A method and apparatus for processing programming tasks

Abstract

The embodiment of the present application discloses a method and device for processing programming tasks. In the embodiment of the present application, the development requirement of a user is acquired, wherein the development requirement carries context information; the development requirement is subjected to workflow intention recognition to determine the task type of the development requirement; the development requirement is split according to the task type to determine a plurality of subtasks and the part of the context information corresponding to each of the subtasks; the execution sequence of the plurality of subtasks is determined, wherein there are subtasks that are executed in parallel in the plurality of subtasks; the plurality of subtasks are executed according to the execution sequence to generate a plurality of subtask results; and the plurality of subtask results are aggregated to generate the target result corresponding to the development requirement. Through the above method, the complex programming task can be processed efficiently and accurately.

Description

Technical Field

[0001] This invention relates to the field of computer technology, and more specifically, to a method and apparatus for processing programming tasks. Background Technology

[0002] With the rapid development of artificial intelligence (AI), AI programming agents are increasingly being used for programming in complex software development tasks.

[0003] In existing technologies, traditional AI programming agents can only execute complex programming tasks sequentially, resulting in a lengthy overall development cycle. Furthermore, due to the context window limitations of large language models, prolonged development dialogues can lead to the compression or discarding of early requirements details, design decisions, and code logic, affecting the accuracy and consistency of subsequent development. In addition, there are issues such as insufficient resource utilization and the risk of error propagation.

[0004] In conclusion, how to efficiently and accurately process complex programming tasks is a problem that needs to be solved. Summary of the Invention

[0005] In view of this, embodiments of the present invention provide a method and apparatus for processing programming tasks, which can efficiently and accurately process complex programming tasks.

[0006] In a first aspect, embodiments of the present invention provide a method for processing programming tasks, the method comprising: acquiring a user's development requirements, wherein the development requirements carry context information; performing workflow intent recognition on the development requirements to determine the task type of the development requirements; splitting the development requirements according to the task type to determine multiple subtasks and a portion of the context information corresponding to each subtask, wherein the portion of the context information corresponding to each subtask includes a complete requirement description, a list of related files, and execution parameters for the subtask; determining the execution order of the multiple subtasks, wherein some of the multiple subtasks are executed in parallel; executing the multiple subtasks according to the execution order to generate multiple subtask results; and aggregating the multiple subtask results to generate a target result corresponding to the development requirements.

[0007] Optionally, the method further includes: obtaining a key parameter summary for each subtask; and generating a prompt word corresponding to each subtask based on partial context information and the key parameter summary.

[0008] Optionally, the method further includes updating the state information of each subtask.

[0009] Optionally, determining the execution order of the plurality of subtasks specifically includes: determining the execution order of the plurality of subtasks based on their dependencies and resource availability.

[0010] Optionally, the method further includes: receiving the status information of the subtask.

[0011] Optionally, the method further includes: sending the status information of the subtask.

[0012] Optionally, the method further includes: dynamically adjusting the priority and execution order of the multiple subtasks based on the results of the multiple subtasks.

[0013] Optionally, the status information includes: pending status, running status, failed status, paused status, and completed status.

[0014] Secondly, embodiments of the present invention provide an apparatus for processing programming tasks, the apparatus comprising: an acquisition unit for acquiring a user's development requirements, wherein the development requirements carry context information; a first determination unit for performing workflow intent recognition on the development requirements and determining the task type of the development requirements; a second determination unit for splitting the development requirements according to the task type, determining multiple subtasks and a portion of the context information corresponding to each subtask, wherein the portion of the context information corresponding to each subtask includes a complete requirement description, a list of related files, and execution parameters for the subtask; a third determination unit for determining the execution order of the multiple subtasks, wherein some of the multiple subtasks are executed in parallel; and a generation unit for executing the multiple subtasks according to the execution order and generating multiple subtask results; the generation unit is further configured to aggregate the multiple subtask results to generate a target result corresponding to the development requirements.

