Block chain practical operation platform and practical training method based on judgeable program

Abstract

The invention discloses a block chain practice operation platform and a practical training method, and relates to a block chain practice operation platform and a practical training method based on a judgeable program, the block chain practice operation platform comprises a task list module, a learning guidance module and a transaction pool module, the task list module comprises a case demand analysis port and a case application design port, the case demand analysis port comprises demand case import, demand case analysis, case diagram design and sequence diagram design, the demand case analysis comprises case names, case description, participants, preconditions, postconditions and event stream description, a judgment module is arranged in the main event stream, an operation platform is constructed by adopting an intelligent judgment type program, and the operation platform is connected with the case demand analysis port. Condition judgment and result analysis are carried out on each process step, when an abnormality occurs, the abnormality can be returned and prompted, and the process trend can be judged and selected according to the process progress and a specific event, so that a learner can be better helped to carry out practical operation drilling, and related operations of the block chain can be more comprehensively mastered.

Description

Technical Field

[0001] The present invention relates to a blockchain practice operation platform and a training method, and relates to a blockchain practice operation platform and a training method based on a predicable program. Background Art

[0002] Blockchain is a decentralized distributed ledger that is tamper-proof, secure and reliable. It combines distributed storage, peer-to-peer transmission, consensus mechanism, cryptography and other technologies to record transactions and information through a growing data block chain to ensure data security and transparency.

[0003] In order to promote and participate in the application and development of blockchain, more professional training is needed for students or users. Most of the existing training is achieved through an operating platform. The teacher edits the teaching content through the operating platform, and the learner learns through the operating platform. The teacher and the student can communicate data. According to the tasks assigned by the teacher, the student can perform practical training, thereby combining theory with practice and better learning blockchain knowledge. However, the existing operating platforms are mostly simple content combinations, and the practical training operations are only based on the analysis and operation of simple case modules, and then look at the returned results. When the operation results have error feedback, multiple leading operations are required for investigation, and it is difficult to quickly find the problem points. Therefore, a blockchain practice operation platform and training method based on a predicated program are proposed to solve the problems existing in the existing technology. Summary of the invention

[0004] The purpose of the present invention is to provide a blockchain practice operation platform and training method based on a judgeable program in response to the defects or shortcomings in the prior art. The operation platform is constructed using an intelligent judgement program, especially in the use case analysis step, a main event flow and an abnormal event flow are set, and conditional judgment and result analysis are performed on each process step. When an abnormality occurs, it will return in time and give a prompt, and the process direction can be selected according to the process progress and specific events, so as to better help learners conduct practical exercises and more comprehensively master the relevant operations of blockchain.

[0005] To achieve the above-mentioned purpose, the present invention adopts the following technical scheme: a blockchain practice operation platform and training method based on a predicable program, which includes a task list module, a learning guidance module, and a transaction pool module. The three modules are parallel parent modules, and are divided into a teacher operation end and a student operation end according to different login account permissions. The task list module includes a case demand analysis port and a case application design port. The learning guidance module includes specific function operation guidance. The transaction pool module includes an EOS blockchain operation port, an ETH blockchain operation port, and a Fabric blockchain operation port.

[0006] Furthermore, the case requirement analysis port includes requirement use case import, requirement use case analysis, use case diagram design, and sequence diagram design. The teacher operation end adds requirement cases through requirement use case import, and the student operation end imports cases to understand the task situation. The use case situation is described and analyzed in the requirement use case analysis, the analysis situation is saved, and the use case diagram design is entered. Finally, the use case diagram is sorted to complete the sequence diagram design.

[0007] Furthermore, the requirement use case analysis includes the use case name, use case description, participants, preconditions, postconditions, and event flow description. The main event flow contains a determination module, which is divided into a main event flow description and an abnormal event flow description. When an abnormal event occurs in the main event flow, the abnormal event flow is entered, and the abnormal event flow performs a return operation.

