Fair test method, device and system

Abstract

The invention provides a fairness test method, device and system. According to the method, the current test result is generated based on the current test unique identifier and the current test input, and the smart contract is adopted to determine whether the current test result and the current test input conform to the specification or not in a mapping manner to obtain the judgment result, so that whether the performance of the tester conforms to the expectation or not can be accurately judged; finally, the score value of the target tester is adjusted according to the judgment result, compared with an existing scheme, quantification of the test result can be achieved, the purpose of fair test reward and punishment is achieved, and therefore the problems that according to the existing scheme, quantification of the test result needs to be achieved in a manual import or manual input mode, and the test efficiency is high are solved. And reward and punishment of the fair test cannot be realized.

Description

Technical Field

[0001] The present application relates to the technical field of software testing, and in particular, to a fair testing method, device, and system. Background Art

[0002] In the traditional software testing process, there are indeed some challenges and problems, such as the difficulty in quantifying test results and the lack of corresponding rewards for testers' efforts. These problems may lead to a decline in testers' enthusiasm, a decrease in testing work efficiency, and even an increase in employee turnover rate, thus bringing risks to the project. Even if a quantitative reward mechanism is implemented, problems may still occur, such as testers not receiving corresponding rewards after completing tasks or test task publishers not receiving test results after paying rewards, which damages the rights and interests of both parties and affects the fairness of the testing process. To ensure the fairness of the testing process, that is, testers can definitely obtain corresponding rewards after completing test tasks, and test task publishers can definitely obtain correct test results after giving rewards, we propose a fair testing system based on blockchain. By leveraging the characteristics of the smart contract in blockchain, such as normativity, irreversibility, and non-defaultability, and through specific test process settings, the fairness of the entire execution process is guaranteed, that is, testers can definitely obtain corresponding rewards after completing test tasks and test task publishers can definitely obtain correct test results after giving rewards.

[0003] In the traditional testing scheme, the quantification of test results needs to be achieved through manual import or manual input. Malicious participants can undermine the fairness of the system based on this feature. When the test task publisher marks the correct test result as an incorrect result during the acceptance of the test result, testers will be unable to obtain corresponding rewards. Or when testers' test results are incorrect but are manually modified to correct results, the test task publisher will obtain incorrect results when giving rewards. Both of the above situations will undermine the fairness of the system, and the interests of participants cannot be guaranteed.

[0004] That is, in the existing scheme, the rewards and punishments for fair testing need to achieve the quantification of test results through manual import or manual input, thus it is easy to fail to implement the rewards and punishments for fair testing. Summary of the Invention

[0005] The main purpose of the present application is to provide a fair testing method, device, and system, so as to at least solve the problem that in the existing scheme, the rewards and punishments for fair testing need to achieve the quantification of test results through manual import or manual input, thus it is easy to fail to implement the rewards and punishments for fair testing.

[0006] To achieve the above object, according to one aspect of the present application, a fairness testing method is provided, which includes: receiving and responding to a current input operation to obtain current test information, where the current test information includes a current test unique identifier and a current test input; generating a current test result based on the current test unique identifier and the current test input, and using a smart contract to determine in a mapping manner whether the current test result and the current test input meet the specifications, to obtain a judgment result; adjusting the score value of the target tester according to the judgment result, where the score value represents the trustworthiness of the target tester.

[0007] Optionally, generating a current test result based on the current test unique identifier and the current test input includes: locating a target test program from a program library based on the current test unique identifier; calling the target test program from the program library; using the current test input as the input of the target test program to run the target test program, to obtain the current test result.

[0008] Optionally, before receiving and responding to a current input operation to obtain current test information, the method further includes: constructing an expected test mapping relationship, where the expected test mapping relationship is a mapping relationship among a test unique identifier, an expected test input, and an expected test result; storing the expected test mapping relationship in a database.

[0009] Optionally, using a smart contract to determine in a mapping manner whether the current test result and the current test input meet the specifications, to obtain a judgment result, includes: determining a target test result and a target test input according to the current test unique identifier and the expected test mapping relationship; in the case where the current test result is the same as the target test result, and the current test input is the same as the target test input, determining that the judgment result is that the score value of the target tester needs to be increased; in the case where the current test result is different from the target test result, and / or the current test input is different from the target test input, determining that the judgment result is that the score value of the target tester needs to be decreased.

[0010] Optionally, after obtaining the current test information, the method further includes: determining a target honor correction value in a mapped manner according to the test importance level corresponding to the unique identifier of the current test, where the target honor correction value is proportional to the test importance level; after determining that the judgment result is that the score value of the target tester needs to be increased, the method further includes: updating the score value of the target tester to the sum of the original score value and the target honor correction value; after determining that the judgment result is that the score value of the target tester needs to be decreased, the method further includes: updating the score value of the target tester to the difference between the original score value and the target honor correction value.

