OTX diagnostic sequence intelligent development method and system based on workflow context awareness
By embedding event listeners and hidden Markov models in the OTX development environment, the development phase and task complexity are identified, and the team's health is monitored in real time. This solves the problems of insufficient workflow understanding and lack of context awareness in the development of OTX diagnostic sequences, realizes adaptive development support and knowledge reuse, and improves development efficiency.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-11-17
- Publication Date
- 2026-03-10
AI Technical Summary
The development of existing OTX diagnostic sequences suffers from problems such as insufficient understanding of workflow, lack of context awareness, inadequate adaptive support, and difficulty in knowledge reuse, resulting in low development efficiency.
By embedding event listeners in the OTX development environment, a hidden Markov model is used to identify the development phase, obtain task complexity and team health, perceive changes in the situation in real time, and make strategy recommendations based on team health.
It improves the efficiency of OTX diagnostic sequence development, avoids recoding due to insufficient resources, effectively accumulates and reuses best practices, and dynamically adjusts the development process.
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Figure CN121635865A_ABST
Abstract
Description
TECHNICAL FIELD
[0001] The present application relates to the technical field of OTX development, and particularly relates to an OTX diagnosis sequence intelligent development method and system based on workflow context awareness. BACKGROUND
[0002] Currently, OTX diagnosis sequence development mainly adopts a rule-based development method. In the OTX diagnosis sequence development process, developers face the following technical challenges: Insufficient understanding of workflow: existing development tools lack a deep understanding of the unique workflow of OTX diagnosis development, and cannot provide targeted intelligent assistance.
[0003] Lack of context awareness: the system cannot perceive the context changes in the development process, including development stages, task complexity, team collaboration status and other key factors.
[0004] Insufficient adaptive support: there is a lack of adaptive development support based on workflow status, and the tool functions and behaviors cannot be dynamically adjusted according to the current development needs.
[0005] Difficulty in knowledge reuse: it is difficult to effectively accumulate and reuse the best practices and successful patterns in OTX development. SUMMARY
[0006] In view of the deficiencies of the prior art, the present application provides an OTX diagnosis sequence intelligent development method and system based on workflow context awareness, which perceives the context changes in the OTX diagnosis sequence development process, dynamically adjusts the strategy recommendation according to the current OTX diagnosis sequence development stage, and effectively accumulates and reuses the best practices and successful patterns in OTX development.
[0007] Other characteristics and advantages of the present application will become apparent from the following detailed description, or will be learned by practice of the present application.
[0008] According to a first aspect of the present application, an OTX diagnosis sequence intelligent development method based on workflow context awareness is provided, comprising: identifying the current OTX diagnosis sequence development stage; acquiring the task complexity of the current OTX diagnosis sequence development stage; real-time sensing of the team collaboration context based on the task complexity, acquiring the team health degree and the corresponding warning indication of the team health degree; strategy recommendation based on the corresponding warning indication of the team health degree.
[0009] In some embodiments of the present application, based on the foregoing scheme, the identification of the current OTX diagnosis sequence development stage comprises: implanting an event listener in an OTX development environment to capture a current operation event of a developer in the OTX environment; taking a preset time threshold as a time window to obtain a current operation feature in real time; using a hidden Markov model to perform current OTX diagnosis sequence development stage recognition.
[0010] In some embodiments of the present application, based on the foregoing scheme, the current operation event includes a graphical design operation event, a parameter configuration operation event, a debugging operation event, and an optimization operation event; The current operation feature includes a graphical editing operation frequency corresponding to the graphical design operation event, a parameter configuration operation density corresponding to the parameter configuration operation event, a debugging operation concentration corresponding to the debugging operation event, and an optimization operation proportion corresponding to the optimization operation event. The method for using a hidden Markov model to perform current OTX diagnosis sequence development stage recognition is: inputting the current operation feature into the hidden Markov model to perform stage recognition, outputting a current OTX diagnosis sequence development stage, performing confidence calculation, and taking a state corresponding to the highest confidence score as the current OTX diagnosis sequence development stage.