[0008] Furthermore, the case application design includes analyzing the contract subject, allocating the contract subject, and blockchain execution data chain. The contract subject analysis needs to select the contract subject of the corresponding case according to the results of the demand analysis. When the contract subject analysis is confirmed, the contract subject can be selected. According to the determined contract subject, the team members are selected. That is, the task of allocating the contract subject is completed and the blockchain execution data chain task link is entered. Sort by blockchain adaptability, click the blockchain name, and select the blockchain with the highest adaptability to the corresponding case.

[0009] Furthermore, the blockchain execution data on-chain includes EOS blockchain on-chain, ETH blockchain on-chain, and Fabric blockchain on-chain. All on-chain operations need to be carried out at the transaction pool port. The data filled in for EOS blockchain on-chain is the number of people in the group. The team leader defines the super node packaging order and submits to complete the pre-chain operation. ETH blockchain on-chain does not require operations in the transaction pool. Fabric blockchain on-chain includes creating an alliance, adding a blockchain, and joining an alliance. After the operation of joining the alliance is completed, the transaction can be viewed.

[0010] Furthermore, the case application design also includes a contract rule design module, which includes a contract library and a rule library. The contract library has built-in case contract subject data, and the rule library has built-in rule data.

[0011] Furthermore, the blockchain execution data uploading also includes a main data analysis uploading port, by selecting the contract main data, adding the contract main data to the contract library, and adding the data in the contract main library to the subject to be analyzed, completing the entry of the main data, and uploading the data after the data is added. The rule library includes displaying the use case contract, action, status, and main data. The main data is the primary selection rule, followed by the status, and ends with an action or use case contract.

[0012] Furthermore, the case application design also includes deploying a smart contract module, which includes a testing smart contract module. The information corresponding to the requirement description is entered according to the input window. After the entry is completed, the smart contract is deployed. After the contract deployment is completed, the testing smart contract module will be entered. The testing smart contract module includes running contracts, contract diagnosis, and operation logs.

[0013] Furthermore, the testing smart contract module also includes a module for viewing a smart contract design certificate. After completing the smart contract test, a contract certificate can be generated. After the contract certificate is generated, the study and operation of the case are completed.

[0014] After adopting the above technical scheme, the beneficial effects of the present invention are as follows: an operating platform is constructed by adopting an intelligent judgment program, especially in the use case analysis step, a main event flow and an abnormal event flow are set, and conditional judgment and result analysis are performed on each process step. When an abnormality occurs, it will return in time and give a prompt, and the process direction can be selected according to the process progress and specific events, so as to better help learners to conduct practical exercises and more comprehensively master the relevant operations of blockchain. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0016] Figure 1 It is the case demand analysis port navigation view in the present invention;

[0017] Figure 2 It is the demand use case analysis interface window in the present invention;

[0018] Figure 3 It is the use case diagram design interface window in the present invention;

[0019] Figure 4 It is the sequence diagram design interface window in the present invention;

[0020] Figure 5 It is the interface window for analyzing the main body of the contract in the present invention;

[0021] Figure 6 It is the interface window for allocating the contract subject in the present invention;

[0022] Figure 7 It is the blockchain execution data uplink interface window in the present invention;

[0023] Figure 8It is the interface window for designing contract rules in the present invention;

[0024] Fig. 9 It is the smart contract interface window deployed in the present invention;

[0025] Fig.10 It is the test smart contract interface window in the present invention;

[0026] Fig.11 It is the operation log interface window in the test smart contract of the present invention;

[0027] Fig.12 It is the interface window for viewing the smart contract design certificate in the present invention;

[0028] Fig.13 It is a schematic diagram of the operating process framework of the present invention;

[0029] Fig.14 This is a schematic diagram of the demand use case flow in the present invention;

[0030] Fig.15 This is a schematic diagram of the main data analysis and chain-up process in the present invention;

[0031] Fig.16 A schematic diagram of the process flow of designing contract rules in the present invention;

[0032] Fig.17 This is a schematic diagram of the process of testing smart contracts in the present invention. DETAILED DESCRIPTION