[0011] Optionally, after adjusting the score value of the target tester according to the judgment result, the method further includes:

[0012] When Honval ∈ (G t , G t+1 ,

[0013] determine the gradient reward value according to ;

[0014] generate at least a corresponding reward strategy according to the gradient reward value;

[0015] where ExtRew is the gradient reward value, Honval is the current score value, G t , G t+1 are the boundary values of the t-th honor gradient interval and the boundary value of the (t + 1)-th honor gradient interval respectively, and p t+1 , p i , p i+1 are the coefficients of the (t + 1)-th honor gradient interval, the i-th honor gradient interval, and the (i + 1)-th honor gradient interval respectively.

[0016] Optionally, generating at least a corresponding reward strategy according to the gradient reward value includes: generating the corresponding reward strategy according to the test importance level corresponding to the unique identifier of the current test and the magnitude of the gradient reward value, or generating the corresponding reward strategy according to the gradient reward value.

[0017] Optionally, the method further includes:

[0018] When , generate an error message for prompting that the test program needs to be corrected;

[0019] where Honval is the current score value, G t , G t+1 are the boundary values of the t-th honor gradient interval and the boundary value of the (t + 1)-th honor gradient interval respectively.

[0020] According to another aspect of the present application, a fair testing device is provided, which includes: an acquisition unit for receiving and responding to a current input operation to acquire current test information, where the current test information includes a current test unique identifier and a current test input; a first processing unit for generating a current test result based on the current test unique identifier and the current test input, and using a smart contract to determine in a mapping manner whether the current test result and the current test input comply with the specifications to obtain a judgment result; a second processing unit for adjusting the score value of a target tester according to the judgment result, where the score value represents the trustworthiness of the target tester.

[0021] According to another aspect of the present application, a fair testing system is provided, including: one or more processors, a memory, and one or more programs, where the one or more programs are stored in the memory and are configured to be executed by the one or more processors, and the one or more programs include those for executing any one of the methods described above.

[0022] Applying the technical solution of the present application, a current test result is generated based on the current test unique identifier and the current test input, and a smart contract is used to determine in a mapping manner whether the current test result and the current test input comply with the specifications to obtain a judgment result, so as to accurately judge whether the performance of the tester meets the expectations. Finally, the score value of the target tester is adjusted according to the judgment result. Compared with the existing solutions, it can quantify the test results and achieve the purpose of rewarding and punishing fair testing, thus solving the problem that the existing solutions need to achieve the quantification of test results through manual import or manual input for rewarding and punishing fair testing, and thus it is easy to fail to achieve the rewarding and punishing of fair testing. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] The specification drawings forming a part of the present application are used to provide a further understanding of the present application. The schematic embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation to the present application. In the drawings:

[0024] Figure 1 Shows a schematic flowchart of a fair testing method provided according to an embodiment of the present application;

[0025] Figure 2 Shows a schematic flowchart of a test task publishing system provided according to an embodiment of the present application;

[0026] Figure 3 Shows a schematic flowchart of a tester submitting a test result system provided according to an embodiment of the present application;

[0027] Figure 4 The structural block diagram of a fairness testing device provided according to an embodiment of the present application is shown. Detailed implementation manners

[0028] It should be noted that, without conflict, the embodiments in the present application and the features in the embodiments may be combined with each other. The present application will be described in detail below with reference to the drawings and in conjunction with the embodiments.

[0029] In order to enable those skilled in the art to better understand the solution of the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present application.

[0030] It should be noted that the terms "first", "second", etc. in the specification and claims of the present application and the above drawings are used to distinguish similar objects, and do not necessarily need to be used to describe a specific order or sequence. It should be understood that such used data may be interchanged under appropriate circumstances so as to the embodiments of the present application described herein. In addition, the terms "include" and "have" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product or device including a series of steps or units does not necessarily need to be limited to those steps or units clearly listed, but may include other steps or units not clearly listed or inherent to these process, method, product or device.

[0031] As introduced in the background art, in the traditional testing scheme, it is necessary to achieve the quantification of test results through manual import or manual input. Among them, malicious participants can destroy the fairness of the system based on this feature. When the test task issuer accepts the test results and marks the correct test results as wrong results, it will cause the testers to be unable to obtain the corresponding rewards. Or when the test results of the testers are wrong but are manually modified to correct results, it will cause the test task issuer to obtain wrong results when giving rewards. The above two situations will both destroy the fairness of the system, and the interests of the participants cannot be guaranteed. To solve the problem that the quantification of test results for the rewards and punishments of fairness testing in the existing scheme needs to be achieved through manual import or manual input, and thus it is easy to fail to achieve the rewards and punishments of fairness testing, the embodiments of the present application provide a fairness testing method, device and system.

