Automatic breakpoint continuous running business process scheduling system based on multi-way tree

Abstract

The invention relates to the technical field of business process scheduling, and discloses a multi-way tree-based automatic breakpoint continuous running business process scheduling system, which comprises a multi-way tree scheduling module and a multi-way tree node actuator module which interact with a state bus through an instruction, the multi-way tree scheduling module constructs a process model based on a multi-way tree structure, takes a root node as an entrance, and realizes multi-branch process circulation by associating child nodes through mutually exclusive execution conditions with priorities; a built-in node monitor monitors an execution state, and a re-execution is automatically triggered when the node is interrupted; the multi-way tree node executor module decouples scheduling and service execution through a process engine adapter, and a node executor subscribes to an instruction and feeds back a result. According to the scheme, flexible scheduling, automatic breakpoint continuous running and low-coupling operation and maintenance of the business process can be realized, the method is adaptive to complex and changeable business scenes, and the process execution reliability and the operation and maintenance efficiency are improved.

Description

Technical Field

[0001] This invention relates to the field of business process scheduling technology, specifically to an automatic breakpoint resume business process scheduling system based on a multi-branch tree. Background Technology

[0002] With the deepening development of the digital economy, business processes in the financial sector are becoming increasingly complex, exhibiting significant characteristics such as multiple branches, multiple conditions, high concurrency, and long cycles. As the core supporting technology for business scheduling and automated execution, the flexibility, reliability, and efficiency of process engines have become key factors affecting the operational efficiency of enterprises. Traditional process engines have gradually exposed many technical shortcomings when dealing with complex business scenarios and high availability requirements, making it difficult to meet the development demands of modern business.

[0003] At the process modeling level, existing technologies mostly rely on fixed linear links or binary tree data structures to design process logic. Fixed linear links can only adapt to simple serial business scenarios and cannot support dynamic flow with multiple conditional branches. Although binary tree structures can realize binary branch judgment, the number of branches is limited. When the business requires multiple branches, it must be implemented through multi-level nested binary trees, resulting in redundant process models, complex condition matching logic, and a large-scale reconstruction of the model structure when business logic changes, leading to high adaptation costs and low iteration efficiency. This rigid modeling approach severely restricts the adaptability of process engines to complex business scenarios.

[0004] Regarding the ability to resume execution from a standby point, most existing workflow engines lack a robust automated recovery mechanism. When node execution is interrupted due to network fluctuations, server resource exhaustion, external dependency service interruptions, or data verification failures, manual intervention is required to investigate the cause of the interruption and restart the workflow. This not only prolongs business downtime and reduces execution efficiency but also easily leads to secondary problems such as data inconsistencies and duplicate workflow execution due to human error. Some workflow engines that support automatic retries adopt a one-size-fits-all strategy of "uniform retry interval + fixed number of retries," which wastes system computing resources and fails to solve the fundamental problem.

[0005] In terms of system architecture design, traditional process engines generally suffer from a high degree of coupling between scheduling logic and business execution logic. When business requirements change, execution logic is iterated or replaced, the core code of process scheduling needs to be modified, which not only increases the difficulty of system maintenance but also easily triggers a chain of failures, resulting in poor system scalability and insufficient stability.

[0006] Therefore, there is an urgent need for a process engine technology that can adapt to complex multi-branch business scenarios, achieve accurate and efficient automatic breakpoint resume, and has low coupling and high scalability characteristics, in order to solve the shortcomings of existing technologies and support the stable and efficient operation of modern complex businesses. Summary of the Invention

[0007] The present invention aims to provide an automatic breakpoint resume business process scheduling system based on multi-branch trees, so as to solve the problems of low reliability, poor process adaptability and high module coupling of traditional business process scheduling.