[0015] Optionally, the acquisition unit is further configured to: acquire a summary of key parameters for each subtask; the generation unit is further configured to: generate a prompt word corresponding to each subtask based on partial context information corresponding to each subtask and the summary of key parameters.

[0016] Optionally, the apparatus further includes an update unit for updating the status information of each of the subtasks.

[0017] Optionally, the third determining unit is specifically used to: determine the execution order of the multiple subtasks based on their dependencies and resource availability.

[0018] Optionally, the device further includes a receiving unit for receiving the status information of the subtask.

[0019] Optionally, the device further includes a sending unit for sending the status information of the subtask.

[0020] Optionally, the device further includes: an adjustment unit, configured to dynamically adjust the priority and execution order of the plurality of subtasks based on the results of the plurality of subtasks.

[0021] Optionally, the status information includes: pending status, running status, failed status, paused status, and completed status.

[0022] Thirdly, embodiments of the present invention provide a system for processing programming tasks, the system comprising: a requirement acquisition module, an intent recognition engine, a task decomposition engine, a parallel scheduler, an execution engine, and an aggregation module; wherein, the requirement acquisition module is used to acquire the user's development requirements, wherein the development requirements carry context information; the intent recognition engine is used to perform workflow intent recognition on the development requirements to determine the task type of the development requirements; the task decomposition engine is used to decompose the development requirements according to the task type to determine multiple subtasks and a portion of the context information corresponding to each subtask, wherein the portion of the context information corresponding to each subtask includes a complete requirement description, a list of related files, and execution parameters for the subtask; the parallel scheduler is used to determine the execution order of the multiple subtasks, wherein some of the multiple subtasks are executed in parallel; the execution engine is used to execute the multiple subtasks according to the execution order to generate multiple subtask results; the aggregation module is used to aggregate the multiple subtask results to generate the target result corresponding to the development requirements.

[0023] Fourthly, embodiments of the present invention provide an electronic device, including a memory and a processor, the memory being used to store one or more computer program instructions, wherein the one or more computer program instructions are executed by the processor to implement the method as described in the first aspect or any one of the possible methods of the first aspect.

[0024] Fifthly, embodiments of the present invention provide a computer-readable storage medium having stored thereon computer program instructions that, when executed by a processor, implement the method as described in the first aspect or any one of the possible methods described in the first aspect.

[0025] In this embodiment of the invention, the development requirements of a user are obtained, wherein the development requirements carry contextual information; workflow intent recognition is performed on the development requirements to determine the task type of the development requirements; the development requirements are split according to the task type to determine multiple sub-tasks and a portion of the contextual information corresponding to each sub-task, wherein the portion of the contextual information corresponding to each sub-task includes a complete requirement description, a list of related files, and execution parameters for the sub-task; the execution order of the multiple sub-tasks is determined, wherein some of the multiple sub-tasks are executed in parallel; the multiple sub-tasks are executed according to the execution order to generate multiple sub-task results; the results of the multiple sub-tasks are aggregated to generate the target result corresponding to the development requirements. Through the above method, workflow intent recognition is used to decompose the development requirements, and context stripping and preservation are achieved during the decomposition and generation of sub-tasks, improving the quality of sub-task results; and multiple sub-tasks are executed in parallel, improving task processing efficiency. Attached Figure Description

[0026] The above and other objects, features and advantages of the present invention will become clearer from the following description of embodiments of the invention with reference to the accompanying drawings, in which: Figure 1 This is a flowchart of a method for processing programming tasks according to an embodiment of the present invention; Figure 2 This is a schematic diagram of state information in an embodiment of the present invention; Figure 3 This is a schematic diagram of the structure of an AI programming agent according to an embodiment of the present invention; Figure 4 This is a schematic diagram of another AI programming agent in an embodiment of the present invention; Figure 5 This is a flowchart of another method for processing programming tasks in an embodiment of the present invention; Figure 6 This is a schematic diagram of a device for processing programming tasks according to an embodiment of the present invention; Figure 7 This is a schematic diagram of an electronic device according to an embodiment of the present invention. Detailed Implementation

[0027] The present application is described below based on embodiments, but it is not limited to these embodiments. In the detailed description of the present application below, certain specific details are described in detail. Those skilled in the art can fully understand the present application without these details. To avoid obscuring the substance of the present application, well-known methods, processes, flows, elements, and circuits are not described in detail.

