A semantically fused graphical software development management method and system

Abstract

The present invention provides a semantically fused graphical software development management method and system, which obtains a multi-user interactive behavior data stream including an operation trajectory sequence and an interface control trigger sequence; constructs a dynamic semantic graph according to the spatiotemporal correlation pattern of the operation trajectory sequences and the interface control trigger sequence of different users; inputs the hierarchical mapping relationship in the dynamic semantic graph into a preset edge computing node to generate a real-time computing power allocation plan that matches the logical dependency chain in the dynamic semantic graph; parses the control trigger timestamp and control type mapping relationship in the spatiotemporal correlation pattern to generate an interface control rendering priority queue; synchronously regulates the interface control rendering priority queue and the operation instruction response sequence corresponding to the logical dependency chain to generate a graphical software development process synchronization instruction set; the present invention integrates the hierarchy and dependency chain to form a dynamic semantic graph, constructs a hierarchical operation structure and logical dependency relationship, and ensures the efficiency and consistency of the graphical development process.

Description

Technical Field

[0001] The present invention relates to the technical field of software development management, and in particular to a semantically fused graphical software development management method and system. Background Art

[0002] With the widespread application of multi-user real-time collaboration in graphical software development, how to efficiently and accurately understand the operational collaboration intentions of different users and achieve dynamic coordination of interfaces and logic has become a key technical requirement for improving development efficiency and user experience.

[0003] The current mainstream solution is graphical collaborative management based on behavior sequence clustering and centralized resource scheduling. By collecting the operation behavior logs of multiple users and using the time series clustering algorithm to identify high-frequency collaboration patterns, a global operation dependency graph is constructed on this basis. The system aggregates all user operation requests to the central server for unified resource scheduling and rendering priority sorting to ensure consistency between interface updates and function execution.

[0004] Existing solutions have some inherent flaws, including high response delays in the central node processing stage, which makes it difficult to meet real-time requirements; static resource allocation strategies cannot dynamically adjust computing power distribution based on user operation intentions, which can easily cause some nodes to be overloaded while other nodes are idle; and the modeling of operation dependencies lacks a semantic understanding, resulting in inconsistencies or conflicts between interface rendering and command execution. Summary of the Invention

[0005] The present invention provides a semantically integrated graphical software development management method and system to solve the problems in the prior art, such as high response delay in the central node processing stage, which makes it difficult to meet real-time requirements; static resource allocation strategies cannot dynamically adjust the computing power distribution according to the user's operation intentions, which easily causes some nodes to be overloaded while other nodes are idle; and the modeling of operation dependencies lacks a semantic level understanding, resulting in inconsistencies or conflicts between interface rendering and instruction execution.

[0006] In a first aspect, the present invention provides a semantically fused graphical software development management method, comprising:

[0007] Obtain multi-user interaction behavior data streams including operation trajectory sequences and interface control triggering timings;

[0008] Constructing a dynamic semantic graph reflecting user collaboration intentions based on the spatiotemporal correlation pattern between the operation trajectory sequences of different users in the multi-user interaction behavior data stream and the triggering timing of the interface controls. The dynamic semantic graph includes a hierarchical mapping relationship of visual control nodes and a logical dependency chain of cross-user operation instructions.

[0009] Inputting the hierarchical mapping relationship into a preset edge computing node, and generating a real-time computing power allocation plan that matches the logical dependency chain according to the distributed computing power allocation strategy within the preset edge computing node;

[0010] Based on a preset rendering priority rule, the mapping relationship between the control trigger timestamp and the control type in the spatiotemporal association pattern is parsed to generate an interface control rendering priority queue;

[0011] Based on the real-time computing power allocation scheme, the interface control rendering priority queue and the operation instruction response sequence corresponding to the logical dependency chain are synchronously regulated to generate a multi-user collaborative intention-driven graphical software development process synchronization instruction set for graphical software development management.

[0012] Optionally, a dynamic semantic graph reflecting the user collaboration intention is constructed based on the spatiotemporal correlation pattern between the operation trajectory sequences of different users in the multi-user interaction behavior data stream and the triggering timing of the interface controls. The dynamic semantic graph includes a hierarchical mapping relationship of visual control nodes and a logical dependency chain of cross-user operation instructions, including:

[0013] Extracting spatial position offsets of visual controls of a graphical software development tool from operation trajectory sequences of different users in the multi-user interaction behavior data stream;

[0014] Extracting the interval durations between adjacent trigger operations from the interface control trigger sequence, and determining the collaborative focus area and operation continuity identifier of the multi-user interaction behavior data stream based on the corresponding relationship between the spatial position offset and the interval durations;

[0015] Counting the triggering frequencies of the function attribute association identifiers of all the visual controls in the collaboration focus area, and determining the visual control corresponding to the function attribute association identifier with the highest triggering frequency as the core function control;

[0016] The core function control is used as the root node of each function attribute association identifier to perform hierarchical merging to generate a hierarchical mapping relationship;

[0017] The earliest triggered control operation event in the operation continuity identifier is used as the starting node, and subsequent control operation events are bound as child nodes of the starting node in the triggering order to generate a logical dependency chain across user operation instructions;

[0018] The hierarchical mapping relationship is combined with the logical dependency chain to generate a dynamic semantic graph.

[0019] Optionally, counting the triggering frequencies of the function attribute association identifiers of all the visual controls in the collaboration focus area, and determining the visual control corresponding to the function attribute association identifier with the highest triggering frequency as the core function control, includes:

[0020] Extracting the functional attribute association identifier and the corresponding trigger time set of each visual control within the preset time window from the collaboration focus area, and generating a mapping relationship between the functional attribute association identifier and the trigger time set;

[0021] Merging all triggering moments under the same functional attribute association identifier into a global triggering sequence, counting the number of triggering times of each functional attribute association identifier in the global triggering sequence, and calculating the triggering frequency of each functional attribute association identifier by the ratio of the number of triggering times to the length of the preset time window;

[0022] Extracting the last triggering time of each function attribute association identifier from the global triggering sequence, and generating a real-time activity factor according to the interval between the last triggering time and the current time;

[0023] Multiplying the triggered frequency by the real-time activity factor to generate a comprehensive trigger weight value for each functional attribute association identifier;

[0024] The visual control corresponding to the functional attribute association identifier with the highest comprehensive trigger weight value is determined as the core functional control.

[0025] Optionally, the hierarchical mapping relationship is input into a preset edge computing node, and a real-time computing power allocation scheme matching the logical dependency chain is generated according to a distributed computing power allocation strategy within the preset edge computing node, including:

[0026] Parsing the hierarchical depth of the visual control node in the hierarchical mapping relationship and the dependency path length of the logical operation instruction in the logical dependency chain;

[0027] Matching a corresponding computing power allocation rule from the distributed computing power allocation strategy according to a proportional relationship between the hierarchical depth and the dependency path length;

[0028] Based on the hierarchical computing power weight coefficient and the path length priority threshold in the computing power allocation rule, the proportion of computing power resources required by the visualization control node at each level is calculated to generate a hierarchical computing power allocation base;

[0029] A real-time computing power allocation plan for the execution order of the logical operation instructions is generated based on the hierarchical computing power allocation base and the real-time available computing power capacity of the preset edge computing node.

[0030] Optionally, based on a preset rendering priority rule, the mapping relationship between the control trigger timestamp and the control type in the spatiotemporal association pattern is parsed to generate an interface control rendering priority queue, including:

[0031] Extracting a set of visual controls having a collaborative operation relationship from the control type mapping relationship to generate a functional association group;

[0032] Extracting the first triggering moment of each visualization control and the interval between adjacent triggering moments from the control triggering timestamp;

[0033] Allocating an initial rendering priority level to each visual control in the same function association group according to the order of the first triggering moments, generating an assigned function association group, wherein the visual control is converted into an assigned visual control;

[0034] Based on a comparison result of the interval duration and a preset duration urgency threshold, adjusting the initial rendering priority level of the allocated visual control to generate a priority ranking of the allocated visual control;

[0035] The priority sorting is performed to arrange each of the assigned function association groups in a global order of the first triggering moment to generate an interface control rendering priority queue.