[0032] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention.

[0033] In this embodiment, a fairness testing method is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. And although the logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in a different order than here.

[0034] Figure 1 It is a schematic flowchart of a fairness testing method provided according to an embodiment of the present application. As Figure 1 shown, the method includes the following steps:

[0035] Step S101, receive and respond to the current input operation to obtain the current test information. The above current test information includes the current test unique identifier and the current test input;

[0036] Among them, before receiving and responding to the current input operation to obtain the current test information, the above method further includes: constructing an expected test mapping relationship, where the expected test mapping relationship is a mapping relationship among the test unique identifier, the expected test input, and the expected test result; storing the above expected test mapping relationship in a database.

[0037] Specifically, by constructing an expected test mapping relationship to bind the test unique identifier, the expected test input, and the expected test result, the standardization and consistency of test cases can be ensured, avoiding inaccurate or repeated tests caused by human errors or misunderstandings. Storing the expected test mapping relationship in a database enables quick retrieval and verification of test cases. When testers submit test results, the system can quickly compare the expected test input and the expected test result to judge the accuracy of the test result, thereby improving test efficiency. The mapping relationship stored in the database provides a complete record for the test, ensuring the traceability of the test process. Anyone can view the expected input and expected result of the test case, increasing the transparency of the test process and facilitating the establishment of trust. The storage of the expected test mapping relationship can promote automated processing. Smart contracts can pre-load or access the mapping relationship in the database to automatically execute the verification of test results without human intervention, which not only saves time but also reduces human errors. By storing the expected test mapping relationship in a database, especially when the database is a blockchain-based decentralized database, data can be prevented from being maliciously tampered with, ensuring the accuracy and reliability of the expected test input and the expected test result.

[0038] Step S102, generate a current test result based on the above current test unique identifier and the above current test input, and use a smart contract to determine whether the above current test result and the above current test input conform to the specification in a mapped manner to obtain a judgment result;

[0039] Among them, a smart contract is a technology that uses computer programs to automatically execute the terms of a contract. Different from traditional written or oral contracts, smart contracts can be automatically triggered and operate according to preset conditions, while recording the operation results in the blockchain. This not only ensures the publicity, transparency, and immutability of the contract, but also increases the degree of automation and reliability of contract execution. There are mainly two ways to implement smart contracts: one is based on specialized smart contract platforms such as Ethereum; the other is to implement through independently developed blockchain technology. The core of a smart contract is a piece of program code that can run automatically. When certain specific conditions are met, this code will change its state and permanently record this state change on the blockchain. Since the entire process requires no human intervention, it greatly reduces the problems caused by misunderstandings, disputes, or disagreements.

[0040] Among them, generating the current test result based on the above-mentioned current test unique identifier and the above-mentioned current test input includes:

[0041] Locate the target test program from the program library based on the above-mentioned current test unique identifier; call the above-mentioned target test program from the above-mentioned program library; use the above-mentioned current test input as the input of the above-mentioned target test program to run the above-mentioned target test program to obtain the above-mentioned current test result.

[0042] Specifically, using the test unique identifier can quickly and accurately locate a specific test program, avoiding the time waste of blindly searching among a large number of test programs. This precise call mechanism ensures the efficiency of the test process. This process can automate the test process, that is, by identifying the test unique identifier to automatically call the corresponding test program and input test data, reducing the manual operation steps and improving the accuracy and speed of the test. Automatically calling the target test program can reduce errors caused by human factors, such as incorrectly selecting the test program or incorrectly inputting data, thus ensuring the reliability of the test result. Calling the test program based on the test unique identifier ensures the repeatability and consistency of the test. Each test based on the same identifier will call the same program, use the same input, and the results obtained will be comparable and consistent.

[0043] When the current test result generated based on the above current test unique identifier and the above current test input is applied to a specific scenario, for example, when developing a quality assurance system for an online education platform based on blockchain, which involves testing functions such as user interaction, payment processing, course content access, and grade recording of the platform. To ensure the fairness and automation of the test, we use smart contracts to implement test result verification and standardization checks of test inputs. First, a series of test cases are defined, each with a unique test identifier (for example, the test identifier for the user login function is "T12345"), as well as the expected test input and the expected test result. For example, the expected test input associated with "T12345" may include the correct username and password, and the expected test result is that the user successfully logs in and enters the personal homepage. These expected test mapping relationships are stored in a blockchain-based database to ensure its immutability and transparency to all test participants. When testers conduct the user login function test, they first submit the current test unique identifier "T12345" and the current test input (for example, a set of username and password) to the system. The system automatically calls the test program for the user login function from the program library based on the identifier "T12345". The input submitted by the tester is passed as a parameter to the called test program, and the current test result is obtained after running, for example, whether the user successfully logs in. The smart contract reads the expected test input and the expected test result related to the identifier "T12345" from the blockchain database. The smart contract conducts a standardization check on the current test input to ensure it is consistent with the expected input. Then, the smart contract compares the current test result with the expected test result to determine whether the test is successful. If the test input is consistent with the expected input and the test result matches the expected result, the smart contract will automatically confirm the test is successful and update the score value and reward value of the tester. Otherwise, the smart contract will mark the test as failed and adjust the score value of the tester according to the specific failure reason. The score value of the tester is automatically updated according to the compliance of their test behavior and the accuracy of the test result. For example, successfully completing multiple "T12345" test cases can increase the score value.