[0011] In some embodiments of the present application, based on the foregoing scheme, the task complexity of obtaining the current OTX diagnosis sequence development stage includes: obtaining the task complexity based on a weighted sum of a control flow complexity and a data flow complexity; The method for obtaining the control flow complexity is: parsing an abstract syntax tree in the current OTX diagnosis sequence development stage, the abstract syntax tree including a loop nesting depth, a branch complexity, and a concurrency complexity, wherein the loop nesting depth is a maximum loop nesting layer number, the branch complexity is a product of an if-else node number and a branch coefficient, and the concurrency complexity is a product of a parallel execution block number and a concurrency weight; obtaining the control flow complexity by weighted sum of the loop nesting depth, the branch complexity, and the concurrency complexity; The method for obtaining the data flow complexity is: parsing a data dependency relationship in the current OTX diagnosis sequence development stage, the data dependency relationship including a variable dependency depth, a data type conversion complexity, and a data access density, wherein the variable dependency depth is a longest data dependency chain length, the data type conversion complexity is a product of an explicit type conversion number and a conversion weight, and the data access density is a read-write operation number divided by a code line number; obtaining the data flow complexity by weighted sum of the variable dependency depth, the data type conversion complexity, and the data access density.
[0012] In some embodiments of the present application, based on the foregoing scheme, the team collaboration context real-time perception based on task complexity, the team health degree and the early warning indication corresponding to the team health degree are obtained, comprising: obtaining the stage adaptation score, the ability adaptation score and the risk score based on the task complexity; weighting and summing the stage adaptation score, the ability adaptation score and the risk score to obtain the team collaboration health degree; obtaining the early warning indication corresponding to the team health degree based on the score of the team health degree, if the team health degree is less than or equal to 0.6, there is a red warning; if the team health degree is greater than 0.6 and less than 0.8, there is a yellow warning; if the team health degree is greater than or equal to 0.8, there is a green warning.
[0013] In some embodiments of the present application, based on the foregoing scheme, the method for obtaining the stage adaptation score, the ability adaptation score and the risk score based on the task complexity is: setting each complexity level based on the score of the task complexity, determining the complexity level to which the task complexity belongs based on the score of the task complexity, and obtaining the stage adaptation score based on the complexity level to which the task complexity belongs and the team experience level; the score of the ability adaptation score is: ability adaptation score = Σ (individual task matching degree × task weight) / total task number; the score of the risk score is: risk score = task complexity × time urgency × (1-member experience matching degree).
[0014] In some embodiments of the present application, based on the foregoing scheme, the strategy recommendation based on the early warning indication corresponding to the team health degree comprises: if the early warning indication corresponding to the team health degree is a red warning, it is recommended to strengthen the architecture review frequency, it is suggested to increase the participation of experts, and it is prompted to decompose complex tasks, if the early warning indication corresponding to the team health degree is a yellow warning and a green warning, it is recommended to divide the parallel test, it is suggested to establish a problem rapid response mechanism, and it is prompted to strengthen the progress synchronization.
[0015] According to the second aspect of the present application, an OTX diagnosis sequence intelligent development system based on workflow context perception is provided, the system comprising: a recognition module for recognizing the current OTX diagnosis sequence development stage; a task complexity acquisition module for acquiring the task complexity of the current OTX diagnosis sequence development stage; a team collaboration context real-time perception module for team collaboration context real-time perception based on task complexity, obtaining team health degree and early warning indication corresponding to team health degree; The recommendation module is configured to make a strategy recommendation based on the early warning indication corresponding to the team health degree.
[0016] According to a third aspect of the present application, a computer readable storage medium is provided, which stores a computer program including executable instructions, when the executable instructions are executed by a processor, the method described above is implemented.
