancement layer large model is continuously updated through the feedback of the user, so that the user experience in a relatively good code editor environment is provided.

The invention provides an element-based online model development system and method, and the system comprises a front-end interface layer which provides a graphical interface comprising an element library, canvas and a code editor; the back-end service layer is used for automatically generating a complete project code containing a standard interface and a basic skeleton code according to a predefined element which is dragged and dropped by a user in a canvas, and managing a construction process; and the containerized execution environment layer is used for providing an isolation container for compiling, packaging and running project codes. The method comprises the following steps: forming a model flow through a drag-and-drop element; automatically generating a project skeleton code; a user compiles core logic at a specified position of the skeleton code; compilation and packaging are completed in the container environment. According to the invention, through combination of element-based, automatic code generation and containerized environment, online development experience of ready-to-use after box opening is realized, the development threshold of the structured element model is reduced, the model code reuse rate and the model development process efficiency are improved, and the environment consistency is ensured.

The application discloses an intelligent completion code optimization method based on texture pre-rendering and multi-level caching, previously establishes a syntax rule set and a GPU cache characteristic database, saves a syntax style table, generates a font atlas and loads current GPU cache parameters when a code editor starts, divides candidate code segments into data blocks after a candidate code segment list is popped out, analyzes a syntax type in parallel, determines a character style, generates candidate code segment textures through instantiation rendering and fragment shader, then according to current GPU cache parameters, a selected priority of the candidate code segments and a volume after compression, the textures are distributed to a first-level cache, a second-level cache or global memory according to rules, metadata is recorded and added to a global texture cache table, when a user selects a candidate code segment, texture data is read from a corresponding GPU cache, display coordinates are calculated in combination with a cursor row and column index, editor basic style parameters and a DPI scaling ratio, rendering and drawing of the textures are completed, and optimized display of the intelligent completion code is realized.

The present disclosure relates to the technical field of computers, and in particular to a method and apparatus for rendering a code editor, and a device, a medium and a program product. The method comprises: in response to a target rendering instruction, determining a target rendering type of a code editor, wherein the target rendering type indicates the scope of rendering the code editor; on the basis of the target rendering type, acquiring, from a first document object node, a first region to be rendered, wherein the first document object node is used for storing content information to be rendered and displayed, and the first region includes the code editor; on the basis of the first region, parsing out the current designated location to be rendered; and rendering elements included in the first region to the designated location.

The invention discloses a GPU context awareness-based code editor dynamic text rendering acceleration method, which comprises the following steps of: establishing a multi-dimensional semantic tag system comprising variables, functions, errors and structures, extracting semantic sub-dimensions of characters, generating character semantic tags through operation, caching the character semantic tags to a semantic tag SSBO, constructing a mapping rule of the semantic tags and rendering styles, and carrying out text rendering on the rendering styles according to the mapping rule. The CPU encodes the semantic rules into semantic rule textures; identifying structural units and layout attributes thereof, encoding the structural units into structural textures by the CPU, and uploading the structural textures to a structural layout SSBO of the GPU; the calculation shader reads two types of SSBO, respectively allocates four types of weights of semantics, interaction, structure and effect for characters, and generates a pattern weight texture after determining a fusion coefficient; the vertex shader calculates the final screen position of the character in parallel according to the structure unit to which the character belongs; and the fragment shader reads the two types of SSBO, each texture and the final screen position output by the vertex shader, hierarchical fusion is carried out according to a weight sequence, and character pixel-level rendering is completed.

The invention provides an online code compiling and running system and method applied to visual development, and relates to the technical field of development, the method comprises the following steps: using a code editor with code formatting capability and code error checking capability to display codes, and providing an editing function; analyzing the code in the code editing module, and persistently storing the code and a data structure obtained by analysis; configuring a data structure stored in the code storage module; and combining the code in the code editing module, the code in the visual designer and the code published last time to obtain a finally published code. According to the method, the user can be supported to write codes on line, the written codes can be compatible with the current visual development method, code conflicts caused by modification of raw codes are avoided, and increasingly complex visual development requirements in enterprise informatization are efficiently met.

The embodiment of the invention discloses a program tuning code marking method and device, a terminal and a medium, and the method comprises the steps: marking an optimization code in a code editor; obtaining a first program performance information file corresponding to the to-be-optimized code; obtaining a second program performance information file corresponding to the modified and optimized code; comparing the first program performance information file with the second program performance information file to obtain a difference function between the first program performance information file and the second program performance information file; and searching the difference function by utilizing a code editor difference tool, and determining a modified source code according to the mark. The change condition of the program performance in the whole source code modification process can be recorded, and a developer can carry out optimization, backtracking and iteration on the program performance conveniently.

The application discloses a code debugging method and device, equipment, medium and product, and relates to the technical field of computers. The method comprises the following steps: acquiring a first debugging command input in a debugging interaction window, wherein the debugging interaction window is created by calling a view interface of a code editor; determining a command execution result based on the first debugging command by calling a debugging interface of the code editor, wherein the debugging interface is used for calling a debugging tool to perform code debugging; and controlling the debugging interaction window to perform display based on the command execution result; wherein an extension plug-in is used to perform at least one of the following functions: command enhancement processing on the first debugging command, and display enhancement processing on the command execution result.