[0044] The beneficial effects of this specific scenario are as follows: The smart contract automatically executes test verification without manual participation, greatly improving the efficiency of the test process. In multiple test cases, automated processing can significantly reduce waiting and processing times, enabling testers to receive feedback more quickly and increasing the overall test speed. Since the execution of the smart contract is based on predefined rules and the results are recorded on the blockchain, all test participants (including testers, system administrators, and platform users) can view the test results and updated score values, increasing the transparency of the test process and ensuring the fairness of the test reward mechanism. The automatic execution function of the smart contract can reduce human errors, such as testers submitting incorrect test inputs or test results, because the smart contract automatically checks and judges based on the specification mapping relationship, and only inputs and results that meet the specifications will be recognized, ensuring the accuracy of the test data.

[0045] In one embodiment of the present application, a smart contract is used to determine whether the above-mentioned current test result and the above-mentioned current test input meet the specifications in a mapped manner, and a judgment result is obtained, including: determining a target test result and a target test input according to the above-mentioned current test unique identifier and the expected test mapping relationship; when the above-mentioned current test result is the same as the above-mentioned target test result, and the above-mentioned current test input is the same as the above-mentioned target test input, determining that the judgment result is that the score value of the target tester needs to be increased; when the above-mentioned current test result is different from the above-mentioned target test result, and / or, the above-mentioned current test input is different from the above-mentioned target test input, determining that the judgment result is that the score value of the above-mentioned target tester needs to be decreased.

[0046] Specifically, by strictly comparing the current test result with the target test result, and the current test input with the target test input, the smart contract can accurately judge whether the performance of the tester meets the expectations. If there is a complete match, the score value is increased to commend their accurate and professional work; otherwise, the score value is decreased as a penalty for their non-standard test behavior or inaccurate results, ensuring the fairness and accuracy of the scoring mechanism. This process is fully automated and executed in real time by the smart contract without manual intervention. Testers can immediately know whether their test results are recognized by the smart contract and the adjustment of the score value, providing instant feedback, which helps testers adjust their behavior in a timely manner and improve work efficiency and quality. Since the score adjustment is based on objective test results and input data, and these data are publicly transparent, it is difficult for disputes to occur. Both testers and task publishers can view how the smart contract makes score adjustments, enhancing the trust and credibility of the system.

[0047] Step S103, adjust the score value of the target tester according to the above-mentioned judgment result, and the score value represents the trustworthiness of the target tester.

[0048] In the above steps, a current test result is generated based on the above current test unique identifier and the above current test input, and a smart contract is used to determine whether the above current test result and the above current test input meet the specifications in a mapped manner, obtaining a judgment result, so as to accurately judge whether the performance of the tester meets the expectations. Finally, the score value of the target tester is adjusted according to the above judgment result. Compared with the existing solutions, it can quantify the test results and achieve the purpose of rewarding and punishing fair tests, thus solving the problem that the existing solutions need to achieve the quantification of test results through manual import or manual input for rewarding and punishing fair tests, and thus it is easy to fail to achieve the rewarding and punishing of fair tests.

[0049] This application introduces a scoring mechanism method aimed at rewarding testers with continuous excellent performance. Under this method, positive behaviors will be rewarded, such as higher task priorities or more generous financial rewards, while negative behaviors will be punished, which may lead to a reduction in scores or even restrictions on task participation qualifications. Utilizing the normativity and immutability of smart contracts ensures that score increases are based only on objective criteria and the results of automated verification, guaranteeing the fairness and reliability of the system. In addition, due to the transparency of the blockchain, all participants can view the honor records of testers, increasing the credibility of the system. Such a long-term incentive mechanism not only improves the enthusiasm of testers but also helps to maintain a healthy and professional testing environment, jointly promoting the improvement of software quality. Further, the method of redeeming additional rewards based on the honor of smart contracts further improves the enthusiasm and work efficiency of testers by introducing gradient rewards. At the same time, the smart contract ensures the fairness of testers, ensuring that the entire process of redeeming additional rewards with points is fair, automatically executed, and trustworthy, and ensuring that the interests of testers are not damaged.