[0028] Furthermore, those skilled in the art should understand that the accompanying drawings provided herein are for illustrative purposes only and are not necessarily drawn to scale.

[0029] Unless the context explicitly requires it, words such as "including" or "contains" throughout the application should be interpreted as including rather than exclusive or exhaustive; that is, meaning "including but not limited to".

[0030] In the description of this application, it should be understood that the terms "first," "second," etc., are used for descriptive purposes only and should not be construed as indicating or implying relative importance. Furthermore, in the description of this application, unless otherwise stated, "a plurality of" means two or more.

[0031] In existing technologies, traditional AI programming agents can only execute complex programming tasks sequentially. Even when multiple independent development modules are involved, the next module cannot begin execution until the previous one is fully completed, resulting in a lengthy development cycle and low execution efficiency. Due to the context window limitations of large language models, prolonged development dialogues can lead to the compression or discarding of early requirement details, design decisions, and code logic, resulting in the loss of contextual information and affecting the accuracy and consistency of subsequent development. Furthermore, there is insufficient resource utilization. Specifically, while waiting for a subtask to complete, such as an API call or file operation, the AI ​​programming agent is idle and cannot process other independent development tasks in parallel, resulting in wasted computing resources. Moreover, in the sequential execution mode, errors in earlier tasks can affect all subsequent tasks, and it is difficult to quickly locate and fix problems, leading to the risk of error propagation. Therefore, how to efficiently and accurately process complex programming tasks is a problem that needs to be solved.

[0032] In this embodiment of the invention, to solve the above problems, an AI programming agent is designed, and a method for processing programming tasks based on the AI ​​programming agent is proposed, specifically as follows: Figure 1 As shown, the method includes: Step S101: Obtain the user's development requirements.

[0033] Specifically, the development requirements carry contextual information.

[0034] In one possible implementation, the user interaction layer (also known as the user interface) of the AI ​​programming agent receives development requirements input by the user. These development requirements can be single-page development, multi-page development, application programming interface (API) development, or full-stack application development. The development requirements carry corresponding context information, and when the development requirements are complex, the context information is also complex.

[0035] Step S102: Perform workflow intent identification on the development requirements to determine the task type of the development requirements.

[0036] Specifically, the intent recognition engine of the AI ​​programming agent performs workflow intent recognition on the development requirements, automatically determining the task type of the development requirements. Different task types correspond to different task decomposition strategies and execution templates. The task decomposition strategy is a strategy for splitting the development requirements into multiple sub-tasks. The task type can be Requirement to Code (R2C), Design to Code (D2C), Technical Solution to Code (T2C), etc., which are only illustrative examples here.

[0037] Step S103: Decompose the development requirements according to the task type, and determine multiple sub-tasks and the corresponding context information for each sub-task.

[0038] Specifically, the context information corresponding to each subtask includes a complete requirement description, a list of related files, and execution parameters for the subtask.

[0039] In one possible implementation, the TaskSplitter engine in the AI ​​programming agent is used to intelligently break down complex tasks into parallel executable subtasks. That is, when the development requirements are split into multiple subtasks, the context information of the development requirements is also fully decomposed. Decomposing the context information of the development requirements according to the data structure of each subtask ensures that each subtask can access the necessary context information, avoiding execution deviations caused by information compression. This complete decomposition of the context information of the development requirements can also be called a context preservation mechanism, ensuring that the original context information is maintained during subtask execution.

[0040] In one possible implementation, while determining the context information corresponding to each subtask, it is necessary to obtain a summary of key parameters for each subtask, and generate a prompt for each subtask based on the partial context information and the summary of key parameters for each subtask.

[0041] In this embodiment of the invention, the prompt words corresponding to the subtask can be used by the execution engine in the AI ​​programming agent when the subtask is executed.