[0033] See also Figure 1-Figure 13 As shown, the technical solution adopted in this specific implementation is: it includes a task list module, a learning guidance module, and a transaction pool module. The three modules are parallel parent modules, and are divided into a teacher operation end and a student operation end according to different login account permissions. In the operation platform described in this embodiment, teaching operations are mainly performed from the three modules. The content operated by the student operation end will be synchronized to the teacher operation end. The teacher can view the teaching content and progress after logging in through his account, which has better interactivity;

[0034] In this embodiment, the task list module includes a case demand analysis port and a case application design port. The case can be viewed and selected by entering from the demand analysis port, and the case application port can be entered to input analysis data according to the judgment rules. The saved use case analysis can be viewed, and multiple case use case analyses can be added. In this step, it is subject to the constraints of the intelligent judgment logic, and it can be found whether there is abnormal data analysis before all analysis results are obtained, so that the data can be re-judged and analyzed in time. This operation is also a simulation of the actual operation, and it can respond in time when the problem is encountered in the actual operation, and clarify the steps where the problem may occur. Taking the vending machine as an example, when the purchase of goods occurs but the goods cannot be obtained, the cause can be quickly determined according to the feedback data from the background, and the correct response can be made;

[0035] The learning guidance module includes specific function operation guidance. Before carrying out specific teaching operations, students can obtain the specific methods of all operations in this module and review them repeatedly during the learning process to ensure correct operation of the system and obtain better learning results;

[0036] The transaction pool module includes an EOS blockchain operation port, an ETH blockchain operation port, and a Fabric blockchain operation port, and specific data on-chain operations are performed through the three blockchain operation ports.

[0037] More specifically, the case demand analysis port includes demand use case import, demand use case analysis, use case diagram design, and sequence diagram design. The teacher operation end adds demand cases through demand use case import, and the student operation end imports cases to understand the task situation. In the demand use case analysis, the use case situation is described and analyzed, the analysis situation is saved, and the use case diagram design is entered. Finally, the use case diagram is sorted, the sequence diagram design is completed, and the task of this link is completed;

[0038] In this embodiment, view the demand use case import, select a use case, and take the vending machine as an example. According to the provided background, analyze the problems or industry needs involved in the case background. After viewing, click Finish in the upper right corner to enter the next task.

[0039] Enter the demand use case analysis task link. The demand use case analysis includes demand description and case use case analysis. The case use case analysis is to describe the use case based on the above demand description. The demand use case analysis includes the use case name, use case description, participants, preconditions, postconditions, and event flow description. The main event flow contains a judgment module, which is divided into the main event flow description and the abnormal event flow description. When an abnormal event occurs in the main event flow, enter the abnormal event flow, and the abnormal event flow performs a return operation. In this embodiment, the event description is the core part of the entire analysis link. Through the main event flow and the abnormal event flow The distinction can quickly enter the respective links when different events occur. For example, there is a vending machine num. When the vending machine is in normal operation, user A buys a drink on the vending machine (main event flow). If the operation status is abnormal, the user cannot use it (abnormal event flow). When user A does not select a product for 5 minutes, it returns to the system home page (abnormal event flow). After user A selects a product, user A can select the product on the vending machine and pay the amount. If the amount is not paid within 5 minutes, the transaction is exited (abnormal event flow). If the payment is made, the system verifies the amount. When the product amount is greater than When the payment amount is paid (abnormal event flow), the transaction fails and the system returns to the commodity selection state. When the commodity amount is less than or equal to the payment amount (main event flow), the transaction is successful and the system verifies whether the commodity has expired. When the commodity shelf life is abnormal (abnormal event flow), the system returns to the commodity selection state. When the commodity shelf life is normal (main event flow), the system performs the shipment operation. In the above transaction process, when the normal event flow is in progress, if an abnormal event occurs, the abnormal event flow processing process will be entered, that is, the system will be returned to close the transaction. The traditional operation teaching platform lacks the event description link in this embodiment, and cannot simulate such situations during teaching. Therefore, it is difficult to quickly find the problem when encountering problems in practice. In this embodiment, due to the actual operation drills through the event flow classification method, students can make correct responses in time according to the abnormal situations fed back by the system when encountering actual problems. The specific operation method is as follows: In the operation platform, enter the demand use case analysis operation window, and fill in the corresponding use case name, use case description, participants, preconditions, postconditions, and event flow description content in the case use case analysis table according to the case selected in the previous step. Specifically, the use case name is: select commodity;

[0040] Use case description: This use case allows user A to purchase a beverage from vending machine num in order to perform subsequent operations;

[0041] Participants: A,num;

[0042] Precondition: Before starting this use case, num runs well. When A enters the system, this use case starts to execute.