[0050] Among them, after obtaining the current test information, the above method further includes: determining a target honor correction value in a mapped manner according to the test importance corresponding to the above current test unique identifier, and the above target honor correction value is proportional to the above test importance;

[0051] After determining that the judgment result is that the score value of the target tester needs to be increased, the above method further includes: updating the above score value of the target tester to the sum value of the original score value and the above target honor correction value;

[0052] After determining that the judgment result is that the score value of the above target tester needs to be decreased, the above method further includes: updating the above score value of the target tester to the difference value between the above original score value and the above target honor correction value.

[0053] Specifically, by associating the test importance level with the honor correction value, the system can identify and give more attention and rewards to important test cases, encourage testers to prioritize critical tests, thereby optimizing the allocation of test resources and ensuring the coverage and quality of critical functions. The target honor correction value is directly proportional to the test importance level, making the motivation for testers more refined and reasonable. The successful completion of important tests can bring a more significant increase in the scoring value, motivating testers to work harder and improve the test quality. For the failure of important tests, the system punishes the testers by reducing the honor correction value. This punishment mechanism linked to the test importance level is more accurate and reasonable, helping to correct the behavioral deviations of testers and reduce the error rate of important tests. By dynamically adjusting the scoring value according to the judgment result, testers can clearly see the direct impact of their behavior on the score. This not only increases the fairness and transparency of the scoring system but also provides immediate feedback to testers, helping them adjust their strategies in a timely manner and improve the test efficiency and accuracy.

[0054] In an embodiment of the present application, after adjusting the scoring value of the target tester according to the above judgment result, the above method further includes:

[0055] The calculation formula of the score value is:

[0056] When Honval ∈ (G t , G t+1 ,

[0057] Determine the gradient reward value according to the gradient reward formula ;

[0058] Generate at least a corresponding reward strategy according to the above gradient reward value;

[0059] Generate the corresponding above reward strategy according to the test importance level corresponding to the above current test unique identifier and the magnitude of the above gradient reward value, or generate the corresponding above reward strategy according to the above gradient reward value. Both methods can be implemented by means of mapping.

[0060] Among them, rew i is the honor reward value for each time, pun i is the honor punishment value for each time, n is the total number of times for calculating the honor reward value, s is the total number of times for calculating the honor punishment value, ExtRew is the above gradient reward value, Honval is the current scoring value, G t , G t+1 are respectively the boundary values of the t-th honor gradient interval and the boundary value of the (t + 1)-th honor gradient interval, p t+1 , p i , p i+1They are the (t + 1)-th honor gradient interval coefficient, the i-th honor gradient interval coefficient, and the (i + 1)-th honor gradient interval coefficient respectively.

[0061] Specifically, the gradient reward mechanism provides different levels of rewards based on the tester's score or scores, which can significantly enhance the incentive effect. When testers see that their efforts can be translated into higher-level rewards, they are motivated to improve their scores, thus participating in the testing more actively and improving the testing quality and efficiency. The gradient reward strategy based on scores ensures a more equitable distribution of rewards because the reward level directly reflects the contributions and professional performance of testers. This mechanism has a high level of transparency, and all participants can clearly see the relationship between scores and rewards, thereby enhancing the credibility of the system. The gradient reward strategy can promote the optimal allocation of resources (such as time and test cases). Testers will give priority to executing those test tasks that can significantly improve their scores, and these tasks often have the greatest impact on software quality. This method ensures that critical tests are given priority, improving the resource utilization efficiency. The gradient reward mechanism encourages testers to maintain good testing behaviors in the long term because they know that over time, their scores will accumulate, enabling them to obtain higher-level rewards. This long-term incentive helps to build a stable testing team and promotes the continuous development of the project. By setting gradient rewards directly associated with scores, the system can reduce negative behaviors during the testing process. In order to obtain higher rewards, testers will avoid submitting incorrect test results or cheating behaviors, thus improving the standardization and accuracy of testing. The gradient reward strategy encourages testers to explore and test all corners of the software, especially those complex areas that may hide potential defects, because testing these areas often brings a greater increase in scores, thereby indirectly improving the comprehensiveness and depth of software testing. The gradient reward mechanism can be flexibly adjusted according to the project requirements and testing complexity, allowing platform administrators to set different reward gradients according to the actual situation, making the reward strategy more adaptable to the testing needs at different stages and maintaining the vitality and effectiveness of the incentive mechanism. This automatic reward system based on scores simplifies the management of the testing platform. The smart contract automatically executes the gradient reward strategy without manual intervention, saving management costs and also avoiding unfairness and disputes that may be caused by human factors.

[0062] In an embodiment of the present application, the above method further includes: in case, generating an error message, where the error message is used to prompt that the test program needs to be corrected;

[0063] where Honval is the current score, and G t and G t+1 are the boundary values of the t-th honor gradient interval and the boundary value of the (t + 1)-th honor gradient interval respectively.