[0042] In one possible implementation, the State Manager in the AI ​​programming agent is used to uniformly manage task status, subtask relationships, and execution progress; wherein, while creating multiple subtasks, multiple subtasks are also created in the State Manager as pending.

[0043] Step S104: Determine the execution order of the multiple subtasks.

[0044] Specifically, among the multiple subtasks, there are subtasks that are executed in parallel.

[0045] In one possible implementation, the parallel scheduler in the AI ​​programming agent manages the concurrent execution and state coordination of multiple subtasks. Specifically, the parallel scheduler determines the execution order of the multiple subtasks. For example, if there are two subtasks, subtask 1 and subtask 2, and these two subtasks are executed in parallel; or if there are four subtasks, where subtask 3 depends on the execution result of subtask 1 and subtask 4 depends on the execution result of subtask 2, then subtask 1 and subtask 2 are executed in parallel first, subtask 3 is executed after subtask 1 is completed, and subtask 4 is executed after subtask 2 is completed. In one possible implementation, the execution order of the multiple subtasks is determined based on their dependencies and resource availability.

[0046] This is just an illustrative example. In actual applications, there can be multiple subtasks, and the execution order is determined according to the actual situation.

[0047] Step S105: Execute the multiple subtasks in the execution order to generate multiple subtask results.

[0048] Specifically, the execution engine of the AI ​​programming agent executes the multiple subtasks in the execution order, wherein each subtask has a pre-generated prompt word, and a subtask result is generated for each subtask.

[0049] Step S106: Aggregate the results of the multiple subtasks to generate the target result corresponding to the development requirements.

[0050] Specifically, the development requirement can also be referred to as the parent task, and the AI ​​programming agent aggregates the results of the multiple sub-tasks to generate the target result corresponding to the development requirement.

[0051] In one possible implementation, the method further includes: after the plurality of subtasks begin execution, the event-driven mechanism (EventEmitter) in the AI ​​programming agent receives a dispatch event triggered by the subtask. Since the event-driven mechanism is used to implement asynchronous communication and state synchronization between tasks, i.e., communication between subtasks and parent tasks, the parent task receives the current state information of the subtask sent by the EventEmitter. Assuming the state information is a running state, the parent task updates the running state of the subtask to the StateManager. Alternatively, a TASK_COMPLETE event is automatically triggered when any subtask completes. After receiving the TASK_COMPLETE event, the EventEmitter determines that the current state is a completed state. The EventEmitter sends the completed state of any subtask to the parent task. That is, the parent task listens for the TASK_COMPLETE event and updates the completed state to the StateManager, achieving efficient state synchronization. The state information includes pending state, running state, failed state, paused state, and completed state, which is only an example for illustration.

[0052] In this embodiment of the invention, the relationship between the state information is as follows: Figure 2 As shown, after a subtask is created, its status is "pending". When the task is started, the subtask enters the "running" state. If the task fails during execution, it is updated to a "failed" state; it is then re-queued and updated to "pending". If the task is completed, it is updated to a "completed" state; if the task is paused or awaiting approval, it is updated to a "paused" state, and will be updated back to "running" after the task resumes. The "pending" state can also be called the "parallel execution" state, supporting multiple subtasks running simultaneously. The "paused" state uses an intelligent pause mechanism that does not block the execution of other subtasks.

[0053] In one possible implementation, the EventEmitter can also be used to receive the status information of the subtask and to send the status information of the subtask.

[0054] In this embodiment of the invention, the AI ​​programming agent also includes a Focus Chain, which is used to dynamically adjust task priorities and execution order. Specifically, the Focus Chain dynamically adjusts the priorities and execution order of the multiple sub-tasks based on the results of the multiple sub-tasks, ensuring that tasks on the critical path are completed first, while also supporting users to manually adjust the task execution order.