[0017] According to a fourth aspect of the present application, an electronic device is provided, comprising: one or more processors; a memory for storing executable instructions of the processor, when the executable instructions are executed by the one or more processors, the one or more processors implement the method described above.
[0018] The beneficial effects of the present application are as follows: The method and system for intelligent development of OTX diagnosis sequence based on workflow context awareness provided by the present application can identify the current OTX diagnosis sequence development stage, obtain the task complexity of the current OTX diagnosis sequence development stage, perform real-time sensing of team collaboration context based on the task complexity, obtain the team health degree and the early warning indication corresponding to the team health degree, identify the potential high-computing scenario of the current OTX diagnosis sequence development stage, make a strategy recommendation based on the early warning indication corresponding to the team health degree, avoid re-coding due to insufficient resources after development is completed, and effectively accumulate and reuse the best practices and successful patterns in OTX development.
[0019] It should be understood that the above general description and the following detailed description are only exemplary and explanatory, and cannot limit the present application. BRIEF DESCRIPTION OF DRAWINGS
[0020] The drawings described herein are used to provide further understanding of the present application, and form a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application, and do not constitute an improper limitation on the present application. In the drawings: Figure 1 a flowchart of the method for intelligent development of OTX diagnosis sequence based on workflow context awareness of the present application; Figure 2 a schematic diagram of the system for intelligent development of OTX diagnosis sequence based on workflow context awareness of the present application; Figure 3 a schematic diagram of the electronic device of the present application. DETAILED DESCRIPTION
[0021] In order to make the application purposes, features and advantages of the present application more obvious and easy to understand, the technical solutions in the embodiments of the present application will be described clearly and completely below in conjunction with the accompanying drawings of the embodiments of the present application. Obviously, the following described embodiments are only some of the embodiments of the present application, but not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor fall within the scope of the present application.
[0022] It should be understood that the terms in the specification or claims of the present application and the above-described drawings include and other similar expressions, which mean to cover non-exclusive inclusion, such as a process, method or system, device including a series of steps or units, which is not limited to the listed steps or units. In addition, the first and second are used to distinguish different objects, and are not used to describe a specific order.
[0023] According to the first aspect of the present application, please refer to Figure 1 , a flow chart of a workflow context-aware OTX diagnosis sequence intelligent development method is shown, the embodiment provides a workflow context-aware OTX diagnosis sequence intelligent development method, which comprises: Step S1: identifying the current OTX diagnosis sequence development stage.
[0024] In some embodiments of the present embodiment, the identification of the current OTX diagnosis sequence development stage comprises: Step S101: implanting an event listener in the OTX development environment to capture the current operation event of the developer in the OTX environment; Step S102: taking a preset time threshold as a time window to obtain the current operation feature in real time; Step S103: using a hidden Markov model to identify the current OTX diagnosis sequence development stage.
[0025] In some embodiments of the present embodiment, the current operation event comprises graphical design operation event, parameter configuration operation event, debugging operation event and optimization operation event. Among them, the graphical design operation event includes node dragging, connection line establishment and block diagram combination, the parameter configuration operation event includes numerical input, constraint setting and data type change, the debugging operation event includes breakpoint setting, single-step execution, variable monitoring, and the optimization operation event includes performance analysis, code reconstruction, resource monitoring, etc.
[0026] In some embodiments of the present embodiment, the current operation features include a graphical editing operation frequency corresponding to a graphical design operation event, a parameter configuration operation density corresponding to a parameter configuration operation event, a debugging operation concentration corresponding to a debugging operation event, and an optimization operation proportion corresponding to an optimization operation event. The preset time threshold is 5 minutes, the graphical editing operation frequency is the number of graphical design operation events divided by the total number of operation times, the parameter configuration operation density is the number of parameter configuration operation events divided by the length of the time window, the debugging operation concentration is the number of continuous occurrences of debugging operation events, and the optimization operation proportion is the number of optimization operation events divided by the total number of operation times.