[0036] In a second aspect, the present invention provides a semantically fused graphical software development and management system, comprising:

[0037] An acquisition module is used to obtain a multi-user interaction behavior data stream including an operation trajectory sequence and an interface control triggering sequence;

[0038] A construction module is used to construct a dynamic semantic graph reflecting the user's collaborative intention based on the spatiotemporal correlation pattern between the operation trajectory sequences of different users in the multi-user interaction behavior data stream and the triggering timing of the interface controls. The dynamic semantic graph includes a hierarchical mapping relationship of visual control nodes and a logical dependency chain across user operation instructions;

[0039] An input module, configured to input the hierarchical mapping relationship into a preset edge computing node, and generate a real-time computing power allocation plan that matches the logical dependency chain according to a distributed computing power allocation strategy within the preset edge computing node;

[0040] A parsing module, configured to parse the mapping relationship between the control trigger timestamp and the control type in the spatiotemporal association pattern based on a preset rendering priority rule to generate an interface control rendering priority queue;

[0041] A control module is used to synchronously control the interface control rendering priority queue and the operation instruction response sequence corresponding to the logical dependency chain based on the real-time computing power allocation plan, and generate a multi-user collaborative intention-driven graphical software development process synchronization instruction set to perform graphical software development management.

[0042] In a third aspect, the present invention provides a computing device comprising a processor and a memory, wherein the memory stores a computer program, and the processor is configured to run the computer program to execute a semantically fused graphical software development management method as described in any one of the first aspects.

[0043] In a fourth aspect, the present invention provides a computer storage medium having computer program instructions stored thereon, wherein the computer program instructions, when executed by a processor, implement a semantically fused graphical software development management method as described in any one of the first aspects.

[0044] In the present invention, a multi-user interaction behavior data stream including an operation trajectory sequence and an interface control trigger sequence is obtained; a dynamic semantic graph reflecting the user collaboration intention is constructed based on the spatiotemporal correlation pattern between the operation trajectory sequences of different users in the multi-user interaction behavior data stream and the interface control trigger sequence, and the dynamic semantic graph includes a hierarchical mapping relationship of visual control nodes and a logical dependency chain of cross-user operation instructions; the hierarchical mapping relationship is input into a preset edge computing node, and a real-time computing power allocation scheme matching the logical dependency chain is generated based on the distributed computing power allocation strategy within the preset edge computing node; based on a preset rendering priority rule, the mapping relationship between the control trigger timestamp and the control type in the spatiotemporal correlation pattern is parsed to generate an interface control rendering priority queue; based on the real-time computing power allocation scheme, the interface control rendering priority queue and the operation instruction response sequence corresponding to the logical dependency chain are synchronously regulated to generate a multi-user collaboration intention-driven graphical software development process synchronization instruction set for graphical software development management.

[0045] The technical solution provided by the present invention provides a multi-dimensional collaborative behavior data foundation by comprehensively capturing the operation trajectories and control triggering timings of multiple users, solving the problem of operation intention analysis deviation caused by the single data in traditional methods; it analyzes user collaboration intentions through spatiotemporal correlation patterns, generates a structured graph including hierarchical mapping relationships and logical dependency chains, and solves the technical barriers of multi-user operation semantic conflicts and unclear dependency relationships; dynamically matches computing power resource allocation strategies based on hierarchical mapping relationships, solves the problems of computing power waste and high-priority task delays caused by static resource allocation, and improves the collaborative response efficiency of edge computing nodes; optimizes interface rendering resource allocation through priority analysis of control trigger timing and type mapping, and solves the problems of interface freeze and rendering conflicts caused by concurrent operations of multiple users; integrates computing power allocation and operation instruction sequences to realize real-time synchronization of development processes driven by multi-user collaborative intentions, and solves the technical defects of the disconnection between operation response and resource scheduling in traditional methods. Among them, by extracting the spatial offset and interval duration from the user operation trajectory and trigger sequence, the collaborative focus area and operation continuity identification are determined; by counting the triggering frequency of the control function attributes in the focus area, the core function control is determined as the root node to construct a hierarchical mapping relationship; based on the operation continuity identification, a logical dependency chain is generated, and the hierarchy and dependency chain are integrated to form a dynamic semantic graph, thereby constructing a hierarchical operation structure and logical dependency relationship, ensuring the efficiency and consistency of the graphical development process.

[0046] These and other aspects of the present invention will become more readily apparent from the following description of the embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following is a brief introduction to the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0048] Figure 1 A flowchart of a semantically fused graphical software development management method provided by an embodiment of the present invention;

[0049] Figure 2 A schematic diagram of the structure of a semantically fused graphical software development and management system provided by an embodiment of the present invention;

[0050] Figure 3 A schematic diagram of the structure of a computing device provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0051] In order to enable those skilled in the art to better understand the solutions of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention.

[0052] In some of the processes described in the specification and claims of the present invention and the above-mentioned figures, multiple operations that appear in a specific order are included, but it should be clearly understood that these operations may not be executed in the order in which they appear in this article or may be executed in parallel. The serial numbers of the operations, such as 101, 102, etc., are only used to distinguish between different operations, and the serial numbers themselves do not represent any execution order. In addition, these processes may include more or fewer operations, and these operations may be executed in sequence or in parallel. It should be noted that the descriptions of "first", "second", etc. in this article are used to distinguish different messages, devices, modules, etc., and do not represent the order of precedence, nor do they limit "first" and "second" to be different types.

[0053] Aiming at the complex technical problems such as conflicting operation intentions, rigid computing power allocation and interface synchronization delay in graphical software development under multi-user real-time collaboration scenarios, traditional methods lack spatiotemporal correlation analysis of multi-source operation data and dynamic resource coordination mechanism, resulting in low collaboration efficiency and broken development process. The present invention breaks through the technical bottleneck through the following paths: First, the operation trajectory sequence and control trigger timing are integrated to construct a dynamic semantic graph, analyze the correlation pattern of multi-user operations in the spatiotemporal dimension, and accurately identify the collaborative focus area and core functional controls; secondly, based on the distributed computing power strategy of edge computing nodes, the hierarchical control structure and operation dependency chain are dynamically mapped to the real-time computing power allocation plan to realize intention-driven elastic resource scheduling; at the same time, the rendering priority queue is generated in combination with the control type and trigger timing, and the computing power allocation and instruction response sequence are integrated through the cross-layer synchronization control mechanism, finally forming a development process instruction set that seamlessly connects the multi-user collaboration intentions.

[0054] It solves the core defects of existing technologies, such as lack of semantic fusion and disconnection between resource allocation and operation logic, and significantly improves the real-time performance and interface response consistency of multi-user collaborative development.

[0055] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without making any creative efforts shall fall within the scope of protection of the present invention.

[0056] Figure 1 A flowchart of a semantically fused graphical software development management method is provided for an embodiment of the present invention, such as Figure 1 As shown, the method includes:

[0057] Step 101: Acquire a multi-user interaction behavior data stream including an operation trajectory sequence and an interface control triggering sequence.

[0058] In this step, the operation trajectory sequence refers to the set of continuous spatial coordinate change paths generated when the user drags, clicks, and performs other operations on the visual controls in the graphical development tool through input devices; the interface control trigger timing refers to the sequence of time points when each visual control is activated by the user, including the first triggering moment and the time interval between adjacent triggering operations; the multi-user interaction behavior data stream refers to the spatiotemporal dimension data set formed by integrating the operation trajectory sequences and interface control trigger timings of multiple users, which is used for collaborative intention analysis.

[0059] In an embodiment of the present invention, the operation trajectory sequences and interface control triggering timings of multiple users are first collected in real time through the user interaction interface of a graphical development tool. The operation trajectory sequences record the spatial coordinate change paths of users performing operations such as dragging and clicking on visual controls. Secondly, the operation trajectory sequences of different users and the interface control triggering timings are time-aligned and spatially correlated. Finally, a multi-user interaction behavior data stream containing spatiotemporal dimensions is formed to serve as the original input for subsequent processing.

[0060] Step 102: Based on the spatiotemporal correlation pattern between the operation trajectory sequences of different users in the multi-user interaction behavior data stream and the triggering timing of the interface controls, a dynamic semantic graph reflecting the user collaboration intention is constructed. The dynamic semantic graph includes a hierarchical mapping relationship of visual control nodes and a logical dependency chain across user operation instructions.