[0008] To achieve the above objectives, the present invention adopts the following technical solution: An automatic breakpoint resume business process scheduling system based on multi-branch trees includes: The system includes a multi-branch tree scheduling module and a multi-branch tree node executor module, which interact with each other via an instruction and a status bus. The multi-branch tree scheduling module constructs a process model based on the multi-branch tree data structure. The process model takes the root node as the process execution entry point. The root node can grow several child nodes downwards, and the child nodes can further grow several child nodes downwards, forming a multi-level multi-branch tree structure. Each child node is associated with its parent node through execution conditions. The execution conditions corresponding to all child nodes under the same parent node are mutually exclusive, and the priority of the execution conditions decreases from left to right. The multi-branch tree scheduling module initiates process execution from the root node, and matches the execution conditions from left to right according to the current process execution result. If a match is successful, it jumps to the corresponding child node for execution; if all conditions are not matched, the process execution terminates. The multi-branch tree scheduling module has a built-in node listener. The node listener monitors the execution status of nodes in real time during the execution of all nodes. When a node execution interruption is detected, the node is automatically triggered to re-execute. The multi-branch tree node executor module includes a process engine adapter and multiple node executors. The process engine adapter is used to decouple the multi-branch tree scheduling module from the node executors. The node executors subscribe to the node execution instructions sent by the multi-branch tree scheduling module through the instruction and status bus, execute the corresponding business logic, and send the execution results to the multi-branch tree scheduling module through the instruction and status bus.

[0009] The principles and advantages of this solution are as follows: In practical applications, the multi-branch tree structure enables flexible process modeling with multiple branches and conditions, solving the problem of insufficient adaptability of traditional fixed-link processes; automatic retries triggered by node listeners solve the problem of low efficiency in manual recovery after process interruption; interaction between the process engine adapter and the bus solves the problem of tight coupling and high maintenance costs between the scheduling module and the business execution module; at the same time, the priority matching rules of the multi-branch tree ensure efficient and orderly process flow, achieving flexible scheduling, reliable continuation, and loosely coupled operation and maintenance of the overall business process.

[0010] Preferably, as an improvement, the process model supports dynamic expansion, adapting to changes in business logic by adding or deleting child nodes, adjusting execution conditions and priorities.

[0011] Technical benefits: Without refactoring the core architecture of the process, it can quickly respond to the addition, modification or deletion of business logic, reduce the development cost and iteration cycle of process adaptation, and improve the system's adaptability to complex and ever-changing business scenarios.

[0012] Preferably, as an improvement, the multi-branch tree scheduling module further includes a process instance management unit, which records the execution trajectory of each process instance, including the execution time, execution result, interruption record and recovery status of each node.

[0013] Technical benefits: Facilitates full-chain traceability of process execution, enables maintenance personnel to quickly locate abnormal nodes and the root cause of interruptions, and reduces the difficulty of troubleshooting.

[0014] Preferably, as an improvement, the multi-branch tree scheduling module further includes an intelligent interruption cause identification unit and a differentiated recovery strategy unit; The intelligent interruption cause identification unit integrates a scene recognition engine, which classifies the interruption types of node execution by collecting system layer data, business layer data and historical execution data; the interruption types include temporary failure, insufficient resources, data anomaly and permanent failure; The differentiated recovery strategy unit works in conjunction with the intelligent interruption cause identification unit to execute corresponding recovery logic for different interruption types.

[0015] Technical benefits: It avoids the resource waste and inefficient recovery problems caused by traditional one-size-fits-all retries, achieves precise and intelligent handling of breakpoint resume, improves the success rate of resume under different interruption scenarios, and reduces the occupation of system resources by invalid retries.

[0016] Preferably, as an improvement, it also includes a hierarchical breakpoint context storage module and an incremental resume execution module; The hierarchical breakpoint context storage module adopts a three-level storage architecture: the core layer stores the input and output data of the process instance, using a dual storage mode of memory and persistent storage; the extension layer stores the node execution log, data verification results, and details of interruption reasons, using distributed file storage; and the association layer records the dependency graph between multi-way tree nodes. The incremental execution module enables differentiated execution based on hierarchical storage data and dependency graphs.

[0017] Technical benefits: It facilitates a balance between storage efficiency and loading speed of breakpoint data, reducing the resource overhead of full storage; incremental resumption avoids the repeated execution of completed nodes, significantly improving the resumption efficiency in long-process and multi-dependency scenarios, while also adapting to the precise resumption requirements after data changes.

[0018] Preferably, as an improvement, it also includes a circuit breaker protection module and the distributed lock control module; The circuit breaker protection module configures a maximum retry threshold for each node. When the retry reaches the threshold and still fails, the circuit breaker mechanism is triggered, the retry process of the node is terminated, the node is marked as retry failure, and a preset fallback strategy is executed. When the breakpoint resume is triggered, the distributed lock control module locks the combination identifier of the process instance ID and the current node path; before the resume starts, it checks whether the current state of the node is consistent with the stored state. If there is a state conflict, the current resume request is terminated.