[0027] In some embodiments of the present embodiment, the current operation features (graphical editing operation frequency, parameter configuration operation density, debugging operation concentration, and optimization operation proportion) are input into a hidden Markov model for stage recognition, and a current OTX diagnosis sequence development stage (graphical design state, parameter configuration state, debugging state, or optimization state) is output. Confidence calculation is performed, and the state corresponding to the highest confidence score is taken as the current OTX diagnosis sequence development stage.
[0028] Specifically, a state transition probability matrix is established to describe the conversion rule between states, an observation probability matrix is constructed to associate operation features with development stages, a forward-backward algorithm is used to calculate state probabilities, a Viterbi algorithm is used to solve the most likely state, and the current OTX diagnosis sequence development stage and the corresponding confidence score are output.
[0029] Step S2: Obtain the task complexity of the current OTX diagnosis sequence development stage.
[0030] In some embodiments of the present embodiment, the task complexity includes a weighted sum of control flow complexity and data flow complexity.
[0031] In the present embodiment, the method for obtaining control flow complexity is as follows: An abstract syntax tree in the current OTX diagnosis sequence development stage is parsed, and the abstract syntax tree includes loop nesting depth, branch complexity, and concurrency complexity, wherein the loop nesting depth is the maximum loop nesting layer number, the branch complexity is the product of the number of if-else nodes and a branch coefficient, and the concurrency complexity is the product of the number of parallel execution blocks and a concurrency weight. The control flow complexity is obtained by weighted summation of the loop nesting depth, the branch complexity, and the concurrency complexity.
[0032] In the present embodiment, the method for obtaining data flow complexity is as follows: Analyzing data dependency in the current OTX diagnostic sequence development stage, including variable dependency depth, data type conversion complexity, and data access density, wherein the variable dependency depth is the length of the longest data dependency chain, the data type conversion complexity is the product of the number of explicit type conversions and the conversion weight, and the data access density is the number of read-write operations divided by the number of code lines; The data flow complexity is obtained by weighted summation of the variable dependency depth, the data type conversion complexity, and the data access density.
[0033] Step S3: Real-time team collaboration context perception based on task complexity, obtaining team health degree and early warning indication corresponding to the team health degree.
[0034] In some embodiments of the present embodiment, the method of real-time team collaboration context perception based on task complexity is: Obtaining stage adaptation score, capability adaptation degree, and risk score based on task complexity; Weighted summation of stage adaptation score, capability adaptation degree, and risk score to obtain team collaboration health degree; Obtaining early warning indication corresponding to the team health degree based on the score of the team health degree.
[0035] In the present embodiment, the stage adaptation score is obtained based on the complexity level to which the task complexity belongs and the team experience level.
[0036] The method of obtaining the complexity level to which the task complexity belongs is: Setting each complexity level based on the score range of the task complexity, and determining the complexity level to which the task complexity belongs based on the score of the task complexity.
[0037] In one specific embodiment, the complexity level is a first complexity level, a second complexity level, or a third complexity level. If the score of the task complexity is less than or equal to 2, the complexity level to which the task complexity belongs is the first complexity level; if the score of the task complexity is greater than 2 and less than 4, the complexity level to which the task complexity belongs is the second complexity level; if the score of the task complexity is greater than or equal to 4, the complexity level to which the task complexity belongs is the third complexity level.
[0038] In the embodiment, the team experience level includes a first-level team, a second-level team and a third-level team, and the method for obtaining the stage adaptation score based on the complexity level to which the task complexity belongs and the team experience level is as follows: the matching degree of the first complexity level and the first-level team is the first level, which is low risk, and the stage adaptation score is 1; the matching degree of the first complexity level and the second-level team is the second level, which is medium risk and needs to be monitored, and the stage adaptation score is 0.8; the matching degree of the first complexity level and the third-level team is the third level, which is high risk and needs to be prewarned, and the stage adaptation score is 0.6; the matching degree of the second complexity level or the third complexity level and any level team is the fourth level, which is medium risk and needs to be monitored, and the stage adaptation score is 0.8.