[0061] In this step, the spatiotemporal association pattern refers to the multi-user collaborative behavior characteristics identified by analyzing the correspondence between the spatial distribution of operation trajectories and the temporal continuity of trigger sequences; the dynamic semantic graph refers to a structured graph that reflects the user's collaborative intention, including the hierarchical tree relationship of visual control nodes and the sequential dependency chain of cross-user operation instructions; the visual control node refers to the logical mapping entity of the interactive interface elements in the graphical development tool in the semantic graph; the hierarchical mapping relationship refers to a tree structure formed by hierarchically connecting other controls with the core function control as the root node according to functional relevance; cross-user operation instructions refer to the instruction sequence formed by multiple users operating the same control or related controls at different time points; the logical dependency chain refers to the instruction execution sequence chain generated based on the operation continuity identifier, reflecting the sequential dependency relationship of operation events.

[0062] In an embodiment of the present invention, first, a spatial clustering analysis is performed on the operation trajectory sequence in the multi-user interaction behavior data stream to extract the distribution characteristics of user operation hot spots, and at the same time, the time interval statistics of the interface control trigger sequence are performed to identify the high-frequency operation period; secondly, the spatial distribution of the operation trajectory is matched with the time continuity of the trigger sequence through the spatiotemporal association pattern algorithm to determine the collaborative focus area and the operation consistency identifier; then, based on the statistical results of the control function attribute association identifier within the collaborative focus area, a hierarchical mapping relationship with the core function control as the root node is constructed, and a logical dependency chain of cross-user operation instructions is generated through the operation consistency identifier; finally, the hierarchical mapping relationship and the logical dependency chain are combined into a dynamic semantic graph to form a structured expression of the user's collaborative intention.

[0063] Step 103: Input the hierarchical mapping relationship into a preset edge computing node, and generate a real-time computing power allocation plan that matches the logical dependency chain based on the distributed computing power allocation strategy within the preset edge computing node.

[0064] In this step, the preset edge computing node refers to the distributed computing unit deployed in the development environment, with built-in resource scheduling rules for real-time computing power allocation; the distributed computing power allocation strategy refers to a set of rules for dynamically allocating computing resources based on the control hierarchy and instruction dependencies, including hierarchical weight coefficients and path priority thresholds; the real-time computing power allocation plan that matches the logical dependency chain refers to a plan for dynamically allocating computing power resources according to the urgency and execution order of instructions in the logical dependency chain.

[0065] In an embodiment of the present invention, the hierarchical mapping relationship in the dynamic semantic graph is first input into the preset edge computing node; secondly, the computing power resources are proportionally allocated according to the hierarchical depth of the visualization control node and the complexity of the logical dependency chain; then, the computing power allocation ratio is dynamically adjusted according to the execution order and dependency relationship of the operation instructions in the logical dependency chain; finally, a real-time computing power allocation plan is generated that matches the high-priority instructions in the logical dependency chain.

[0066] Step 104: Based on a preset rendering priority rule, the mapping relationship between the control trigger timestamp and the control type in the spatiotemporal association pattern is parsed to generate an interface control rendering priority queue.

[0067] In this step, the preset rendering priority rule refers to the predefined rule for calculating the rendering priority based on the functional importance of the control type and the trigger time density; the control trigger timestamp refers to the data recording the precise time point when the visual control is activated by the user; the control type mapping relationship refers to the association relationship that classifies controls with the same or complementary functions into the same functional group; the parsing operation refers to the process of feature extraction and association analysis of the timestamp and type data in the spatiotemporal association pattern according to the preset rules; the interface control rendering priority queue refers to the execution sequence of the visual controls sorted from high to low by the rendering priority score.

[0068] In an embodiment of the present invention, first, based on a preset rendering priority rule, the control trigger timestamps in the spatiotemporal association pattern are divided into time windows, and the mapping relationship of the control types triggered in the same time period is extracted; secondly, the rendering priority score of each control is calculated according to the functional importance of the control type and the density of the trigger timestamps; then, the controls are sorted from high to low according to the priority score; finally, an interface control rendering priority queue is generated to ensure that high-frequency core controls are rendered first.

[0069] Step 105: Based on the real-time computing power allocation plan, the interface control rendering priority queue and the operation instruction response sequence corresponding to the logical dependency chain are synchronously regulated to generate a multi-user collaborative intention-driven graphical software development process synchronization instruction set for graphical software development management.

[0070] In this step, the operation instruction response sequence refers to the set of instructions to be executed generated according to the logical dependency chain, including the execution order and weight coefficients; the synchronous control operation refers to the resource matching process that integrates computing power allocation and instruction sequence, including the dynamic adjustment of immediate execution and delayed instructions; the graphical software development process synchronization instruction set refers to the final generated instruction execution plan that includes the intention of multi-user collaboration to ensure real-time synchronization of the development process.

[0071] In an embodiment of the present invention, first, the computing power allocation ratio in the real-time computing power allocation scheme is matched with the interface control rendering priority queue to determine the available rendering resource amount of each time slice unit; secondly, according to the execution order of the operation instruction response sequence corresponding to the logical dependency chain, the instructions are mapped to the corresponding time slice unit according to the weight coefficient; then, when the rendering resources are insufficient, the low-priority instructions are delayed and reallocated to the subsequent time slice unit; finally, the instruction execution plans of all time slice units are integrated through the cross-layer synchronization control mechanism to generate a graphical software development process synchronization instruction set containing immediate execution and delayed execution instructions.

[0072] The embodiment of the present invention analyzes the operation intentions of multiple users through a spatiotemporal correlation model, dynamically constructs a hierarchical control structure and a logical dependency chain, and combines the elastic resource allocation mechanism of edge computing nodes to systematically solve the complex technical barriers such as operation intention conflicts, rigid computing power allocation, and interface synchronization delays in traditional graphical collaborative development, significantly improving the real-time performance, resource utilization efficiency, and interface response consistency of multi-user collaboration.

[0073] The present invention provides a specific embodiment, step 102, constructing a dynamic semantic graph reflecting user collaboration intentions based on the spatiotemporal correlation pattern between the operation trajectory sequences of different users in the multi-user interaction behavior data stream and the triggering timing of the interface controls. The dynamic semantic graph includes a hierarchical mapping relationship of visual control nodes and a logical dependency chain of cross-user operation instructions. The specific steps include:

[0074] Step 201: extracting the spatial position offset of the visual control of the graphical software development tool from the operation trajectory sequence of different users in the multi-user interaction behavior data stream.

[0075] In this step, visual controls refer to user-interactive interface elements in graphical software development tools, including buttons, input boxes, flowchart nodes, etc., which are components used to implement specific functional logic; spatial position offset refers to the difference between the starting and end point coordinates when the user drags or moves the visual control, which is used to quantify the spatial movement amplitude of the operation.

[0076] In an embodiment of the present invention, first, the user's dragging and moving operation records on the visual control are extracted through the operation log of the graphical development tool to obtain the starting point coordinates and end point coordinates of each operation trajectory; secondly, the coordinate difference between the starting point and end point of each operation trajectory is calculated to generate the spatial position offset of the visual control, where the spatial position offset is used to quantify the spatial movement characteristics of the user operation.

[0077] Step 202: extracting the interval duration between adjacent trigger operations from the interface control trigger sequence, and determining the collaborative focus area and operation continuity identifier of the multi-user interaction behavior data stream based on the corresponding relationship between the spatial position offset and the interval duration.

[0078] In this step, the collaborative focus area refers to the interface area where the operation trajectories of multiple users highly overlap in space and are continuously triggered in time, reflecting the core operation scope of user collaboration; the operation continuity identifier refers to the mark generated by analyzing the time interval between adjacent trigger operations, which is used to identify operation sequences with strong continuity and close logical association.

[0079] In an embodiment of the present invention, the time interval between two adjacent trigger operations is first extracted from the interface control trigger sequence; secondly, the correspondence between the spatial position offset and the time interval is analyzed. When the spatial position offsets of the operation trajectories of multiple users in a specific area are dense and the time intervals are continuous, the area is marked as a collaborative focus area; finally, the time period of continuous trigger operations is marked as an operation continuity identifier.