[0064] Specifically, the error message can directly point to the error or exception part in the test program, helping developers quickly locate the places that need to be corrected, reducing the time for troubleshooting problems, and improving the overall development efficiency.

[0065] As Figure 2 shown, the test task publishing system process includes: the test task publisher initializes the initial information for the tester, including the tester ID TID, the initial reward value RepVal, and the initial rating value HonVal, and forms a mapping of TID with RepVal and HonVal. The initial RepVal is 0. At this time, the tester has not completed any test tasks, and the initial reward value is 0; the initial rating value HonVal can be a fixed value negotiated by multiple parties, as long as the initial values of all people are the same;

[0066] The test task publisher sends the test case number Ref, the test case description, the expected result EepRes, the reward for this case Rewd, and the completion flag Flag (initialized to false) to the smart contract SC. SC forms a mapping relationship between Ref and the test case description, EepRes, and Rewd. The remaining test result verification, reward distribution, and changes in the tester's honor will be automatically executed by SC. During the subsequent execution process, the test task publisher cannot modify the results according to personal will, ensuring that the interests of the tester are not damaged.

[0067] As Figure 3 shown, the tester submission of test results system process includes:

[0068] Step 1: The tester submits the test input TInput and the test case number Ref. After being run and circulated by the system under test, the tester receives the test result TRes and the log binding ID. At the same time, the blockchain platform smart contract SC synchronously obtains the test input SCTInput, the test result SCTRes, the test log binding SCID, and the test case number SCRef, and automatically maps SCRef and SCID together to SCTRes and SCTInput.

[0069] Step 2: The tester submits the test results TInput, TRes, ID, and Ref. The smart contract obtains the completion flag Flag of the test case information through Ref and determines whether the test case is completed. If Flag is true, it means the test case is completed, and this test task is directly ended. If it is false, further judgment is continued. Adding this judgment can prevent the repeated consumption of test case rewards and damage the interests of the test task publisher, ensuring fairness for the test task publisher. Then the smart contract obtains the corresponding SCTInput and SCTRes through the ID and Ref input by the tester, that is, the map mapping obtains the corresponding values through key-value pairs. Then the SC automatically determines whether SCTInput and SCTRes are the same as TInput and TRes. If they are different, it jumps to Step 3. At this time, it is determined that the tester has not submitted the test results correctly and there is a deception behavior. If they are the same, it can be determined that the tester has no deception behavior, and then further judgment is continued. The smart contract obtains the corresponding expected test result EepRes through Ref and determines whether EepRes is equal to TRes. If they are the same, it jumps to Step 4. If they are different, this test session is directly ended, and the tester cannot obtain the corresponding reward, ensuring that the interests of the test case publisher will not be damaged. In the case of not receiving the correct result, the reward will definitely not be lost. At this time, the inequality of the two results may be due to errors in the program code or incorrect understanding by the tester resulting in incorrect test inputs, leading to inconsistency with the expected results. Since the tester's behavior is honest, neither reward nor punishment is given.

[0070] Step 3: Since the tester sent incorrect test results, resulting in inconsistency with the log results, it indicates that the tester may be deceptive. The SC will reduce the score value HonVal of the tester as a punishment, and the reduction amount can be determined by the administrator. It ensures that testers with dishonest behaviors will be punished, and the corresponding punishment pun is deducted from the score value. i , further standardizing the behavior of testers. HonVal = HonVal - pun i , and the smart contract ensures that the entire process is automatically executed. At the same time, based on the non-breachable and standardized characteristics, it ensures that the corresponding tester will definitely receive the corresponding punishment.

[0071] Step 4: At this time, TRes is the same as ERes, indicating that the test input is correct. The completion flag Flag of the test case will be set to true. At the same time, the tester will automatically receive the corresponding reward Rewd, and RepVal = RepVal + Rewd. This ensures that the interests of testers are not damaged when they give correct test inputs. Giving correct test inputs will definitely result in obtaining corresponding rewards, ensuring fairness for testers. At the same time, when Flag is set to true, subsequent testers cannot repeat submitting test inputs to repeatedly obtain test rewards, ensuring that the interests of test case publishers are not damaged and realizing fairness for test case publishers. The score value HonVal of the tester will increase, and corresponding honor rewards rew will be added, further motivating testers to conduct personal behaviors according to norms. Accumulating higher honor scores can enable testers to obtain more generous rewards, thereby inspiring them to maintain a positive work attitude. i , further motivating testers to conduct personal behaviors according to norms. Accumulating higher honor scores can enable testers to obtain more generous rewards, thereby inspiring them to maintain a positive work attitude.