[0043] Post-condition: If the use case ends successfully, enter the payment process;

[0044] Event flow description: Set the name of the main event flow. You can set multiple main event flows as the main judgment logic conditions. For example, in main event flow 1, user A selects a product at the vending machine num. If he does not select a product within 5 minutes, he will enter the abnormal event flow e1. In main event flow 2, if he selects a product, he will enter the payment operation and this use case will end. Set the abnormal event flow and return to the system main page. The use case ends. After each main event flow event is judged to enter the abnormal event flow, it will return to the system main page and end the use case.

[0045] When each use case description is completed, the name of the use case will be displayed on the main page, and it can be viewed at any time and the next use case can be added.

[0046] The following is further explained through specific use cases:

[0047] Product selection use case

[0048] Use case name: Select product

[0049] Use case description: This use case allows user A to purchase a beverage from vending machine num in order to perform subsequent operations.

[0050] Participants: A, num

[0051] Precondition: Before starting this use case, num runs well. When A enters the system, this use case starts to execute.

[0052] Post-condition: If the use case ends successfully, enter the payment process;

[0053] Main event flow:

[0054] User A selects a product at vending machine num. If he does not select any product within 5 minutes, the abnormal event flow e1 will be entered;

[0055] If you select a product, you will enter the payment process and this use case will end.

[0056] Abnormal event flow e1:

[0057] Return to the system main page and the use case ends;

[0058] Payment Operation Use Case

[0059] Use case name: Payment operation

[0060] Use case description: This use case allows user A to pay for vending machine num in order to perform subsequent operations.

[0061] Participants: A, num

[0062] Precondition: Before starting this use case, user A selects a product and the use case starts to execute;

[0063] Postcondition: If the use case ends successfully, enter the shelf life judgment process;

[0064] Main event flow:

[0065] User A performs payment operation;

[0066] The system determines whether the payment amount is paid within 5 minutes. If not, it enters the abnormal event flow e1;

[0067] If a payment operation is performed, the system determines whether the amount is sufficient. If the amount is sufficient, the system enters the shelf life determination use case and the execution of this use case ends.

[0068] Abnormal event flow e1:

[0069] The system exits the transaction and returns to the system main page, and the use case ends;

[0070] Shelf life judgment use case

[0071] Use case name: Shelf life determination

[0072] Use case description: This use case allows the vending machine num to determine whether the shelf life of the product is sufficient for subsequent operations

[0073] Participants: num

[0074] Precondition: Before starting this use case, the vending machine num determines that the payment amount is sufficient, and the use case starts to execute;

[0075] Post-condition: If the use case is successfully completed, enter the shipping process;

[0076] Main event flow:

[0077] The system enters the product expiration date judgment. If the product is not within the expiration date, the abnormal event flow e1 is executed;

[0078] If the product is within the shelf life, the product will go through the sales process and this use case ends.

[0079] Abnormal event flow e1:

[0080] The system exits the transaction and the use case ends;

[0081] Selling goods use case

[0082] Use case name: Selling goods

[0083] Use case description: This use case allows the vending machine to perform delivery operations to complete the transaction;

[0084] Participants: A, num

[0085] Precondition: Before starting this use case, the vending machine num determines that the product has a normal shelf life, and the use case starts to execute;

[0086] Postcondition: If the use case ends successfully, the transaction is successful;

[0087] Main event flow:

[0088] The vending machine num performs the shipment operation and the transaction is completed;

[0089] In the above use cases, by setting preconditions and coordinating event flows, intelligent judgment can be made, which can effectively complete transaction behaviors and quickly respond to abnormal event flows. This allows students to clearly understand the possible problems in each link, and thus have a more comprehensive grasp of the demand use case analysis link;