[0055] In this embodiment of the invention, a system for processing programming tasks is provided, namely the AI ​​programming agent, the system specifically as follows: Figure 3 As shown, the system includes the following components: a requirement acquisition module 301, an intent recognition engine 302, a task decomposition engine 303, a parallel scheduler 304, an execution engine 305, and an aggregation module 306. The requirement acquisition module 301 acquires the user's development requirements, which carry contextual information. The intent recognition engine 302 performs workflow intent recognition on the development requirements to determine the task type. The task decomposition engine 303 splits the development requirements according to the task type, determining multiple subtasks and a portion of the contextual information corresponding to each subtask. The portion of the contextual information corresponding to each subtask includes a complete requirement description, a list of related files, and execution parameters for the subtask. The parallel scheduler 304 determines the execution order of the multiple subtasks, including subtasks that can be executed in parallel. The execution engine 305 executes the multiple subtasks according to the execution order, generating multiple subtask results. The aggregation module 306 aggregates the multiple subtask results to generate the target result corresponding to the development requirement.

[0056] In one possible implementation, the system further includes other modules, including: a state manager and an event-driven mechanism, and a focus chain management, wherein the state manager is used to record the state information of each subtask, the event-driven mechanism is used for communication between subtasks and parent tasks, and the focus chain management is used to dynamically adjust task priorities and execution order.

[0057] The task execution method of the AI ​​programming agent is described in detail below through two complete embodiments: Specific Implementation Example 1 Assuming that the AI ​​programming agent is as follows: Figure 4It includes a user interaction layer 401, a task decomposition layer 402, a parallel scheduling layer 403, an execution engine layer 404, and a monitoring and coordination layer 405. The user interaction layer 401 includes an engine for acquiring development requirements and an intent recognition engine. The task decomposition layer 402 includes workflow intent recognition, a task decomposition engine, and a context preservation mechanism. The parallel scheduling layer 403 includes a state manager, a parallel scheduler, and a subtask queue. The execution engine layer 404 includes subtask 1, subtask 2…subtask N, and an event-driven mechanism event bus. The monitoring and coordination layer 405 includes task state synchronization, focus chain management, and result aggregation, ultimately outputting the results corresponding to the development requirements. Specific Implementation Example 2 Assume the parallel scheduling execution flowchart is as follows: Figure 5 The diagram illustrates the relationship between the user and the various modules within the AI ​​programming agent. Specifically, the user submits complex development requirements to the AI ​​programming agent. The agent identifies these requirements as the parent task and analyzes it using an intent recognition engine and a task decomposition engine. A sub-task queue is created, and the state manager updates all sub-tasks in the queue to a pending state. Multiple sub-tasks are started in parallel; for example, only sub-tasks 1 and 2 exist and execute concurrently. Sub-tasks 1 and 2 send task start emission events to the event-driven mechanism. The event-driven mechanism then sends its running status to the parent task, which then executes the event. The status is updated in the status manager, and subtask 1 and subtask 2 are executed in parallel. For example, subtask 1 is for UI development, and subtask 2 is for API integration. After subtask 1 and subtask 2 are completed, a task completion dispatch event is triggered, which is sent to the event-driven mechanism. The event-driven mechanism sends the completion status to the parent task, and the parent task updates the completion status in the status manager. The status manager determines that all subtasks in the subtask queue are completed, and the parent task aggregates the results of each subtask for verification and generates the final result to be returned to the user. The focus chain management can also participate in the processing, but this will not be elaborated here.

[0059] In this embodiment of the invention, a file lock mechanism (File Lock Manager) is also set in the AI ​​programming agent. At any given time, only one subtask can read and modify the same file, which solves the file conflict problem in concurrent execution, ensures that multiple subtasks can safely modify different files at the same time, and avoids competitive writing to the same file.

[0060] Through the above embodiments, multiple subtasks can be executed simultaneously, reducing development time for complex development requirements. Furthermore, the subtask structure strictly preserves the complete context information of each subtask, avoiding information loss due to context window limitations. Moreover, a unified state management interface supports precise tracking of various states such as pending, running, completed, failed, and paused, improving the reliability of state management. In addition, in parallel execution mode, the failure of a single subtask will not affect the execution of other independent tasks, allowing for rapid problem location and localized repair. These embodiments of the invention not only shorten execution time but also improve the accuracy of task generation.