[0072] Step 5: After testers complete the established test tasks, they will be given corresponding score values, which can be accumulated to form a "honor pool" savings. When the honor pool accumulates to a preset score, testers are eligible to use it to exchange for various additional rewards as a further reward for their continuous contributions. The calculation of additional rewards is achieved through a gradient reward formula. This formula ensures that higher rewards can be obtained by setting score value gradient intervals, ensuring that more score values can obtain higher rewards and that the rewards can improve the enthusiasm and efficiency of testers. Once testers decide to exchange their score values, the process will be automatically executed based on the technology of smart contracts without manual intervention. The automatic execution feature and normativity of smart contracts ensure the transparency and immutability of transactions, thereby ensuring that each tester can obtain the due additional rewards during the exchange process. This not only safeguards the legitimate interests of testers from infringement but also greatly enhances their enthusiasm by providing clear incentives. This positive feedback loop lays a solid foundation for improving the overall work efficiency and quality and also enhances the loyalty and satisfaction of testers towards the project.

[0073] It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. And although the logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in a different order than here.

[0074] The embodiments of the present application also provide a fairness testing device. It should be noted that the fairness testing device of the embodiments of the present application can be used to execute the fairness testing method provided by the embodiments of the present application. The device is used to implement the above embodiments and preferred implementation manners, and those that have been described will not be repeated. As used below, the term "module" can be a combination of software and / or hardware that can achieve a predetermined function. Although the devices described in the following embodiments are preferably implemented in software, implementation in hardware, or a combination of software and hardware is also possible and contemplated.

[0075] The fairness testing device provided by the embodiments of the present application will be introduced below.

[0076] Figure 4 It is a structural block diagram of a fairness testing device provided according to an embodiment of the present application. As Figure 4 shown, the device includes:

[0077] An acquisition unit 41, configured to receive and respond to a current input operation to obtain current test information, where the current test information includes a current test unique identifier and a current test input;

[0078] A first processing unit 42, configured to generate a current test result based on the current test unique identifier and the current test input, and use a smart contract to determine whether the current test result and the current test input meet the specifications in a mapping manner, so as to obtain a judgment result;

[0079] A second processing unit 43, configured to adjust the score value of a target tester according to the judgment result, where the score value represents the trustworthiness of the target tester.

[0080] In the above device, a current test result is generated based on the current test unique identifier and the current test input, and a smart contract is used to determine whether the current test result and the current test input meet the specifications in a mapping manner, so as to obtain a judgment result, so that it can accurately judge whether the performance of the tester meets the expectations. Finally, the score value of the target tester is adjusted according to the judgment result. Compared with the existing solutions, it can quantify the test results and achieve the purpose of rewarding and punishing fair testing, thus solving the problem that the existing solutions need to quantify the test results by manual import or manual input for rewarding and punishing fair testing, so it is easy to fail to achieve the rewarding and punishing of fair testing.

[0081] In an embodiment of the present application, the first processing unit includes a first processing module, a second processing module, and a third processing module. The first processing module is configured to locate a target test program from a program library based on the current test unique identifier; the second processing module is configured to call the target test program from the program library; the third processing module is configured to use the current test input as the input of the target test program to run the target test program to obtain the current test result.

[0082] In an embodiment of the present application, the device further includes a construction unit and a storage unit. The construction unit is configured to construct an expected test mapping relationship before receiving and responding to a current input operation to obtain current test information. The expected test mapping relationship is a mapping relationship among a test unique identifier, an expected test input, and an expected test result; the storage unit is configured to store the expected test mapping relationship in a database.

[0083] In an embodiment of the present application, the first processing unit includes a fourth processing module, a fifth processing module, and a sixth processing module. The fourth processing module is configured to determine a target test result and a target test input according to the current test unique identifier and the expected test mapping relationship; the fifth processing module is configured to determine that the judgment result is that the score value of the target test personnel needs to be increased when the current test result is the same as the target test result and the current test input is the same as the target test input; the sixth processing module is configured to determine that the judgment result is that the score value of the target test personnel needs to be decreased when the current test result is different from the target test result and / or the current test input is different from the target test input.

[0084] In an embodiment of the present application, the device further includes a determination unit, configured to determine a target honor correction value in a mapped manner according to the test importance degree corresponding to the current test unique identifier after obtaining the current test information. The target honor correction value is proportional to the test importance degree;

[0085] The first processing unit includes a seventh processing module and an eighth processing module. The seventh processing module is configured to update the score value of the target test personnel to the sum of the original score value and the target honor correction value after determining that the judgment result is that the score value of the target test personnel needs to be increased; the eighth processing module is configured to update the score value of the target test personnel to the difference between the original score value and the target honor correction value after determining that the judgment result is that the score value of the target test personnel needs to be decreased.

[0086] In an embodiment of the present application, the device further includes a fourth processing unit and a fifth processing unit.