[0080] Step 203: Count the triggering frequencies of the function attribute association identifiers of all the visual controls in the collaboration focus area, and determine the visual control corresponding to the function attribute association identifier with the highest triggering frequency as the core function control.

[0081] In this step, the functional attribute association identifier refers to the classification tag defined according to the functional type of the control; the triggering frequency refers to the number of times the control corresponding to a functional attribute association identifier is operated per unit time, which is used to measure the collaborative activity of the functional module; the core functional control refers to the control corresponding to the functional attribute association identifier with the highest triggering frequency in the collaborative focus area, which serves as the root node of the hierarchical structure.

[0082] In an embodiment of the present invention, the number of times the functional attribute association identifiers of all visual controls in the collaborative focus area are triggered is first counted; secondly, the triggering frequency of each functional attribute association identifier within a preset time window is calculated, and the triggering frequency is the number of triggers divided by the total duration of the time window; finally, the visual control corresponding to the functional attribute association identifier with the highest triggering frequency is selected and determined as the core functional control.

[0083] Step 204: The core function control is used as the root node of each function attribute association identifier to perform hierarchical merging to generate a hierarchical mapping relationship.

[0084] In this step, the root node of the functional attribute association identifier refers to the core functional control as the top layer in the hierarchical mapping relationship, and other similar controls extend downward according to their functional dependencies; the hierarchical merging operation refers to the process of hierarchically connecting similar controls to the core functional control according to their functional dependencies to form a tree structure.

[0085] In an embodiment of the present invention, the core function control is first taken as the root node, and other visual controls are classified according to the functional attribute association identifier; secondly, similar controls are hierarchically connected according to the functional dependency relationship between the controls; and finally, a tree-like hierarchical mapping relationship is generated with the core function control as the top level.

[0086] Step 205: taking the earliest triggered control operation event in the operation continuity identifier as the starting node, and binding the subsequent control operation events as child nodes of the starting node in the triggering order to generate a logical dependency chain across user operation instructions.

[0087] In this step, the binding operation refers to associating subsequent control operation events to the child node positions of the starting node in the triggering order to establish a dependency relationship of the operation instructions; the child node of the starting node refers to the operation event triggered later than the starting node in the logical dependency chain, and its execution depends on the completion status of the starting node; the logical dependency chain of cross-user operation instructions refers to the instruction execution chain formed by multiple users operating the same control or associated controls in chronological order.

[0088] In an embodiment of the present invention, first, the earliest triggered control operation event is extracted from the operation continuity identifier as the starting node of the logical dependency chain; secondly, the subsequent control operation events are sequentially bound as child nodes of the starting node in the order of triggering time; and finally, a logical dependency chain across user operation instructions is formed, wherein the logical dependency chain reflects the execution order of the operation events.

[0089] Step 206: Combine the hierarchical mapping relationship with the logical dependency chain to generate a dynamic semantic graph.

[0090] In this step, the combination operation refers to associating and mapping the hierarchical mapping relationship with the logical dependency chain and structurally fusing them to generate a dynamic semantic graph with unified expression.

[0091] In an embodiment of the present invention, the tree-like control structure in the hierarchical mapping relationship is first associated and mapped with the operation instruction sequence in the logical dependency chain; secondly, the hierarchical relationship and the dependency chain are integrated into a dynamic semantic graph through a combination operation, wherein the dynamic semantic graph simultaneously describes the functional hierarchy of the control and the logical dependency relationship of the operation instructions.

[0092] The present invention provides a specific embodiment, step 203, counting the triggering frequencies of the function attribute association identifiers of all the visual controls in the collaboration focus area, and determining the visual control corresponding to the function attribute association identifier with the highest triggering frequency as the core function control, specifically includes the following steps:

[0093] Step 231: extracting the functional attribute association identifier and the corresponding trigger time set of each visual control within the preset time window from the collaboration focus area, and generating a mapping relationship between the functional attribute association identifier and the trigger time set.

[0094] In this step, the corresponding trigger moment set refers to the set of time points when all visual controls under the same functional attribute association identifier are operated, which is used to analyze the operation timing characteristics of the functional module; the mapping relationship refers to the data association table between the functional attribute association identifier and its trigger moment set, which is used to structure the storage of operation timing data.

[0095] In an embodiment of the present invention, first, the functional attribute association identifier of each visual control within a preset time window is extracted from the collaborative focus area; secondly, the trigger time set corresponding to each functional attribute association identifier is collected; finally, a mapping relationship is established between the functional attribute association identifier and its corresponding trigger time set to form a structured data association table.

[0096] Step 232: Merge all triggering moments under the same functional attribute association identifier into a global triggering sequence, count the number of triggering times of each functional attribute association identifier in the global triggering sequence, and calculate the triggering frequency of each functional attribute association identifier by the ratio of the number of triggering times to the length of the preset time window.

[0097] In this step, the merging operation refers to the process of integrating multiple trigger moment sequences under the same functional attribute association identifier into a single global timing sequence in chronological order; the global trigger sequence refers to the complete time point sequence under the functional attribute association identifier formed after integrating multi-user operations, reflecting the cross-user collaborative timing characteristics; the ratio calculation operation refers to the calculation process of obtaining the triggered frequency by dividing the number of triggers by the preset time window length, which is used to quantify the operation density per unit time.

[0098] In an embodiment of the present invention, first, all trigger moments under the same functional attribute association identifier are merged into a global trigger sequence in chronological order, and the global trigger sequence integrates the operation timing of multiple users on the functional attribute control; secondly, the number of triggers of each functional attribute association identifier in the global trigger sequence is counted; finally, the trigger frequency of each functional attribute association identifier is calculated by dividing the number of triggers by the length of the preset time window, and the trigger frequency reflects the collaborative activity of the functional module.

[0099] Step 233: extract the last triggering time of each function attribute association identifier from the global triggering sequence, and generate a real-time activity factor according to the interval length from the last triggering time to the current time.

[0100] In this step, the generation operation refers to the process of calculating the real-time activity based on the interval from the last triggering moment to the current time, and the formula is 1 divided by the sum of the interval and 1; the real-time activity factor refers to a quantitative indicator reflecting the recent operation popularity of the function attribute association identifier. The shorter the interval, the higher the activity factor value.

[0101] In an embodiment of the present invention, first, the last triggering moment of each functional attribute association identifier is extracted from the global trigger sequence; secondly, the interval duration from the last triggering moment to the current time is calculated, and the interval duration is the difference between the current time and the last triggering moment; finally, a real-time activity factor is generated according to the interval duration to quantify the real-time operation heat of the functional attribute.

[0102] Step 234: Multiply the triggered frequency by the real-time activity factor to generate a comprehensive trigger weight value for each functional attribute association identifier.

[0103] In this step, the multiplication operation refers to the calculation process of numerically multiplying the triggered frequency and the real-time activity factor to generate a comprehensive weight value by integrating historical and real-time data; the comprehensive trigger weight value refers to a comprehensive evaluation index generated by combining historical operation frequency and real-time activity, which is used to dynamically determine the core function control.

[0104] In an embodiment of the present invention, the triggered frequency is first numerically multiplied by the real-time activity factor, and the real-time activity factor reflects the recent operation activity; secondly, the historical frequency and the real-time heat are fused through a multiplication operation, and finally a comprehensive trigger weight value of each functional attribute association identifier is generated, and the comprehensive trigger weight value is used to comprehensively evaluate the collaborative importance of the functional attributes.

[0105] Step 235: Determine the visual control corresponding to the functional attribute association identifier with the highest comprehensive trigger weight value as the core functional control.

[0106] In this step, the corresponding visual control refers to a specific interface element bound to the functional attribute association identifier with the highest comprehensive trigger weight value, which serves as the core node of the collaborative process.

[0107] In an embodiment of the present invention, the comprehensive trigger weight values ​​of all functional attribute association identifiers are first sorted in descending order, and the sorting result reflects the collaboration priority of each functional attribute; secondly, the functional attribute association identifier with the highest comprehensive trigger weight value is selected, and its corresponding visual control is determined as the core functional control, wherein the core functional control serves as the core node for resource allocation and process scheduling.