[0090] When the demand use case analysis is completed, enter the use case diagram design phase. Drag the icon on the left to the right to complete the design of the use case diagram. Each use case description corresponds to a use case diagram. Click Save after completing the design of a use case diagram. When designing the use case diagram, it should be noted that each use case needs to use a different use case diagram to ensure that the intention of each use case can be clearly indicated. After completing the task, click the Finish button in the upper right corner to enter the next task;

[0091] After the use case diagram design is completed, enter the sequence diagram design phase. According to the sequence of use case events, drag the icon on the left to the right to complete the design of the sequence diagram. Each use case description corresponds to a sequence diagram. Click Save after completing the design of each sequence diagram. After completing the task, click the Done button in the upper right corner to enter the next task. Corresponding to the aforementioned vending machine, it may include product selection use case diagram, payment operation use case diagram, retention period judgment use case diagram, and product selling use case diagram. The case demand analysis phase has been completed. In this phase, learners analyze and learn the use cases through a predicate program, and through intelligent judgment logic, they can more effectively grasp the links where problems may occur, so that they can respond quickly in subsequent operations.

[0092] More specifically, the case application design includes analyzing the contract subject, allocating the contract subject, and blockchain execution data chain. The contract subject analysis needs to select the contract subject of the corresponding case according to the results of the demand analysis. When the contract subject analysis is confirmed, the contract subject can be selected. According to the determined contract subject, the team members are selected, that is, the task of allocating the contract subject is completed to enter the blockchain execution data chain task link. According to the blockchain adaptability sorting, click the blockchain name, and select the blockchain with the highest adaptability of the corresponding case. In this link, the contract subject analysis is to select the contract subject of this case according to the results of the analysis requirements. Click Add to select the contract subject in the subject library. Click OK after clicking the contract subject selection, that is, the contract subject is successfully selected. Then select the saved subject in the subject library, and the subject can be added from the subject library to the upper contract subject. Click Delete Subject and then click Save to verify whether the selected contract subject is correct. If it is correct, it is saved successfully. After completing the task, click the Finish button to enter the next task;

[0093] The assignment of the contract subject is to select the team members according to the determined contract subject, click to confirm the assignment, and after confirming that the assignment is successful, it cannot be assigned again. After completing the task, click the completion button in the upper right corner to proceed to the next task;

[0094] So far, the analysis and allocation of the contract entities have been completed. Through this link, students can master the selection of contract entities and make correct allocations based on the analysis.

[0095] To be more specific, the blockchain execution data on-chain includes EOS blockchain on-chain, ETH blockchain on-chain, and Fabric blockchain on-chain. All on-chain operations need to be carried out at the transaction pool port. The data filled in for EOS blockchain on-chain is the number of people in the group. The team leader defines the super node packaging order and submits to complete the pre-chain operation. ETH blockchain on-chain does not require operations in the transaction pool. Fabric blockchain on-chain includes creating an alliance, adding a blockchain, and joining an alliance. After joining the alliance, you can view the transaction. In this embodiment, after the contract subject is allocated, it is necessary to sort by blockchain adaptability. Click the blockchain name and select the blockchain with the highest adaptability in this case. Click Confirm Selection to successfully select the blockchain. After confirming the selection, it cannot be changed again. The adapted blockchains in this case are from high to low: EOS, ETH, Fabric. Students learn to analyze and establish different regional chains and on-chain operations in this module.

[0096] More specifically, the blockchain execution data on-chain also includes a main data analysis on-chain port. By selecting the contract main data, the contract main data is added to the contract library, and the data in the contract main library is added to the subject to be analyzed, the main data is entered, and the data is uploaded to the chain after the data is added. After the on-chain Hash is generated, the on-chain data on the right is dragged to the left window, and OK is clicked to check whether the on-chain data is correct. After completing the task, click the completion button in the upper right corner to enter the next task. At the same time, the blockchain on which the executed data is uploaded is selected for accounting. In summary, the main data analysis and on-chain process is to enter entity data and attribute data. Entity data includes subsystem data, role data, and entity data. Attribute data includes identity data, account data, action data, and system data.