[0019] Technical benefits: It helps prevent system resource exhaustion caused by infinite retries, and ensures system stability through circuit breaking mechanisms and fallback strategies; it avoids running conflicts and data inconsistencies in distributed or multi-threaded scenarios, and improves the reliability of breakpoint resumption and data security.

[0020] Preferably, as an improvement, it also includes a breakpoint preloading module and a resource preheating module; The breakpoint preloading module works in conjunction with the node listener. When a node execution interruption is detected, the breakpoint context preloading operation is triggered synchronously. Based on the core layer, the input and output data of the currently interrupted node and the basic configuration information of subsequent associated nodes are loaded and cached in the local high-speed storage area. The node path to be executed next is predicted through the dependency graph, and the execution condition rules of the path are parsed. The resource preheating module works in conjunction with the differentiated recovery strategy unit to preheat resources based on different interruption types; The preloading and preheating status are synchronized to the multi-branch tree scheduling module in real time. When the continuation is triggered, the preloaded data and the preheated execution environment are directly reused.

[0021] Technical benefits: It facilitates the elimination of data loading and environment initialization time during resume execution, significantly improving the startup speed and execution efficiency of resume execution, and is suitable for business scenarios with high requirements for response timeliness.

[0022] Preferably, as an improvement, the instruction and status bus includes an instruction transmission channel and a status feedback channel. The instruction transmission channel is used by the multi-branch tree scheduling module to send execution instructions to the node executor, and the status feedback channel is used by the node executor to provide feedback on the execution result and execution status to the multi-branch tree scheduling module.

[0023] Technical benefits: It facilitates the separate transmission of command sending and status feedback, avoids information delays or loss caused by channel congestion, improves the real-time performance and stability of inter-module interaction, and ensures efficient collaboration in process scheduling.

[0024] Preferably, as an improvement, the process engine adapter provides a standardized interface protocol, through which the node executor establishes a connection with the instruction and status bus to realize instruction subscription and status transmission.

[0025] Technical benefits: It facilitates lowering the access threshold for node executors, supports rapid integration of executors with different technology stacks and business types; at the same time, it enables plug-and-play executors, and when business execution logic is iterated or replaced, there is no need to modify the core code of process scheduling, thus improving system scalability and ease of maintenance.

[0026] Preferably, as an improvement, the multi-branch tree scheduling module synchronizes the node execution status to the process model in real time during node execution, and displays the real-time execution status of the multi-branch tree process through a visual interface, including the currently executing node, completed nodes, pending nodes, and interrupted nodes.

[0027] Technical benefits: It enables intuitive presentation of process execution status, facilitating real-time monitoring of process operation status by maintenance personnel, quick identification and intervention of interruption points, and improving the visualization level and response efficiency of process operation and maintenance. Attached Figure Description

[0028] Figure 1 This is a schematic diagram of the process model of the multi-branch tree data structure according to an embodiment of the present invention; Figure 2 This is a schematic diagram of the workflow of the process engine and process executor bus in an embodiment of the present invention. Detailed Implementation

[0029] The following detailed description illustrates the specific implementation method: The basic implementation examples are as follows: Figure 1 Appendix Figure 2 As shown: The automatic breakpoint resume business process scheduling system based on multi-branch trees includes a multi-branch tree scheduling module and a multi-branch tree node executor module. The multi-branch tree scheduling module and the multi-branch tree node executor module interact through an instruction and status bus.

[0030] The multi-branch tree scheduling module constructs a process model based on a multi-branch tree data structure. This model uses the root node as the entry point for process execution. The root node can grow several child nodes downwards, and these child nodes can further grow several more child nodes, forming a multi-level multi-branch tree structure. Each child node is associated with its parent node through execution conditions. Execution conditions for all child nodes under the same parent node are mutually exclusive, and the priority of execution conditions decreases from left to right. The process model supports dynamic expansion, adapting to changes in business logic by adding or deleting child nodes and adjusting execution conditions and priorities.

[0031] The multi-branch tree scheduling module initiates process execution from the root node. Based on the current process execution result, it matches the execution conditions from left to right. If a match is successful, it jumps to the corresponding child node for execution. If none of the conditions are matched, the process execution terminates.