[0039] In some embodiments of the embodiment, the calculation formula for obtaining the capability adaptation degree is: Capability adaptation degree = Σ (individual task matching degree x task weight) / total task number.
[0040] In some embodiments of the embodiment, the method for obtaining the risk score is: Risk score = task complexity x time urgency x (1 - member experience matching degree).
[0041] In some embodiments of the embodiment, the method for obtaining the prewarning indication corresponding to the team health degree based on the score of the team health degree is: Set the prewarning index: Red prewarning: the team health degree is less than or equal to 0.6, which may exist a high-risk task; Yellow prewarning: the team health degree is greater than 0.6 and less than 0.8, which may exist a medium-risk task; Green state: the team health degree is greater than 0.8, which may have no risk task.
[0042] Step S4: strategy recommendation based on the prewarning indication corresponding to the team health degree.
[0043] In some embodiments of the embodiment, if the prewarning indication corresponding to the team health degree is red prewarning, it is recommended to strengthen the architecture review frequency, suggest to increase the participation of experts, and prompt to decompose complex tasks, if the prewarning indication corresponding to the team health degree is yellow prewarning and green prewarning, it is recommended to recommend parallel testing division, suggest to establish a problem rapid response mechanism and prompt to strengthen progress synchronization.
[0044] According to the second aspect of the present application, as Figure 2 shown, the embodiment provides an OTX diagnosis sequence intelligent development system based on workflow context awareness, which comprises: A recognition module for recognizing the current OTX diagnosis sequence development stage; a task complexity acquisition module, configured to acquire a task complexity of a current OTX diagnosis sequence development stage; a team collaboration context real-time perception module, configured to perform team collaboration context real-time perception based on the task complexity, and acquire a team health degree and an early warning indication corresponding to the team health degree; a recommendation module, configured to perform strategy recommendation based on the early warning indication corresponding to the team health degree.
[0045] Specifically, the embodiments correspond to the above-mentioned method embodiments one by one, and the functions of each module have been described in detail in the corresponding method embodiments, thus will not be described one by one.
[0046] According to a third aspect of the present application, the embodiments provide a computer readable storage medium having a computer program stored thereon, the computer program comprising executable instructions which, when executed by a processor, implement the above-mentioned method.
[0047] The present application can implement all or part of the above-mentioned method, and can also be completed by a computer program instructing related hardware. The computer program can be stored in a computer readable storage medium, and the computer program can implement the steps of each method embodiment when executed by a processor. The computer program includes computer program code, which can be in the form of source code, object code, executable files or some intermediate forms. The computer readable medium can include any entity or system capable of carrying computer program code, recording medium, U disk, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signal, telecommunication signal and software distribution medium, etc. It should be noted that the content of the computer readable medium can be appropriately increased or decreased according to the requirements of legislation and patent practice in the jurisdiction, for example, in some jurisdictions, according to legislation and patent practice, the computer readable medium does not include electrical carrier signals and telecommunication signals.
[0048] According to a fourth aspect of the present application, an electronic device is provided, such as Figure 3 as shown, comprising: one or more processors; a memory for storing executable instructions of the processor, when the executable instructions are executed by the one or more processors, the one or more processors implement the above-mentioned method.
[0049] The electronic device is in the form of a general-purpose computing device. The components of the electronic device can include but are not limited to the above-mentioned at least one processor, the above-mentioned at least one memory, a bus connecting different system components including the memory and the processor.
[0050] The processor can be a central processing unit (CPU), and can also be other general-purpose processors, digital signal processors (DSP), application specific integrated circuits (ASIC), field programmable gate arrays (FPGA) or other programmable logic devices, discrete gates or transistor logic, discrete hardware components, etc. The general-purpose processor can be a microprocessor or the processor can be any conventional processor. The processor is a control center of the computer system and connects all parts of the computer system through various interfaces and lines.