[0108] The present invention provides a specific embodiment, step 103, inputting the hierarchical mapping relationship into a preset edge computing node, and generating a real-time computing power allocation plan that matches the logical dependency chain based on the distributed computing power allocation strategy within the preset edge computing node, specifically comprising the following steps:

[0109] Step 301: parsing the hierarchical depth of the visual control node in the hierarchical mapping relationship and the dependency path length of the logical operation instruction in the logical dependency chain.

[0110] In this step, the hierarchical depth of the visual control node refers to the number of levels from the root node to the current node of the visual control in the hierarchical mapping relationship tree, reflecting the position depth of the control in the functional structure; the logical operation instruction refers to the execution command generated by the user's operation on the visual control, such as creation, modification, binding events, etc.; the dependency path length refers to the total number of nodes in the logical dependency chain from the starting operation instruction to the end instruction, reflecting the complexity of the instruction chain.

[0111] In an embodiment of the present invention, the hierarchical depth of the visualized control node in the dynamic semantic graph is first parsed, where the hierarchical depth is the number of levels of the control node from the root node to the current node in the hierarchical mapping relationship tree; secondly, the dependency path length of the logical operation instructions in the logical dependency chain is parsed, and the hierarchical depth and dependency path length are output as key parameters for computing power allocation.

[0112] Step 302: According to the proportional relationship between the hierarchical depth and the dependent path length, a corresponding computing power allocation rule is matched from the distributed computing power allocation strategy.

[0113] In this step, the proportional relationship refers to the ratio of the hierarchical depth to the dependent path length, which is used to match the rules in the computing power allocation strategy; the matching operation refers to the process of selecting an adapted computing power allocation rule from a preset rule library based on the proportional relationship; the computing power allocation rule refers to a predefined resource allocation strategy, which includes parameters such as the hierarchical weight coefficient and the path priority threshold.

[0114] In an embodiment of the present invention, the proportional relationship between the hierarchical depth and the dependent path length is first calculated, and the proportional relationship is the value of the hierarchical depth divided by the dependent path length; secondly, the corresponding computing power allocation rule is matched from the rule base of the distributed computing power allocation strategy according to the proportional relationship, and the allocation strategies corresponding to different proportional intervals are pre-stored in the rule base, including the hierarchical weight coefficient and the path priority threshold.

[0115] Step 303: Based on the hierarchical computing power weight coefficient and the path length priority threshold in the computing power allocation rule, calculate the proportion of computing power resources required by the visualization control node at each level and generate a hierarchical computing power allocation base.

[0116] In this step, the hierarchical computing power weight coefficient refers to the resource allocation weight value set according to the importance of different levels, and the shallower the level, the higher the weight; the path length priority threshold refers to the resource preemption priority parameter triggered when the dependent path length exceeds the set value; the computing power resource ratio refers to the allocation ratio of a single hierarchical node in the total resources, which is obtained by multiplying the hierarchical weight coefficient by the path threshold; the hierarchical computing power allocation base refers to the set of computing power resource ratios of all hierarchical nodes, which serves as the input benchmark for the real-time allocation plan.

[0117] In an embodiment of the present invention, first, the hierarchical computing power weight coefficient and the path length priority threshold are extracted according to the matching computing power allocation rules, where the hierarchical computing power weight coefficient is the resource allocation weight value of nodes at different levels; secondly, the computing power resource proportion of each hierarchical node is calculated, and the computing power resource proportions of all hierarchical nodes are summarized as the hierarchical computing power allocation base.

[0118] Step 304: Generate a real-time computing power allocation plan for the execution order of the logic operation instructions based on the hierarchical computing power allocation base and the real-time available computing power capacity of the preset edge computing node.

[0119] In this step, the real-time available computing capacity refers to the total amount of unoccupied computing resources that can be currently scheduled by the edge computing node, expressed as a percentage.

[0120] In an embodiment of the present invention, first, the real-time available computing power capacity is obtained from the preset edge computing node, and the real-time available computing power capacity is the percentage of computing resources that are currently unoccupied; secondly, the available computing power is proportionally allocated to each level node according to the hierarchical computing power allocation base, and finally a real-time computing power allocation plan is generated for the execution order of logical operation instructions, so as to ensure that high-priority instructions obtain resources first.

[0121] The present invention provides a specific embodiment, step 104, based on a preset rendering priority rule, parsing the mapping relationship between the control trigger timestamp and the control type in the spatiotemporal association pattern to generate an interface control rendering priority queue, specifically comprising the following steps:

[0122] Step 401: extracting a set of visual controls having a collaborative operation relationship from the control type mapping relationship to generate a function association group.

[0123] In this step, the collaborative operation relationship refers to the association relationship between multiple visual controls that need to be used together or complement each other in terms of functional logic, for example, the data input control and the data verification control need to work together to complete form validation; the functional association group refers to a collection of visual controls with a collaborative operation relationship, which is a logical grouping formed by classifying them according to functional complementarity.

[0124] In an embodiment of the present invention, first, a set of visual controls with collaborative operation relationships are extracted from the control type mapping relationship, where the collaborative operation relationships are logical associations in which the functions of the controls are complementary or need to be used together; secondly, controls of the same type are classified into functional association groups according to the functional complementarity of the control types, and finally a structured grouping list is generated.

[0125] Step 402: extracting the first triggering moment of each visualization control and the interval between adjacent triggering moments from the control triggering timestamp.

[0126] In this step, the first triggering moment refers to the time point when a certain visual control is operated by the user for the first time within the preset time window; the adjacent triggering moment refers to the time point when the same visual control is operated twice in succession, and the difference between the latter moment and the previous moment is the interval duration.

[0127] In an embodiment of the present invention, the first triggering moment of each visual control is first extracted from the control trigger timestamp, where the first triggering moment is the time point when the control is first operated by the user; secondly, the interval length between adjacent triggering moments is calculated, where the interval length is the difference between the latter triggering moment and the previous triggering moment, so as to reflect the operation intensity.

[0128] Step 403: assigning initial rendering priority levels to the visual controls in the same function association group according to the order of the first triggering moments, generating an assigned function association group, wherein the visual controls are converted into assigned visual controls.

[0129] In this step, the initial rendering priority level refers to the initial priority value assigned to the controls in the function association group based on the order of the first triggering time, and the earlier the first triggering, the higher the level; the assigned function association group refers to the function association group after the initial rendering priority level is bound, which includes controls and their priority attributes; the assigned visual control refers to the visual control in the assigned function association group that has been bound to the initial rendering priority level.

[0130] In an embodiment of the present invention, the visual controls within the same functional association group are first sorted in order of the first triggering moment, and the controls with earlier first triggering moments are assigned higher initial rendering priority levels; secondly, the assigned visual controls are bound to the priority levels, and finally an assigned functional association group containing initial priority attributes is generated.

[0131] Step 404: Based on the comparison result of the interval duration and the preset duration urgency threshold, the initial rendering priority level of the allocated visual control is adjusted to generate a priority ranking of the allocated visual control.

[0132] In this step, the preset duration urgency threshold refers to the critical time value for determining the urgency of the operation, and an interval duration less than this value is regarded as a high-urgency operation; the adjustment operation refers to the process of dynamically modifying the priority level of the assigned visual control based on the comparison result between the interval duration and the threshold; the priority sorting of the assigned visual control refers to the sequence of controls in the adjusted functional association group arranged from high to low priority level.

[0133] In an embodiment of the present invention, first, the interval duration between adjacent trigger moments is compared with a preset duration urgency threshold, wherein the preset duration urgency threshold is a critical value for determining the urgency of the operation; secondly, if the interval duration is less than the threshold, the initial rendering priority level of the corresponding assigned visual control is increased; if the interval duration is greater than the threshold, the priority level is maintained or lowered; finally, an adjusted priority ranking of the assigned visual controls is generated.

[0134] Step 405: Arrange the assigned function association groups according to the global order of the first triggering moment according to the priority sorting to generate an interface control rendering priority queue.

[0135] In this step, the global order of the first triggering moment refers to the global timeline order formed by the earliest triggered control time point in all function association groups; the arrangement operation refers to the process of integrating the priority sorting within each group according to the global order to generate the final interface control rendering queue.