[0032] The multi-branch tree scheduling module has a built-in node listener. The node listener monitors the execution status of nodes in real time during the execution of all nodes. When a node execution interruption is detected, the node is automatically triggered to re-execute.

[0033] The multi-branch tree scheduling module also includes a process instance management unit, which records the execution trajectory of each process instance, including the execution time, execution result, interruption record and recovery status of each node.

[0034] The multi-branch tree scheduling module also includes an intelligent interruption cause identification unit and a differentiated recovery strategy unit.

[0035] The intelligent interruption cause identification unit integrates a scene recognition engine, which classifies the types of node execution interruptions by collecting system-level data, business-level data, and historical execution data. System-level data includes network status, server resource utilization, and service health status; business-level data includes input / output data integrity, business rule verification results, and external dependency response status; and historical execution data includes node historical interruption records and retry success probability. Interruption types include temporary faults, insufficient resources, data anomalies, and permanent faults.

[0036] The differentiated recovery strategy unit works in conjunction with the intelligent interruption cause identification unit to execute corresponding recovery logic for different interruption types: When a temporary failure is identified, the node is re-executed using an immediate retry and exponential backoff mechanism. The first retry triggers an immediate retry, and subsequent retryes are performed at intervals of 2s, 4s, and 8s, with a maximum of 3 retries.

[0037] When resources are identified as insufficient, a temporary resource reservation request is sent to the resource scheduling center. At the same time, the task to be executed by the current node is added to the priority queue. Once the resources are released, the task will be automatically woken up for execution, and the waiting status will be synchronized to the multi-branch tree scheduling module in real time.

[0038] When a data anomaly is identified, the process is paused and retried. The current process context data (including input data, execution progress, and node status) is recorded, an alarm notification is triggered, and an interface is provided to support manual correction of the data before resuming the process precisely. Only the current abnormal node and subsequent processes are executed.

[0039] When a permanent failure is identified, the current process branch is terminated, the node is marked as having failed and feedback is sent to the parent node, which then triggers subsequent processing according to the preset branch jump rules, while retaining the failure log.

[0040] It also includes a hierarchical breakpoint context storage module and an incremental resume execution module.

[0041] The hierarchical breakpoint context storage module adopts a three-level storage architecture: the core layer stores the process instance ID, the current node path identifier, the node execution status, and core input / output data affecting subsequent processes, using a dual storage mode of memory and persistent storage. Memory is used for fast reading, while persistent storage prevents data loss in case of system crashes. The extension layer stores node execution logs, data verification results, and details of interruption reasons, using distributed file storage and loading on demand. The association layer records the dependency graph between multi-way tree nodes, clearly defining the dependency relationships of each node on the output data of its predecessor node.

[0042] The incremental resume execution module implements differentiated resume execution based on hierarchical storage data and dependency graphs. For example, in a normal resume execution scenario: execution resumes from the interrupted node, directly reusing the output data of the preceding nodes stored in the core layer, skipping completed nodes. In a data change resume execution scenario: the dependency graph identifies the range of nodes affected by data changes, only re-executing nodes within that range, while reusing the original execution results for the remaining nodes. Context management: a configurable context storage validity period is set; expired context storage data is automatically cleaned up, and a manual renewal interface is also provided.

[0043] It also includes a circuit breaker protection module, a distributed lock control module, and a data consistency verification module.

[0044] The circuit breaker protection module configures an adjustable maximum retry threshold for each node. When the retry reaches the threshold and still fails, the circuit breaker mechanism is triggered, the node's retry process is terminated, it is marked as a retry failure, and a preset fallback strategy is executed. The fallback strategy includes switching to a backup node or manual intervention notification.

[0045] When a breakpoint resume is triggered, the distributed lock control module locks the combination identifier of the process instance ID and the current node path to prevent the same node from being repeatedly triggered for resume in multi-threaded or distributed deployment scenarios. Before the resume starts, it checks whether the current state of the node is consistent with the storage state. If there is a state conflict, the current resume request is terminated.

[0046] The data consistency verification module performs dual verification logic: pre-run verification and post-run verification. Pre-run verification compares the current node's input data with the input data stored at the breakpoint to determine the legality of the data change. If the change is legal, the process continues; if the change is illegal, an alarm is triggered. Post-run verification checks whether the node's output data conforms to the business rules. If it does not conform, it automatically rolls back to the state stored at the breakpoint.