[0051] The memory can be used to store computer programs and / or modules, and the processor can realize various functions of the computer system by running or executing the computer programs and / or modules stored in the memory and calling data stored in the memory. The memory can mainly include a program storage area and a data storage area, wherein the program storage area can store an operating system, at least one application program required by a function (such as a sound playing function, an image playing function, etc.); and the data storage area can store data created according to the use of the mobile phone (such as audio data, video data, etc.). In addition, the memory can include a high-speed random access memory, and can also include a nonvolatile memory, such as a hard disk, a memory, a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, at least one disk storage device, a flash memory device, or other volatile solid-state memory devices.
[0052] Those skilled in the art should understand that the embodiments of the present application can be provided as a method, a system, a server or a computer program product. Therefore, the present application can take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Moreover, the present application can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage and memory, etc.) including computer-usable program code.
[0053] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), servers and computer program products according to the embodiments of the present application. It should be understood that each flow and / or block in the flowcharts and / or block diagrams, and the combination of the flows and / or blocks in the flowcharts and / or block diagrams can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing devices generate a means for implementing the functions specified in the flowcharts and / or block diagrams. Figure 1 one or more flows and / or blocks. Figure 1 one or more flows and / or blocks.
[0054] These computer program instructions can also be stored in a computer readable memory capable of directing the computer or other programmable data processing devices to work in a specific manner, so that the instructions stored in the computer readable memory produce a manufactured product including an instruction system, which implements the functions specified in the flowcharts and / or block diagrams. Figure 1 one or more flows and / or blocks. Figure 1 one or more flows and / or blocks.
[0055] These computer program instructions can also be loaded into a computer or other programmable data processing device, so that a series of operation steps are performed on the computer or other programmable device to produce a computer implemented process, so that the instructions executed on the computer or other programmable device provide steps for implementing the functions specified in the flowcharts and / or block diagrams. Figure 1 one or more flows and / or blocks. Figure 1 one or more flows and / or blocks.
[0056] It should be understood that the sequence of the steps in the above embodiments does not mean the order of execution, and the execution order of the processes should be determined according to their functions and inherent logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.
[0057] In the above embodiments, the description of each embodiment has its own focus, and the parts not described or recorded in a certain embodiment can be referred to the related description of other embodiments.
[0058] The above, the above embodiments are only used to illustrate the technical solutions of the present application, and not to limit them; although the present application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that they can still modify the technical solutions recorded in the foregoing embodiments, or make equivalent replacement for part of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present application.
Claims
1. A workflow context-aware based OTX diagnosis sequence intelligent development method, characterized in that, The method comprises the following steps: identifying the current OTX diagnostic sequence development stage; obtaining the task complexity of the current OTX diagnostic sequence development stage; based on the task complexity, real-time sensing of the team collaboration situation is performed to obtain the team health degree and the corresponding early warning indication of the team health degree; based on the corresponding early warning indication of the team health degree, a strategy recommendation is made.
2. The method of claim 1, wherein, The identification of the current OTX diagnostic sequence development stage comprises the following steps: implanting an event listener in the OTX development environment to capture the current operation events of the developer in the OTX environment; using a preset time threshold as a time window, real-time operation features are obtained; using a hidden Markov model to identify the current OTX diagnostic sequence development stage.
3. The method of claim 2, wherein: the current operation events include graphical design operation events, parameter configuration operation events, debugging operation events and optimization operation events; the current operation features include the graphical editing operation frequency corresponding to the graphical design operation events, the parameter configuration operation density corresponding to the parameter configuration operation events, the debugging operation concentration corresponding to the debugging operation events, and the optimization operation proportion corresponding to the optimization operation events; the method for identifying the current OTX diagnostic sequence development stage using a hidden Markov model comprises the following steps: inputting the current operation features into the hidden Markov model for stage identification, outputting the current OTX diagnostic sequence development stage, performing confidence calculation, and taking the state corresponding to the highest confidence score as the current OTX diagnostic sequence development stage.