[0136] In an embodiment of the present invention, each group is first sorted in a global order according to the first triggering moment of the function association group, and the global order of the first triggering moment is the earliest triggered control time point in all function association groups; secondly, the adjusted priority sorting within each function association group is integrated according to the order between groups, and finally a globally unified interface control rendering priority queue is generated.

[0137] The present invention provides a specific embodiment, step 105, based on the real-time computing power allocation scheme, synchronously regulating the interface control rendering priority queue and the operation instruction response sequence corresponding to the logical dependency chain, generating a multi-user collaborative intent-driven graphical software development process synchronization instruction set to perform graphical software development management, specifically including the following steps:

[0138] Step 501: extracting the computing power allocation ratio of each visualization control node and the weight coefficient of the operation instruction execution order from the real-time computing power allocation plan.

[0139] In this step, the computing power allocation ratio refers to the percentage of computing power resources occupied by a single visualization control node extracted from the real-time computing power allocation plan, which is used to guide resource allocation; the weight coefficient refers to the instruction priority quantization value generated based on the logical dependency chain. The higher the weight coefficient, the higher the execution priority.

[0140] In an embodiment of the present invention, the computing power allocation ratio of each visualization control node is first extracted from the real-time computing power allocation plan, and the computing power allocation ratio is the allocation percentage of the node in the total computing power resources; then the weight coefficient of the execution order of the operation instructions is extracted, and the weight coefficient is generated according to the urgency and execution dependency of the instructions in the logical dependency chain to reflect the priority of the instructions.

[0141] Step 502: Divide the interface control rendering priority queue into rendering resource allocations of multiple time slice units according to the computing power allocation ratio, and map the operation instruction response sequence into an execution instruction set of the corresponding time slice unit according to the weight coefficient.

[0142] In this step, the time slice unit refers to dividing the total execution time into segments of equal length, and each segment is allocated fixed computing power resources for processing instructions in stages; the rendering resource allocation amount refers to the total amount of computing power resources available in a single time slice unit, which is obtained by multiplying the computing power allocation ratio by the time slice length; the mapping operation refers to the process of sorting the operation instructions by priority according to the weight coefficient and allocating them to the corresponding time slice unit; the execution instruction set refers to the set of operation instructions to be executed in the same time slice unit, sorted by the weight coefficient.

[0143] In an embodiment of the present invention, the interface control rendering priority queue is first divided into time slice units according to the computing power allocation ratio, and the time slice unit is a preset fixed-length segment; secondly, the instructions in the operation instruction response sequence are sorted by priority according to the weight coefficient, and then mapped to the execution instruction set of the corresponding time slice unit to ensure that high-weight instructions are allocated to the front time slice first.

[0144] Step 503: within the same time slice unit, matching the rendering resource allocation amount with the execution instruction set, and generating a synchronous execution instruction when the rendering resource allocation amount supports the rendering requirements of all execution instructions within the current time slice unit.

[0145] In this step, the matching operation refers to the process of comparing the rendering resource allocation amount with the total rendering requirement of the execution instruction set to determine whether the resources are sufficient; the rendering requirement of the execution instruction refers to the amount of computing power resources required to execute a single operation instruction, the sum of which is the total rendering requirement of the execution instruction set; the synchronous execution instruction refers to a set of instructions marked as being executable immediately in the current time slice when resources are sufficient.

[0146] In an embodiment of the present invention, the amount of rendering resource allocation is first compared with the total rendering requirement of the execution instruction set within the same time slice unit. The total rendering requirement is the sum of the computing power consumption of all instructions in the execution instruction set. Then, when the amount of rendering resource allocation is greater than or equal to the total rendering requirement, a synchronous execution instruction is finally generated to mark that all instructions in the time slice can be executed immediately.

[0147] Step 504: When the rendering resource allocation amount is insufficient, adding a delayed execution instruction to the logic operation instruction with a low path criticality tag according to the path criticality tag of the logic operation instruction in the logic dependency chain.

[0148] In this step, the path criticality tag refers to the importance of the logical operation instruction in the dependency chain. The higher the tag value, the more critical the instruction. Delayed execution instructions refer to instructions that are postponed due to insufficient resources, and include information on reallocated time slices and the maximum allowable delay duration.

[0149] In an embodiment of the present invention, when the amount of rendering resource allocation is less than the total amount of rendering demand, the path criticality mark of the logical operation instruction is first extracted from the logical dependency chain, and the path criticality mark is generated based on the hierarchical depth of the instruction and the dependency path length; secondly, a delayed execution instruction is added to the instruction whose path criticality mark is lower than a preset threshold.

[0150] Step 505: Integrate the synchronous execution instructions and delayed execution instructions of each time slice unit in a time axis sequence to generate a graphical software development process synchronous instruction set.

[0151] In this step, the timeline sequence refers to the global execution order arranged in chronological order according to the start time of the time slice unit; the integration operation refers to the process of merging the synchronous execution instructions and the delayed execution instructions into a complete instruction set according to the timeline sequence.

[0152] In an embodiment of the present invention, the synchronous execution instructions of each time slice unit are first arranged in a timeline order, and the timeline order is the chronological order of the start moments of the time slice units; secondly, the delayed execution instruction is inserted into the end of the execution instruction set of its reallocated time slice unit; finally, all instructions are merged into a graphical software development process synchronization instruction set according to the execution sequence through an integration operation.

[0153] The present invention provides a specific embodiment, in step 504, when the amount of rendering resource allocation is insufficient, adding a delayed execution instruction to the logic operation instruction with a low path criticality flag according to the path criticality flag of the logic operation instruction in the logic dependency chain, specifically comprising the following steps:

[0154] Step 541: When the rendering resource allocation is insufficient, the hierarchical dependency depth of the visual control node corresponding to the logical operation instruction and the total number of directly associated visual control nodes are extracted from the dynamic semantic graph to generate a path criticality mark of the logical operation instruction. The hierarchical dependency depth is the number of levels of the visual control node in the hierarchical mapping relationship.

[0155] In this step, the hierarchical dependency depth refers to the number of levels of the visual control node from the root node to the current node in the hierarchical mapping relationship tree, reflecting the position depth of the control in the functional structure; the total number of visual control nodes refers to the number of child nodes or sibling nodes that have a direct functional dependency relationship with the current control, reflecting the influence range of the control; the path criticality mark refers to the instruction importance mark generated by the combination of the hierarchical dependency depth and the total number of directly associated nodes, which is used for resource allocation decisions; the hierarchical number refers to the position level of the control in the hierarchical tree, with the root node at level 1 and the child nodes increasing step by step.

[0156] In an embodiment of the present invention, when the amount of rendering resource allocation is insufficient, the hierarchical dependency depth of the visual control node corresponding to the logical operation instruction is first extracted from the dynamic semantic graph, and the hierarchical dependency depth is the number of levels of the visual control node from the root node to the current node in the hierarchical mapping relationship tree; secondly, the total number of visual control nodes directly associated with the control node is extracted, and the total number of directly associated nodes is the number of child nodes or sibling nodes that have a functional dependency relationship with the control; finally, the hierarchical dependency depth and the total number of directly associated nodes are combined into a path criticality mark.

[0157] Step 542: Multiply the hierarchical dependency depth by the total number of directly associated visual control nodes to generate a path criticality value of the logic operation instruction.

[0158] In this step, the multiplication operation refers to the calculation process of generating a path criticality value by numerically multiplying the hierarchical dependency depth by the total number of directly associated nodes; the path criticality value refers to a quantitative indicator of instruction importance generated by multiplying the hierarchical depth by the number of associated nodes, and the higher the value, the more critical it is.

[0159] In an embodiment of the present invention, the hierarchical dependency depth is first multiplied by the total number of directly associated visual control nodes. The greater the hierarchical dependency depth and the more directly associated nodes, the larger the product result. Secondly, through the multiplication operation, the path criticality value of the logical operation instruction is finally generated. The path criticality value is used to quantify the importance of the instruction in the collaborative process.

[0160] Step 543: According to the real-time computing power allocation plan, the logic operation instructions whose path criticality values ​​are lower than the preset path criticality threshold are marked as low-criticality instructions.