[0061] In this embodiment of the invention, an apparatus for processing programming tasks is provided, such as... Figure 6 As shown, it specifically includes: an acquisition unit 601, a first determination unit 602, a second determination unit 603, a third determination unit 604, and a generation unit 605; The acquisition unit 601 is used to acquire the user's development requirements, wherein the development requirements carry context information; the first determination unit 602 is used to perform workflow intent recognition on the development requirements and determine the task type of the development requirements; the second determination unit 603 is used to split the development requirements according to the task type, determine multiple sub-tasks and a portion of the context information corresponding to each sub-task, wherein the portion of the context information corresponding to each sub-task includes a complete requirement description, a list of related files, and execution parameters for the sub-task; the third determination unit 604 is used to determine the execution order of the multiple sub-tasks, wherein some of the multiple sub-tasks are executed in parallel; the generation unit 605 is used to execute the multiple sub-tasks according to the execution order and generate multiple sub-task results; the generation unit 605 is further used to aggregate the multiple sub-task results to generate the target result corresponding to the development requirements.

[0062] Furthermore, the acquisition unit is also configured to: acquire a summary of key parameters for each subtask; the generation unit is also configured to: generate a prompt word corresponding to each subtask based on the partial context information corresponding to each subtask and the summary of key parameters.

[0063] Furthermore, the device also includes an update unit for updating the status information of each of the subtasks.

[0064] Furthermore, the third determining unit is specifically used to: determine the execution order of the multiple subtasks based on their dependencies and resource availability.

[0065] Furthermore, the device further includes a receiving unit for receiving the status information of the subtask.

[0066] Furthermore, the device also includes a sending unit for sending the status information of the subtask.

[0067] Furthermore, the device also includes an adjustment unit, configured to dynamically adjust the priority and execution order of the multiple subtasks based on the results of the multiple subtasks.

[0068] Furthermore, the status information includes: pending status, running status, failed status, paused status, and completed status.

[0069] Figure 7 This is a schematic diagram of the structure of the electronic device described in an embodiment of the present invention. Figure 7 As shown, it includes a general computer hardware architecture, which includes at least a processor 701 and a memory 702. The processor 701 and the memory 702 are connected via a bus 703. The memory 702 is adapted to store instructions or programs executable by the processor 701. The processor 701 can be a standalone microprocessor or a collection of one or more microprocessors. Thus, the processor 701 executes the instructions stored in the memory 702 to perform the method flow of the embodiments of the present invention as described above, thereby realizing data processing and control of other devices. The bus 703 connects the above-mentioned components together, and also connects the above-mentioned components to a display controller 704, a display device, and an input / output (I / O) device 705. The input / output (I / O) device 705 can be a mouse, keyboard, modem, network interface, touch input device, motion-sensing input device, printer, and other devices known in the art. Typically, the input / output device 705 is connected to the system via an input / output (I / O) controller 706.

[0070] The instructions stored in memory 702 are executed by at least one processor 701 to: acquire user development requirements, wherein the development requirements carry context information; perform workflow intent recognition on the development requirements to determine the task type of the development requirements; split the development requirements according to the task type to determine multiple subtasks and a portion of the context information corresponding to each subtask; determine the execution order of the multiple subtasks; execute the multiple subtasks according to the execution order to generate multiple subtask results; and aggregate the multiple subtask results to generate the target result corresponding to the development requirements.

[0071] Specifically, the electronic device includes: one or more processors 701 and a memory 702. Figure 7Take a processor 701 as an example. The processor 701 and the memory 702 can be connected via a bus or other means. Figure 7 Taking a bus connection as an example, memory 702, as a non-volatile computer-readable storage medium, can be used to store non-volatile software programs, non-volatile computer-executable programs, and modules. Processor 701 executes various functional applications and data processing of the device by running the non-volatile software programs, instructions, and modules stored in memory 702, thereby implementing the aforementioned method for determining and programming processing tasks.