4. The method of claim 1, wherein, The method for obtaining the task complexity of the current OTX diagnostic sequence development stage comprises the following steps: obtaining the task complexity based on the weighted sum of the control flow complexity and the data flow complexity; the method for obtaining the control flow complexity comprises the following steps: parsing an abstract syntax tree in the current OTX diagnostic sequence development stage, wherein the abstract syntax tree comprises a loop nesting depth, a branch complexity and a concurrency complexity, the loop nesting depth is the maximum loop nesting level, the branch complexity is the product of the number of if-else nodes and the branch coefficient, and the concurrency complexity is the product of the number of parallel execution blocks and the concurrency weight; obtaining the control flow complexity by weighted sum of the loop nesting depth, the branch complexity and the concurrency complexity; the method for obtaining the data flow complexity comprises the following steps: parsing the data dependency relationship in the current OTX diagnostic sequence development stage, wherein the data dependency relationship comprises a variable dependency depth, a data type conversion complexity and a data access density, the variable dependency depth is the longest data dependency chain length, the data type conversion complexity is the product of the number of explicit type conversions and the conversion weight, and the data access density is the number of read-write operations divided by the number of code lines; obtaining the data flow complexity by weighted sum of the variable dependency depth, the data type conversion complexity and the data access density.
5. The method of claim 1, wherein, The method for obtaining the task complexity of the current OTX diagnostic sequence development stage comprises the following steps: obtaining the stage adaptation score, the ability adaptation degree and the risk score based on the task complexity; obtaining the team collaboration health degree by weighted sum of the stage adaptation score, the ability adaptation degree and the risk score; The score based on the team health degree is used to obtain a corresponding early warning indication of the team health degree, if the team health degree is less than or equal to 0.6, a red early warning exists; if the team health degree is greater than 0.6 and less than 0.8, a red early warning exists; if the team health degree is greater than or equal to 0.8, a green early warning exists.
6. The method of claim 5, wherein: The method for obtaining the stage adaptation score, the capability adaptation degree and the risk score based on the task complexity is: The score range of the task complexity is set according to each complexity level, the complexity level to which the task complexity belongs is determined according to the score of the task complexity, and the stage adaptation score is obtained according to the complexity level to which the task complexity belongs and the team experience level; The score of the capability adaptation degree is: Capability adaptation degree = Σ (individual task matching degree × task weight) / total task number; The score of the risk score is: Risk score = task complexity × time urgency × (1 - member experience matching degree).
7. The method of claim 5, wherein, The strategy recommendation based on the early warning indication corresponding to the team health degree includes: If the early warning indication corresponding to the team health degree is a red early warning, it is recommended to strengthen the architecture review frequency, it is suggested to increase the participation of experts, and it is prompted to decompose complex tasks, if the early warning indication corresponding to the team health degree is a yellow early warning and a green early warning, it is recommended to divide the parallel test, it is suggested to establish a problem rapid response mechanism, and it is prompted to strengthen the progress synchronization.
8. A workflow context-aware based OTX diagnosis sequence intelligent development system, characterized in that, The system includes: An identification module for identifying the current OTX diagnosis sequence development stage; A task complexity acquisition module for acquiring the task complexity of the current OTX diagnosis sequence development stage; A team collaboration context real-time perception module for real-time perception of the team collaboration context based on the task complexity, obtaining the team health degree and the early warning indication corresponding to the team health degree; A recommendation module for strategy recommendation based on the early warning indication corresponding to the team health degree.
9. A computer readable storage medium having stored thereon a computer program, characterized in that, The computer program includes executable instructions, when the executable instructions are executed by a processor, the method of any one of claims 1-7 is implemented.
10. An electronic device, comprising: It includes: One or more processors; A memory for storing executable instructions of the processor, when the executable instructions are executed by the one or more processors, the one or more processors implement the method of any one of claims 1-7.