[0161] In this step, the preset path criticality threshold refers to the dynamically adjusted instruction criticality judgment standard, which is set according to the real-time computing resource status; low-criticality instructions refer to instructions whose path criticality value is lower than the threshold, and delayed execution is allowed to prioritize high-criticality operations.

[0162] In an embodiment of the present invention, the current available computing power resource status is first obtained from the real-time computing power allocation plan; secondly, the preset path criticality threshold is dynamically adjusted according to the remaining computing power capacity, and the lower the remaining computing power, the higher the threshold; then, the logical operation instructions with path criticality values ​​lower than the threshold are marked as low-criticality instructions, and the low-criticality instructions are non-core operations that can be executed delayed.

[0163] Step 544: Calculate the maximum allowable delay duration of the low-criticality instruction based on the sum of the remaining rendering resource allocation of the current time slice unit and the pre-allocated rendering resource allocation of the next time slice unit, combined with the rendering demand rate of the low-criticality instruction.

[0164] In this step, the remaining rendering resource allocation refers to the amount of unoccupied computing resources in the current time slice unit; the pre-allocated rendering resource allocation refers to the amount of computing resources planned to be allocated in the next time slice unit; the rendering demand rate refers to the amount of computing resources required per unit time when low-criticality instructions are executed; the calculation operation refers to the process of obtaining the maximum allowable delay duration by dividing the sum of the remaining resources and the pre-allocated resources by the rendering demand rate; the maximum allowable delay duration refers to the maximum time that the low-criticality instructions can be postponed for execution, and exceeding this time duration may cause process abnormalities.

[0165] In an embodiment of the present invention, the remaining rendering resource allocation of the current time slice unit and the pre-allocated rendering resource allocation of the next time slice unit are first obtained; secondly, the rendering requirement rate of the low-criticality instruction is combined, and the rendering requirement rate is the amount of computing power resources required per unit time. The maximum allowable delay duration is calculated by dividing the sum of the remaining resources and the pre-allocated resources by the rendering requirement rate.

[0166] Step 545: Generate a delayed execution instruction containing the maximum allowed delay duration for the low criticality instruction, and bind the delayed execution instruction to the end of the logic operation instruction of the next available time slice unit to add a delayed execution instruction to the logic operation instruction marked with a low path criticality.

[0167] In this step, the generation operation refers to creating an instruction entity containing the delay duration and binding time slice information for the low-criticality instruction; the binding operation refers to the process of inserting the delayed execution instruction into the end of the target time slice unit and ensuring resource matching; the low path criticality mark refers to the instruction identifier whose path criticality value is lower than the threshold, which characterizes its attribute of delayed execution.

[0168] In an embodiment of the present invention, first, a delayed execution instruction containing the maximum allowed delay duration is generated for the low-criticality instruction; secondly, the delayed execution instruction is bound to the end of the logical operation instruction of the next available time slice unit, and finally, it is verified whether the remaining resources of the bound time slice meet its rendering requirements to ensure that the delayed instruction is executed within the allowed duration.

[0169] Figure 2 The present invention provides a structural diagram of a semantically fused graphical software development management system, such as Figure 2 As shown, the system includes:

[0170] An acquisition module 21 is used to acquire a multi-user interaction behavior data stream including an operation trajectory sequence and an interface control triggering sequence;

[0171] A construction module 22 is configured to construct a dynamic semantic graph reflecting user collaboration intentions based on a spatiotemporal correlation pattern between the operation trajectory sequences of different users in the multi-user interaction behavior data stream and the triggering timing of the interface controls, wherein the dynamic semantic graph includes a hierarchical mapping relationship of visual control nodes and a logical dependency chain of cross-user operation instructions;

[0172] An input module 23 is configured to input the hierarchical mapping relationship into a preset edge computing node, and generate a real-time computing power allocation plan that matches the logical dependency chain according to the distributed computing power allocation strategy within the preset edge computing node;

[0173] The parsing module 24 is configured to parse the mapping relationship between the control trigger timestamp and the control type in the spatiotemporal association pattern based on a preset rendering priority rule to generate an interface control rendering priority queue;

[0174] The control module 25 is used to synchronously control the interface control rendering priority queue and the operation instruction response sequence corresponding to the logical dependency chain based on the real-time computing power allocation plan, and generate a multi-user collaborative intention-driven graphical software development process synchronization instruction set to perform graphical software development management.

[0175] Figure 2 The semantic fusion graphical software development management system can be executed Figure 1 The implementation principle and technical effects of the semantically fused graphical software development management method described in the illustrated embodiment will not be elaborated on here. The specific manner in which each module and unit performs operations in the semantically fused graphical software development management system in the above embodiment has been described in detail in the embodiments of the method and will not be elaborated on here.

[0176] In one possible design, Figure 2 A semantically fused graphical software development management system of the embodiment shown can be implemented as a computing device, such as Figure 3 As shown, the computing device may include a storage component 31 and a processing component 32;

[0177] The storage component 31 stores one or more computer instructions, wherein the one or more computer instructions are called and executed by the processing component 32 .

[0178] The processing component 32 is used for the above Figure 1 The embodiment provides a semantically fused graphical software development management method.

[0179] The processing component 32 may include one or more processors to execute computer instructions to perform all or part of the steps in the above method. Of course, the processing component may also be implemented as one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field programmable gate arrays (FPGAs), controllers, microcontrollers, microprocessors, or other electronic components to perform the above method.

[0180] The storage component 31 is configured to store various types of data to support operations at the terminal. The storage component can be implemented by any type of volatile or non-volatile memory device, or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk, or optical disk.

[0181] Of course, a computing device may also include other components, such as input / output interfaces, display components, communication components, etc.

[0182] The input / output interface provides an interface between the processing component and the peripheral interface module, which can be an output device, an input device, etc.

[0183] The communication component is configured to facilitate, among other things, wired or wireless communications between the computing device and other devices.

[0184] Among them, the computing device can be a physical device or an elastic computing host provided by a cloud computing platform, etc. In this case, the computing device can refer to a cloud server, and the above-mentioned processing components, storage components, etc. can be basic server resources rented or purchased from the cloud computing platform.

[0185] The embodiment of the present invention further provides a computer storage medium storing a computer program, which can achieve the above-mentioned Figure 1 The illustrated embodiment provides a semantically fused graphical software development management method.

[0186] Those skilled in the art will clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0187] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, i.e., they may be located in one location or distributed across multiple network units. Some or all of the modules may be selected based on actual needs to achieve the objectives of the present embodiment. Persons of ordinary skill in the art will be able to understand and implement the present invention without inventive effort.

[0188] Through the description of the above embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus a necessary general hardware platform, or of course, by hardware. Based on this understanding, the essence of the above technical solution or the part that contributes to the existing technology can be embodied in the form of a software product. The computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a magnetic disk, an optical disk, etc., and includes a number of instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or certain parts of the embodiments.

[0189] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the various embodiments of the present invention.