[0047] It also includes a breakpoint preloading module and a resource preheating module.

[0048] The breakpoint preloading module works in conjunction with the node listener. When a node execution interruption is detected, a breakpoint context preloading operation is triggered synchronously. Based on the core layer data of the hierarchical breakpoint context storage module, the input parameters of the currently interrupted node, the output data of the dependent preceding nodes, and the basic configuration information of the subsequent associated nodes are preloaded and cached in the local high-speed storage area. At the same time, the node paths that may be executed later are predicted through the dependency graph, and the execution condition rules of the path are parsed in advance to avoid the overhead of repeated parsing when resuming execution.

[0049] The resource preheating module works in conjunction with the differentiated recovery strategy unit. For temporary fault types, during the interval of triggering exponential backoff retry, it initiates a lightweight resource locking request to the resource scheduling center to reserve core resources such as CPU, memory, and network connection required for the current node to execute, ensuring that resources are available immediately during retry. For resource shortage types, while the node task is waiting in the priority queue, the resource preheating process is started to initialize the execution environment in advance, such as loading business dependent libraries, establishing a database connection pool, and initializing cache instances. After the resources are released, the node can be started directly, omitting the time spent on environment initialization.

[0050] The preloading and preheating status are synchronized to the multi-branch tree scheduling module in real time. When the continuation is triggered, the preloaded data and the preheated execution environment can be reused directly without re-executing the data loading and environment initialization steps.

[0051] During node execution, the multi-branch tree scheduling module synchronizes the node execution status to the process model in real time and displays the real-time execution status of the multi-branch tree process through a visual interface, including the currently executing node, completed nodes, pending nodes, and interrupted nodes.

[0052] The multi-branch tree node executor module includes a process engine adapter and multiple node executors. The process engine adapter is used to decouple the multi-branch tree scheduling module from the node executors and isolate the process engine from the business execution logic. The node executors subscribe to the node execution instructions sent by the multi-branch tree scheduling module through the instruction and status bus, execute the corresponding business logic, and send the execution results to the multi-branch tree scheduling module through the instruction and status bus.

[0053] The node executors are independent of each other and correspond to different business logic. Adding or replacing node executors can be supported without affecting the operation of the multi-branch tree scheduling module.

[0054] The process engine adapter provides a standardized interface protocol, through which the node executor establishes a connection with the instruction and status bus to realize instruction subscription and status transmission.

[0055] The instruction and status bus includes an instruction transmission channel and a status feedback channel. The instruction transmission channel is used by the multi-branch tree scheduling module to send execution instructions to the node executor, and the status feedback channel is used by the node executor to provide feedback on the execution result and execution status to the multi-branch tree scheduling module.

[0056] The above descriptions are merely embodiments of the present invention, and common knowledge such as specific technical solutions and / or characteristics are not described in detail here. It should be noted that those skilled in the art can make various modifications and improvements without departing from the technical solutions of the present invention, and these should also be considered within the scope of protection of the present invention. These modifications and improvements will not affect the effectiveness of the implementation of the present invention or the practicality of the patent. The scope of protection claimed in this application should be determined by the content of its claims, and the specific embodiments described in the specification can be used to interpret the content of the claims.

Claims

1. An automatic breakpoint resume business process scheduling system based on multi-branch trees, characterized in that, include: The system includes a multi-branch tree scheduling module and a multi-branch tree node executor module, which interact with each other via an instruction and a status bus. The multi-branch tree scheduling module constructs a process model based on the multi-branch tree data structure. The process model takes the root node as the process execution entry point. The root node can grow several child nodes downwards, and the child nodes can further grow several child nodes downwards, forming a multi-level multi-branch tree structure. Each child node is associated with its parent node through execution conditions. The execution conditions corresponding to all child nodes under the same parent node are mutually exclusive, and the priority of the execution conditions decreases from left to right. The multi-branch tree scheduling module initiates process execution from the root node, and matches the execution conditions from left to right according to the current process execution result. If a match is successful, it jumps to the corresponding child node for execution; if all conditions are not matched, the process execution terminates. The multi-branch tree scheduling module has a built-in node listener. The node listener monitors the execution status of nodes in real time during the execution of all nodes. When a node execution interruption is detected, the node is automatically triggered to re-execute. The multi-branch tree node executor module includes a process engine adapter and multiple node executors. The process engine adapter is used to decouple the multi-branch tree scheduling module from the node executors. The node executors subscribe to the node execution instructions sent by the multi-branch tree scheduling module through the instruction and status bus, execute the corresponding business logic, and send the execution results to the multi-branch tree scheduling module through the instruction and status bus.