[0072] Memory 702 may include a program storage area and a data storage area, wherein the program storage area may store the operating system and applications required for at least one function; the data storage area may store an option list, etc. Furthermore, memory 702 may include high-speed random access memory, and may also include non-volatile memory, such as at least one disk storage device, flash memory device, or other non-volatile solid-state storage device. In some embodiments, memory 702 may optionally include memory remotely located relative to processor 701, and these remote memories may be connected to external devices via a network. Examples of such networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.

[0073] One or more modules are stored in memory 702, and when executed by one or more processors 701, they perform the method for processing programming tasks in any of the above method embodiments.

[0074] As those skilled in the art will recognize, various aspects of the embodiments of the present invention can be implemented as a system, method, or computer program product. Therefore, various aspects of the embodiments of the present invention can take the form of a completely hardware implementation, a completely software implementation (including firmware, resident software, microcode, etc.), or an implementation combining software and hardware aspects, which may generally be referred to herein as a "circuit," "module," or "system." Furthermore, various aspects of the embodiments of the present invention can take the form of a computer program product implemented in one or more computer-readable media having computer-readable program code implemented thereon.

[0075] Any combination of one or more computer-readable media can be used. A computer-readable medium can be a computer-readable signal medium or a computer-readable storage medium. A computer-readable storage medium can be, for example, (but not limited to) an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or apparatus, or any suitable combination thereof. More specific examples (not an exhaustive list) of computer-readable storage media will include: an electrical connection having one or more wires, a portable computer floppy disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable optical disc read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In the context of embodiments of the present invention, a computer-readable storage medium can be any tangible medium capable of containing or storing a program used by or in conjunction with an instruction execution system, device, or apparatus.

[0076] Computer-readable signal media may include propagated digital signals having computer-readable program code implemented therein, such as in baseband or as part of a carrier wave. Such propagated signals may take any of a variety of forms, including, but not limited to, electromagnetic, optical, or any suitable combination thereof. A computer-readable signal medium may be any computer-readable medium that is not a computer-readable storage medium and can communicate, propagate, or transmit a program used by or in conjunction with an instruction execution system, device, or apparatus.

[0077] Program code implemented on a computer-readable medium may be transmitted using any suitable medium, including but not limited to wireless, wired, fiber optic cable, RF, or any suitable combination thereof.

[0078] Computer program code for performing operations relating to various aspects of embodiments of the present invention can be written in any combination of one or more programming languages, including: object-oriented programming languages ​​such as Java, Smalltalk, C++, etc.; and conventional procedural programming languages ​​such as the "C" programming language or similar programming languages. The program code can be executed as a standalone software package entirely on the user's computer, partially on the user's computer, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the latter case, the remote computer can be connected to the user's computer via any type of network, including a local area network (LAN) or a wide area network (WAN), or it can be connected to an external computer (e.g., via the Internet provided by an Internet service provider).

[0079] The flowchart illustrations and / or block diagrams of the methods, apparatus (systems), and computer program products according to embodiments of the present invention describe various aspects of the embodiments of the present invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, or other programmable data processing apparatus to produce a machine such that the instructions (executed via the processor of the computer or other programmable data processing apparatus) create means for implementing the functions / actions specified in the flowchart and / or block diagram blocks or blocks.

[0080] These computer program instructions may also be stored in a computer-readable medium that can direct a computer, other programmable data processing apparatus or other means to operate in a particular manner, such that the instructions stored in the computer-readable medium produce an article of writing that includes instructions that implement the functions / actions specified in flowchart and / or block diagram blocks or blocks.

[0081] Computer program instructions may also be loaded onto a computer, other programmable data processing apparatus or other device to cause a series of operable steps to be performed on the computer, other programmable apparatus or other device to produce a computer-implemented process, such that the instructions, which execute on the computer or other programmable apparatus, provide for implementing the functions / actions specified in flowchart and / or block diagram blocks or blocks.

[0082] The above description is merely a preferred embodiment of this application and is not intended to limit this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the protection scope of this application.