Claims

1. A semantically fused graphical software development management method, characterized in that: include: Obtain multi-user interaction behavior data streams including operation trajectory sequences and interface control triggering timings; Constructing a dynamic semantic graph reflecting user collaboration intentions based on the spatiotemporal correlation pattern between the operation trajectory sequences of different users in the multi-user interaction behavior data stream and the triggering timing of the interface controls. The dynamic semantic graph includes a hierarchical mapping relationship of visual control nodes and a logical dependency chain of cross-user operation instructions. Inputting the hierarchical mapping relationship into a preset edge computing node, and generating a real-time computing power allocation plan that matches the logical dependency chain according to the distributed computing power allocation strategy within the preset edge computing node; Based on a preset rendering priority rule, the mapping relationship between the control trigger timestamp and the control type in the spatiotemporal association pattern is parsed to generate an interface control rendering priority queue; Based on the real-time computing power allocation scheme, the interface control rendering priority queue and the operation instruction response sequence corresponding to the logical dependency chain are synchronously regulated to generate a multi-user collaborative intention-driven graphical software development process synchronization instruction set for graphical software development management; The method constructs a dynamic semantic graph reflecting the user collaboration intention based on the spatiotemporal correlation pattern between the operation trajectory sequences of different users in the multi-user interaction behavior data stream and the triggering timing of the interface controls. The dynamic semantic graph includes a hierarchical mapping relationship of visual control nodes and a logical dependency chain of cross-user operation instructions, including: Extracting spatial position offsets of visual controls of a graphical software development tool from operation trajectory sequences of different users in the multi-user interaction behavior data stream; Extracting the interval durations between adjacent trigger operations from the interface control trigger sequence, and determining the collaborative focus area and operation continuity identifier of the multi-user interaction behavior data stream based on the corresponding relationship between the spatial position offset and the interval durations; Counting the triggering frequencies of the function attribute association identifiers of all the visual controls in the collaboration focus area, and determining the visual control corresponding to the function attribute association identifier with the highest triggering frequency as the core function control; The core function control is used as the root node of each function attribute association identifier to perform hierarchical merging to generate a hierarchical mapping relationship; The earliest triggered control operation event in the operation continuity identifier is used as the starting node, and subsequent control operation events are bound as child nodes of the starting node in the triggering order to generate a logical dependency chain across user operation instructions; The hierarchical mapping relationship is combined with the logical dependency chain to generate a dynamic semantic graph.

2. The method according to claim 1, characterized in that Counting the triggering frequencies of the function attribute association identifiers of all the visual controls in the collaboration focus area, and determining the visual control corresponding to the function attribute association identifier with the highest triggering frequency as the core function control, including: Extracting the functional attribute association identifier and the corresponding trigger time set of each visual control within the preset time window from the collaboration focus area, and generating a mapping relationship between the functional attribute association identifier and the trigger time set; Merging all triggering moments under the same functional attribute association identifier into a global triggering sequence, counting the number of triggering times of each functional attribute association identifier in the global triggering sequence, and calculating the triggering frequency of each functional attribute association identifier by the ratio of the number of triggering times to the length of the preset time window; Extracting the last triggering time of each function attribute association identifier from the global triggering sequence, and generating a real-time activity factor according to the interval between the last triggering time and the current time; Multiplying the triggered frequency by the real-time activity factor to generate a comprehensive trigger weight value for each functional attribute association identifier; The visual control corresponding to the functional attribute association identifier with the highest comprehensive trigger weight value is determined as the core functional control.

3. The method according to claim 1, characterized in that Inputting the hierarchical mapping relationship into a preset edge computing node, and generating a real-time computing power allocation plan that matches the logical dependency chain according to a distributed computing power allocation strategy within the preset edge computing node, including: Parsing the hierarchical depth of the visual control node in the hierarchical mapping relationship and the dependency path length of the logical operation instruction in the logical dependency chain; Matching a corresponding computing power allocation rule from the distributed computing power allocation strategy according to a proportional relationship between the hierarchical depth and the dependency path length; Based on the hierarchical computing power weight coefficient and the path length priority threshold in the computing power allocation rule, the proportion of computing power resources required by the visualization control node at each level is calculated to generate a hierarchical computing power allocation base; A real-time computing power allocation plan for the execution order of the logical operation instructions is generated based on the hierarchical computing power allocation base and the real-time available computing power capacity of the preset edge computing node.

4. The method according to claim 1, wherein Based on the preset rendering priority rules, the mapping relationship between the control trigger timestamp and the control type in the spatiotemporal association pattern is parsed to generate an interface control rendering priority queue, including: Extracting a set of visual controls having a collaborative operation relationship from the control type mapping relationship to generate a functional association group; Extracting the first triggering moment of each visualization control and the interval between adjacent triggering moments from the control triggering timestamp; Allocating an initial rendering priority level to each visual control in the same function association group according to the order of the first triggering moments, generating an assigned function association group, wherein the visual control is converted into an assigned visual control; Based on a comparison result of the interval duration and a preset duration urgency threshold, adjusting the initial rendering priority level of the allocated visual control to generate a priority ranking of the allocated visual control; The priority sorting is performed to arrange each of the assigned function association groups in a global order of the first triggering moment to generate an interface control rendering priority queue.

5. The method according to claim 1, wherein Based on the real-time computing power allocation scheme, the interface control rendering priority queue and the operation instruction response sequence corresponding to the logical dependency chain are synchronously regulated to generate a multi-user collaborative intent-driven graphical software development process synchronization instruction set for graphical software development management, including: Extracting the computing power allocation ratio of each visualization control node and the weight coefficient of the operation instruction execution order from the real-time computing power allocation plan; Dividing the interface control rendering priority queue into rendering resource allocations of a plurality of time slice units according to the computing power allocation ratio, and mapping the operation instruction response sequence into an execution instruction set corresponding to the time slice unit according to the weight coefficient; In the same time slice unit, the rendering resource allocation amount is matched with the execution instruction set, and when the rendering resource allocation amount supports the rendering requirements of all execution instructions in the current time slice unit, a synchronous execution instruction is generated; When the rendering resource allocation amount is insufficient, adding a delayed execution instruction to the logic operation instruction with a low path criticality mark according to the path criticality mark of the logic operation instruction in the logic dependency chain; The synchronous execution instructions and delayed execution instructions of each time slice unit are integrated in timeline order to generate a graphical software development process synchronous instruction set.

6. The method according to claim 5, characterized in that When the rendering resource allocation amount is insufficient, adding a delayed execution instruction to the logic operation instruction with a low path criticality mark according to the path criticality mark of the logic operation instruction in the logic dependency chain, including: When the rendering resource allocation is insufficient, extracting the hierarchical dependency depth of the visualization control node corresponding to the logic operation instruction and the total number of directly associated visualization control nodes from the dynamic semantic graph to generate a path criticality tag of the logic operation instruction, wherein the hierarchical dependency depth is the number of levels of the visualization control node in the hierarchical mapping relationship; Multiplying the hierarchical dependency depth by the total number of directly associated visual control nodes to generate a path criticality value of the logic operation instruction; According to the real-time computing power allocation scheme, the logic operation instructions whose path criticality values ​​are lower than a preset path criticality threshold are marked as low-criticality instructions; Calculate the maximum allowable delay duration of the low-criticality instruction based on the sum of the remaining rendering resource allocation amount of the current time slice unit and the pre-allocated rendering resource allocation amount of the next time slice unit, combined with the rendering demand rate of the low-criticality instruction; A delayed execution instruction including the maximum allowed delay duration is generated for the low criticality instruction, and the delayed execution instruction is bound to the end of the logic operation instruction of the next available time slice unit to add the delayed execution instruction to the logic operation instruction marked with a low path criticality.

7. A semantically fused graphical software development management system, applied to a semantically fused graphical software development management method according to any one of claims 1 to 6, characterized in that: include: An acquisition module is used to obtain a multi-user interaction behavior data stream including an operation trajectory sequence and an interface control triggering sequence; A construction module is used to construct a dynamic semantic graph reflecting the user's collaborative intention based on the spatiotemporal correlation pattern between the operation trajectory sequences of different users in the multi-user interaction behavior data stream and the triggering timing of the interface controls. The dynamic semantic graph includes a hierarchical mapping relationship of visual control nodes and a logical dependency chain across user operation instructions; An input module, configured to input the hierarchical mapping relationship into a preset edge computing node, and generate a real-time computing power allocation plan that matches the logical dependency chain according to a distributed computing power allocation strategy within the preset edge computing node; A parsing module, configured to parse the mapping relationship between the control trigger timestamp and the control type in the spatiotemporal association pattern based on a preset rendering priority rule to generate an interface control rendering priority queue; A control module is used to synchronously control the interface control rendering priority queue and the operation instruction response sequence corresponding to the logical dependency chain based on the real-time computing power allocation plan, and generate a multi-user collaborative intention-driven graphical software development process synchronization instruction set to perform graphical software development management.

8. A computing device, characterized in that It includes a processing component and a storage component; the storage component stores one or more computer instructions; the one or more computer instructions are used to be called and executed by the processing component to implement a semantically fused graphical software development management method as described in any one of claims 1 to 6.

9. A computer storage medium, characterized in that A computer program is stored, and when the computer program is executed by a computer, the semantically fused graphical software development management method according to any one of claims 1 to 6 is implemented.

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