[0097] Take the vending machine as an example. In the main data analysis and chain window, select the subject to be analyzed, which is divided into users and vending machines. After selecting the user as the analysis subject, click the minus sign to delete the subject data, and then click the plus sign to add the subject data to the subject to be analyzed, such as machine operation status, product selection time, payment waiting time, and payment amount. After the selection is completed, click Save. In this case, the payment amount is selected as the main data. Which subject is selected on the left, the main data is added to the corresponding subject. Finally, click Data Chain to chain the selected main contract data. Then select the vending machine as the contract subject, select the machine operation status, product selection time, product selection information, payment waiting time, product retention period and shipment status as the main data. Similarly, save and chain the data. When the chain is completed, click Generate. After generating the chain Hash, drag the chain data on the right to the left window, click OK, and check whether the chain data is correct. For example, after the user contract subject data is chained, generate the payment amount Hash, drag the payment amount module into the left inspection window, click OK for detection, and after completion, select the blockchain where the executed data is chained for accounting;

[0098] Specifically, there are three optional operations after the chain is successfully uploaded. First, click the transaction pool on the left, click the EOS blockchain, click competition, and click package to package all the chain data. Different members of the group will package the super nodes in the order assigned when the contract subject is assigned. After completion, you can select the chain details and accounting details options on the corresponding items. Click on the chain details to view the chain data and data Hash. Click on the accounting details to view the accounting members, accounting time, and accounting status. At the same time, there is a return option above the project bar. Click to return to the upper interface. The upper interface has a packaging log function button. Enter to view the packaging log;

[0099] Second, click on the transaction pool on the left, click on the ETH blockchain, click on competition, click on the start competition option, click on the answer according to the question, and start the competitive accounting. After completion, you can select the chain details and competition details on the project bar. Click on the chain details to view the chain data and data hash. Click on the competition details, the accounting situation is the specific details of the competitive accounting, and you can view the accounting members, accounting time, and accounting status;

[0100] Third, click the transaction pool on the left, click Fabric blockchain, click Alliance details, place the mouse on the consensus sorting service to see the transactions to be packaged, click Package to package the transaction, click Transaction details to view business data, click L or S to view transaction data, and click Chain details to view chain data and data Hash.

[0101] More specifically, the case application design also includes a contract rule design module, which includes a contract library and a rule library. The contract library has built-in case contract subject data, and the rule library has built-in rule data. In order to realize the operation of smart contracts, a contract rule module is designed to comprehensively apply various contract rules. Learners can choose different contracts and rules according to their needs, and they will take effect in subsequent operations, so as to better perform predictable learning operations. In summary, the contract rule design process is to call according to the rules from the data set, state library, and action library, and also output according to the data set, state library, and action library data;

[0102] Take the vending machine as an example. After entering the design contract rule window, the upper window prompts the contract name, and the lower window shows the contract library and rule library. Click Add to select a contract subject from the commodity, payment operation, retention period judgment and sold commodity. Click OK and save to complete the selection of a contract subject. You can add contract subjects repeatedly, and you can add and delete after adding the contract subject. Click Delete to delete the contract subject. Click Add above the contract subject to add the contract subject to the contract name above, so as to prepare for the subsequent addition of contract rules.

[0103] After the contract body is added, enter the rule design. The rule base includes displaying the use case contract, action, status, and subject data. The subject data is the primary selection rule, followed by the status, and ends with the action or use case contract.