2. The automatic breakpoint resume business process scheduling system based on multi-branch trees according to claim 1, characterized in that: The process model supports dynamic expansion, adapting to changes in business logic by adding or deleting sub-nodes and adjusting execution conditions and priorities.

3. The automatic breakpoint resume business process scheduling system based on multi-branch trees according to claim 1, characterized in that: The multi-branch tree scheduling module also includes a process instance management unit, which records the execution trajectory of each process instance, including the execution time, execution result, interruption record and recovery status of each node.

4. The automatic breakpoint resume business process scheduling system based on multi-branch trees according to claim 1, characterized in that: The multi-branch tree scheduling module also includes an intelligent interruption cause identification unit and a differentiated recovery strategy unit; The intelligent interruption cause identification unit integrates a scene recognition engine, which classifies the interruption types of node execution by collecting system layer data, business layer data and historical execution data; the interruption types include temporary failure, insufficient resources, data anomaly and permanent failure; The differentiated recovery strategy unit works in conjunction with the intelligent interruption cause identification unit to execute corresponding recovery logic for different interruption types.

5. The automatic breakpoint resume business process scheduling system based on multi-branch trees according to claim 1, characterized in that: It also includes a hierarchical breakpoint context storage module and an incremental resume execution module; The hierarchical breakpoint context storage module adopts a three-level storage architecture: the core layer stores the input and output data of the process instance, and adopts a dual storage mode of memory and persistent storage; The extension layer stores node execution logs, data verification results, and details of interruption reasons, using distributed file storage; the association layer records the dependency graph between multi-way tree nodes. The incremental execution module enables differentiated execution based on hierarchical storage data and dependency graphs.

6. The automatic breakpoint resume business process scheduling system based on multi-branch trees according to claim 1, characterized in that: It also includes a circuit breaker protection module and the distributed lock control module; The circuit breaker protection module configures a maximum retry threshold for each node. When the retry reaches the threshold and still fails, the circuit breaker mechanism is triggered, the retry process of the node is terminated, the node is marked as retry failure, and a preset fallback strategy is executed. When the breakpoint resume is triggered, the distributed lock control module locks the combination identifier of the process instance ID and the current node path; before the resume starts, it checks whether the current state of the node is consistent with the stored state. If there is a state conflict, the current resume request is terminated.

7. The automatic breakpoint resume business process scheduling system based on multi-branch trees according to claim 5, characterized in that: It also includes a breakpoint preloading module and a resource preheating module; The breakpoint preloading module works in conjunction with the node listener. When a node execution interruption is detected, the breakpoint context preloading operation is triggered synchronously. Based on the core layer, the input and output data of the currently interrupted node and the basic configuration information of subsequent associated nodes are loaded and cached in the local high-speed storage area. The node path to be executed next is predicted through the dependency graph, and the execution condition rules of the path are parsed. The resource preheating module works in conjunction with the differentiated recovery strategy unit to preheat resources based on different interruption types; The preloading and preheating status are synchronized to the multi-branch tree scheduling module in real time. When the continuation is triggered, the preloaded data and the preheated execution environment are directly reused.

8. The automatic breakpoint resume business process scheduling system based on multi-branch trees according to claim 1, characterized in that: The instruction and status bus includes an instruction transmission channel and a status feedback channel. The instruction transmission channel is used by the multi-branch tree scheduling module to send execution instructions to the node executor, and the status feedback channel is used by the node executor to provide feedback on the execution result and execution status to the multi-branch tree scheduling module.

9. The automatic breakpoint resume business process scheduling system based on multi-branch trees according to claim 1, characterized in that: The process engine adapter provides a standardized interface protocol, through which the node executor establishes a connection with the instruction and status bus to realize instruction subscription and status transmission.

10. The automatic breakpoint resume business process scheduling system based on multi-branch trees according to claim 1, characterized in that: During node execution, the multi-branch tree scheduling module synchronizes the node execution status to the process model in real time and displays the real-time execution status of the multi-branch tree process through a visual interface, including the currently executing node, completed nodes, pending nodes, and interrupted nodes.

Images