[0083] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, and displayed data) involved in this application are all information and data authorized by the user or fully authorized by all parties. Furthermore, the collection, use, and processing of such data must comply with the relevant laws, regulations, and standards of the relevant countries and regions, and corresponding access points are provided for users to choose to authorize or refuse processing. A user's refusal to process personal information beyond what is necessary for basic functions will not affect the user's use of basic functions.

Claims

1. A method for processing programming tasks, characterized in that, The method includes: Obtain the user's development requirements, wherein the development requirements carry contextual information; Workflow intent identification is performed on the development requirements to determine the task type of the development requirements; The development requirements are broken down according to the task type to determine multiple sub-tasks and a portion of the context information corresponding to each sub-task. The portion of the context information corresponding to each sub-task includes a complete requirement description, a list of related files, and execution parameters for the sub-task. Determine the execution order of the plurality of subtasks, wherein some of the plurality of subtasks are executed in parallel; The multiple subtasks are executed in the specified execution order to generate multiple subtask results; The results of the multiple subtasks are aggregated to generate the target result corresponding to the development requirements.

2. The method according to claim 1, characterized in that, The method further includes: Obtain a summary of the key parameters for each of the subtasks; Based on the partial context information and the key parameter summary corresponding to each subtask, a prompt word corresponding to the subtask is generated.

3. The method according to claim 1, characterized in that, The method further includes: Update the status information for each of the subtasks.

4. The method according to claim 1, characterized in that, Determining the execution order of the plurality of subtasks specifically includes: The execution order of the multiple subtasks is determined based on their dependencies and resource availability.

5. The method according to claim 1, characterized in that, The method further includes: Receive the status information of the subtask.

6. The method according to claim 5, characterized in that, The method further includes: Send the status information of the subtask.

7. The method according to claim 1, characterized in that, The method further includes: The priority and execution order of the multiple subtasks are dynamically adjusted based on the results of the multiple subtasks.

8. The method according to claim 3, characterized in that, The status information includes: pending status, running status, failed status, paused status, and completed status.

9. An apparatus for processing programming tasks, characterized in that, The device includes: The acquisition unit is used to acquire the user's development requirements, wherein the development requirements carry context information; The first determining unit is used to perform workflow intent recognition on the development requirements and determine the task type of the development requirements. The second determining unit is used to break down the development requirements according to the task type, determine multiple sub-tasks and a portion of the context information corresponding to each sub-task, wherein the portion of the context information corresponding to each sub-task includes a complete requirement description, a list of related files and execution parameters for the sub-task; The third determining unit is used to determine the execution order of the plurality of subtasks, wherein some of the plurality of subtasks are executed in parallel; The generation unit is configured to execute the plurality of subtasks in the execution order and generate the results of the plurality of subtasks; The generation unit is further configured to aggregate the results of the multiple subtasks to generate the target result corresponding to the development requirement.

10. A system for processing programming tasks, characterized in that, The system includes: The module includes a requirement acquisition module, an intent recognition engine, a task decomposition engine, a parallel scheduler, an execution engine, and an aggregation module. The system comprises the following components: a requirement acquisition module for acquiring user development requirements, wherein the development requirements carry contextual information; an intent recognition engine for performing workflow intent recognition on the development requirements to determine the task type of the development requirements; a task decomposition engine for splitting the development requirements according to the task type to determine multiple subtasks and a portion of the contextual information corresponding to each subtask, wherein the portion of the contextual information corresponding to each subtask includes a complete requirement description, a list of related files, and execution parameters for the subtask; a parallel scheduler for determining the execution order of the multiple subtasks, wherein some of the multiple subtasks are executed in parallel; an execution engine for executing the multiple subtasks according to the execution order to generate multiple subtask results; and an aggregation module for aggregating the multiple subtask results to generate the target result corresponding to the development requirements.

11. An electronic device comprising a memory and a processor, characterized in that, The memory is used to store one or more computer program instructions, wherein the one or more computer program instructions are executed by the processor to implement the method as described in any one of claims 1-8.

12. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, implements the method as described in any one of claims 1-8.

Images