[0104] Click on the selected contract subject, and the rule base option will appear. Select the required rules from the rule base below. The use case contract in the rule base is the first option, which includes product selection, payment operation, retention period judgment and product sale options; action options include end and refund; status options include true and false. After selecting the contract subject, you can choose to add rule items. The number of rules can be added by clicking the add button. At the same time, there is a subject data filling item below to edit the specific content of the analysis subject, such as adding specific data for the payment amount. After all selection operations are completed, save and complete the contract rule design. The following is an example of contract rule design with vending machine as the subject:

[0105] The contract name is "Select Product". The contract subject includes the machine operation status, product selection time, and product selection information. Rule 1: The contract subject is the machine operation status, the rule status is false, and the rule action is end. Rule 2: The contract subject is the machine operation status, the rule status is true, and the contract subject is the product selection time. The rule status is false, and the rule action is end. Rule 3: The contract subject is the machine operation status, the rule status is true, and the contract subject is the product selection time. The rule status is true, and the contract subject is the product selection information. The rule status is true. Enter the payment operation rules, complete the design of a specific contract rule for a contract name, and click Save. The design logic of other contract subject rules is the same. They all set multiple state logics to cooperate with rule operations for design to ensure that all possible situations can be covered and the best training effect can be obtained.

[0106] More specifically, the case application design also includes a smart contract deployment module, which is applied in accordance with the aforementioned contract rules. The smart contract deployment module includes a smart contract test module. The corresponding requirement description information is entered in the input window. After the entry is completed, the smart contract is deployed. After the contract is deployed, the test smart contract module will be entered. The test smart contract module includes running contracts, contract diagnosis, and operation logs. Clicking on the run contract will start running the contract. Clicking on the contract diagnosis can detect whether the contract rules are designed correctly. Clicking on the operation log can view the correct and incorrect operation logs for this and the last time. Please enter according to the prompts when testing the contract. In the operation log, you can view the scores obtained by the rules you set. When running the smart contract, you need to run each rule you set according to the complete path. After completing the task, click the finish button in the upper right corner to enter the next task. It should be noted that the entire transaction and status processing is automatically completed by the built-in smart contract system at the bottom of the blockchain, which is transparent and cannot be tampered with.

[0107] Specific examples are as follows:

[0108] Enter the smart contract deployment module, and four contract icons will be displayed, including product selection, payment operation, retention period judgment and product sale. Select the contract icon, click the deployment icon below to start deploying the smart contract, and enter the specific contract data deployment filling interface, which reflects the product number, name, unit price, production date and retention period. The filling items are product selection time, payment waiting time and account balance. The filling items are the aforementioned entered contract rules. The specific details of the product have been completed in the data entry in the previous link. After filling in, click Start Deployment, and click Finish to enter the next link;

[0109] After the smart contract is deployed, enter the test step. There are three function options in the window interface: run contract, contract diagnosis and operation log. Click Run Contract to start running the contract. Click Contract Diagnosis to detect whether the contract rules are designed correctly. Click Operation Log to view the correct and incorrect operation logs of this and last time. Please enter according to the prompts when testing the contract. In the operation log, you can view the scores obtained by the rules you set. When running the smart contract, you need to run each rule you set according to the complete path. After completing the task, click the Finish button in the upper right corner. In summary, the process of testing the smart contract is to enter the initial data, function connection, and contract rule validator to verify the contract. The contract rule validator includes process driver, contract scorer, and log statuser to verify the data, action, status, and threshold.

[0110] More specifically, the testing smart contract module also includes a module for viewing the smart contract design certificate. After completing the smart contract test, a contract certificate can be generated. Specifically, clicking on Generate Contract Certificate will generate a smart contract design certificate based on six dimensions: subject analysis and collection, subject data collection, contract security performance calculation, chain selection, contract rule collection, and testing smart contract. After the contract certificate is generated, the case study and operation are completed.

[0111] In summary, the blockchain practice operation platform and training method based on a decidable program provided in this embodiment includes the following stages and steps:

[0112] Phase 1, the requirements analysis phase, includes use case analysis, use case diagram design, and sequence diagram design;

[0113] Phase 2, the design phase, includes analyzing the contract subject, allocating the contract subject, uploading the regional chain execution data, and uploading the subject data analysis to the chain;

[0114] Phase three, implementation phase, designing contract rules;

[0115] Phase 4, the testing phase, deploys and tests smart contracts.

[0116] The above four stages are the four core parts of the operating platform described in this implementation. Each step has a rigorous logical judgment design. Through the four-stage learning and practical training, students can fully master all aspects of various types of blockchains from construction to transactions. Based on decidable programs, through decidable operation feedback and records in learning and actual operations, students can promptly discover problems in practical applications and make correct responses, thereby better promoting the development of blockchain.