A system receives a request from a software developer's issue tracker or code editor to perform a software engineering task, and outputs an issue report which describes the software engineering task and / or source code for performing the software engineering task to the software developer. The system stores the software developer's update of the issue report and / or source code changes for the software engineering task. The system receives the software developer's request for a predicted completion of the software engineering task, retrieves the software engineering task's context data, and transforms the context data to be data format compatible with a machine-learning model that learned to assist with software engineering tasks. The machine-learning model uses the transformed context data to predict completions of the software engineering task. The system enables the software developer to complete the software engineering task by outputting the predicted completions of the software engineering task to the developer.

A system stores a source code file's changes from a software developer's code editor, for a software engineering task. Upon receiving the code editor's request to predict source code for the source code file, the system retrieves the software engineering task's context data, and transforms the context data to be compatible with the data format used to train a machine-learning model to assist with performing software engineering tasks. The machine-learning model uses the transformed context data to predict the source code for the source code file, with source code file portions corresponding to predicted source code portions. The system identifies each portion of the source code file which is differing from a corresponding portion of the predicted source code, via the code editor. The system commits any differing portions of the predicted source code, which are requested and accepted by the code editor, to the source code file.

This invention discloses a GPU-based context-aware code editor dynamic text rendering acceleration method. It establishes a multi-dimensional semantic tagging system including variables, functions, errors, and structures. Semantic sub-dimensions of characters are extracted and processed to generate character semantic tags, which are then cached in semantic tag SSBOs. A mapping rule between semantic tags and rendering styles is constructed, and the CPU encodes the semantic rules into semantic rule textures. Structural units and their layout attributes are identified, and the CPU encodes them into structural textures and uploads them to the GPU's structural layout SSBOs. The compute shader reads two types of SSBOs and assigns four weights—semantic, interactive, structural, and effect—to the characters. After determining the fusion coefficients, it generates style-weighted textures. The vertex shader calculates the final screen position of the character in parallel based on the structural unit to which the character belongs. The fragment shader reads the two types of SSBOs, each texture, and the final screen position output by the vertex shader, and fuses them layer by layer according to the weight order to complete pixel-level character rendering.

Aspects of the disclosed technology include computer-implemented systems and methods for integrating machine-learned generative models with code editing tools. A code editor is configured to execute computer-executable code within code cells of a code editor interface including a first interface portion and a second interface portion. The interface portion is configured to receive user input for defining and editing a set of code cells within the first interface portion. Each code cell of the set of code cells is independently executable by the code editor application. The second interface portion is configured to receive user input for defining and submitting user queries to a machine-learned generative model. The code editor is configured to modify at least one code cell of the set of cells based at least in part on an output of the machine-learned generative model in response to a user query.

An omissible text is constructed that prioritizes content included in hints of a large language model having a context window of a fixed size. Generation of texts according to instructions generated by developers or automatic generation of source codes within a source code editor may be omitted. The source code editor may include features that select certain code lines as important or focal, which are assigned high priority values. The changed line, the source code line at the current cursor position, the source code line at the beginning of the file, and the line of output data are regarded as focus lines. The non-focal row is assigned a priority based on a distance from the focal row. Text may be omitted to limit data included in the hint to a contextual window size by replacing the lowest value text and source code line with a replacement string.

The invention provides a data development debugging method and device, equipment, a storage medium and a program product. Relates to the technical field of data development. The method comprises the following steps: in response to a received debugging request initiated by a user through a data development platform, allocating computing resources based on the debugging request and starting an interactive debugging environment instance; the debugging request comprises a Python operator code to be debugged; executing the Python operator code to be debugged in the interactive debugging environment instance, and displaying a code execution result and a variable value; and backfilling the debugged Python operator code in the interactive debugging environment instance into a static code editor of the data development platform. According to the method provided by the invention, the code execution state can be checked in real time, the code writing and debugging process is deeply integrated, environment switching and manual operation are avoided, and human errors are reduced; through a reasonable resource management and scheduling mechanism, it is ensured that computing resources can be fully utilized in the starting and running process of the interactive debugging environment instance, and resource waste is avoided.

The invention discloses an upper computer integration method and system based on Vs Code edition, and the method comprises the steps: enabling Vs Code to run into upper computer software through the interoperation of. NET and JavaScript in the same process, and enabling the Vs Code and the upper computer software to form a unified application program; loading the first plug-in and the second plug-in by using the Vs Code, and editing the first code and the second code respectively; respectively compiling and debugging the first code and the second code by utilizing the first plug-in and the second plug-in; and enabling the first code or the second code to interact with the interaction interface of the upper computer software and the lower computer software through the dynamic library. According to the method, the Vs Code editor is used for editing, compiling and debugging the codes, so that the codes can directly interact with the upper computer and the lower computer, seamless Vs Code integration of the upper computer is realized, other AI tools can be integrated, and the code development efficiency is improved.