[0117] The above description is only used to illustrate the technical solution of the present invention rather than to limit it. Other modifications or equivalent substitutions made to the technical solution of the present invention by ordinary technicians in this field should be included in the scope of the claims of the present invention as long as they do not depart from the spirit and scope of the technical solution of the present invention.

Claims

1. A blockchain practice operation platform and training method based on a decidable program, characterized by: It includes a task list module, a learning guidance module, and a transaction pool module. The three modules are parallel parent modules and are divided into a teacher operation end and a student operation end according to different login account permissions. The task list module includes a case demand analysis port and a case application design port. The learning guidance module includes specific function operation guidance. The transaction pool module includes an EOS blockchain operation port, an ETH blockchain operation port, and a Fabric blockchain operation port. The case demand analysis port includes demand use case import, demand use case analysis, use case diagram design, and sequence diagram design. The teacher operation end adds demand cases through demand use case import, and the student operation end imports cases to understand the task situation. In the demand use case analysis, the use case situation is described and analyzed, the analysis situation is saved, and the use case diagram design is entered, and finally the use case diagram is sorted to complete the sequence diagram design. The demand use case analysis includes a use case name, a use case description, participants, preconditions, postconditions, and an event flow description. The main event flow contains a judgment module, which is divided into a main event flow description and an abnormal event flow description. When an abnormal event occurs in the main event flow, the abnormal event flow is entered, and the abnormal event flow performs a return operation.

2. A blockchain practice operation platform and training method based on a decidable program according to claim 1, characterized in that: The case application design includes analyzing the contract subject, allocating the contract subject, and blockchain execution data chain. The contract subject analysis needs to select the contract subject of the corresponding case according to the results of the demand analysis. When the contract subject analysis is confirmed, the contract subject can be selected. According to the determined contract subject, the team members are selected. That is, the task of allocating the contract subject is completed and the blockchain execution data chain task is entered. Sort by blockchain adaptability, click the blockchain name, and select the blockchain with the highest adaptability to the corresponding case.

3. A blockchain practice operation platform and training method based on a decidable program according to claim 1, characterized in that: The blockchain execution data on-chain includes EOS blockchain on-chain, ETH blockchain on-chain, and Fabric blockchain on-chain. All on-chain operations need to be carried out at the transaction pool port. The data filled in for EOS blockchain on-chain is the number of group members. The team leader defines the super node packaging order and submits to complete the pre-chain operation. ETH blockchain on-chain does not require operations in the transaction pool. Fabric blockchain on-chain includes creating an alliance, adding a blockchain, and joining an alliance. After joining the alliance, you can view the transaction.

4. A blockchain practice operation platform and training method based on a decidable program according to claim 1, characterized in that: The case application design also includes a contract rule design module, which includes a contract library and a rule library. The contract library has built-in case contract subject data, and the rule library has built-in rule data.

5. According to claim 1, a blockchain practice operation platform and training method based on a decidable program is characterized by: The blockchain execution data uploading also includes a main data analysis uploading port. By selecting the contract main data, the contract main data is added to the contract library, and the data in the contract main library is added to the subject to be analyzed, the main data entry is completed, and the data is uploaded to the chain after the data is added. The rule library includes displaying use case contracts, actions, status, and main data. The main data is the primary selection rule, followed by the status, and ends with an action or use case contract.

6. A blockchain practice operation platform and training method based on a decidable program according to claim 1, characterized in that: The case application design also includes deploying a smart contract module, which includes a testing smart contract module. The information corresponding to the requirement description is entered into the input window. After the entry is completed, the smart contract is deployed. After the contract is deployed, the testing smart contract module will be entered. The testing smart contract module includes running contracts, contract diagnosis, and operation logs.

7. A blockchain practice operation platform and training method based on a decidable program according to claim 1, characterized in that: The testing smart contract module also includes a module for viewing the smart contract design certificate. After completing the smart contract test, a contract certificate can be generated. After the contract certificate is generated, the case study and operation are completed.

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