[0087] The fourth processing unit is used to adjust the score value of the target tester according to the above judgment result,

[0088] when Honval ∈ (G t , G t+1 ),

[0089] determine the gradient reward value according to ;

[0090] The fifth processing unit is used to generate a corresponding reward strategy at least according to the above gradient reward value;

[0091] wherein, ExtRew is the above gradient reward value, Honval is the current score value, G t , G t+1 are the boundary values of the t-th honor gradient interval and the boundary value of the (t + 1)-th honor gradient interval respectively, and p t+1 , p i , p i+1 are the coefficients of the (t + 1)-th honor gradient interval, the i-th honor gradient interval, and the (i + 1)-th honor gradient interval respectively.

[0092] In an embodiment of the present application, the fifth processing unit includes a ninth processing module, and the ninth processing module is used to generate the corresponding above reward strategy according to the importance of the test corresponding to the above current test unique identifier and the magnitude of the above gradient reward value, or generate the corresponding above reward strategy according to the above gradient reward value.

[0093] In an embodiment of the present application, the above device further includes a generating unit;

[0094] The generating unit is used to generate an error message, and the above error message is used to prompt that the test program needs to be corrected;

[0095] wherein, Honval is the current score value, G t , G t+1 are the boundary values of the t-th honor gradient interval and the boundary value of the (t + 1)-th honor gradient interval respectively.

[0096] The above fair test device includes a processor and a memory, and the above obtaining unit, the first processing unit, the second processing unit, etc. are all stored in the memory as program units, and the corresponding functions are implemented by the processor executing the above program units stored in the memory. The above modules are all located in the same processor; or, the above each module is located in different processors in any combination form.

[0097] The processor contains a kernel, which retrieves the corresponding program unit from the memory. One or more kernels can be set. By adjusting the kernel parameters, the problem that the rewards and punishments for fair testing in the existing solutions need to be realized by manual import or manual input to quantify the test results, and thus it is easy to fail to implement the rewards and punishments for fair testing can be solved.

[0098] The memory may include non-permanent memory in a computer-readable medium, forms such as random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash memory (flash RAM), and the memory includes at least one memory chip.

[0099] An embodiment of the present invention provides a computer-readable storage medium. The above computer-readable storage medium includes a stored program. When the above program runs, it controls the device where the above computer-readable storage medium is located to execute the above fair testing method.

[0100] An embodiment of the present invention provides a processor. The above processor is used to run a program. When the above program runs, it executes the above fair testing method.

[0101] An embodiment of the present invention provides a device. The device includes a processor, a memory, and a program stored on the memory and executable on the processor. When the processor executes the program, it realizes at least the following steps: receiving and responding to the current input operation to obtain the current test information, where the above current test information includes the current test unique identifier and the current test input; generating a current test result based on the above current test unique identifier and the above current test input, and using a smart contract to determine whether the above current test result and the above current test input meet the specifications in a mapped manner to obtain a judgment result; adjusting the score value of the target tester according to the above judgment result, where the above score value represents the trustworthiness of the above target tester. The device in this article can be a server, a PC, a PAD, a mobile phone, etc.

[0102] The present application also provides a computer program product. When executed on a data processing device, it is suitable for executing a program initialized with at least the following method steps: receiving and responding to the current input operation to obtain the current test information, where the above current test information includes the current test unique identifier and the current test input; generating a current test result based on the above current test unique identifier and the above current test input, and using a smart contract to determine whether the above current test result and the above current test input meet the specifications in a mapped manner to obtain a judgment result; adjusting the score value of the target tester according to the above judgment result, where the above score value represents the trustworthiness of the above target tester.

[0103] The present application also provides a fairness testing system, including: one or more processors, a memory, and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors. The one or more programs include those for executing any of the above methods. Based on the current test unique identifier and the current test input, a current test result is generated, and a smart contract is used to determine in a mapped manner whether the current test result and the current test input meet the specifications, obtaining a judgment result, so as to accurately determine whether the performance of the tester meets the expectations. Finally, the score value of the target tester is adjusted according to the judgment result. Compared with the existing solutions, it can quantify the test results and achieve the purpose of rewarding and punishing fairness testing, thus solving the problem that the existing solutions need to realize the quantification of test results by manual import or manual input for rewarding and punishing fairness testing, and thus it is easy to fail to achieve the rewarding and punishing of fairness testing.

[0104] Obviously, those skilled in the art should understand that the various modules or steps of the above-mentioned present invention can be implemented by a general-purpose computing device. They can be concentrated on a single computing device or distributed on a network composed of multiple computing devices. They can be implemented by program codes executable by the computing device. Thus, they can be stored in a storage device and executed by the computing device. And in some cases, the steps shown or described can be executed in a different order from here, or they can be separately made into individual integrated circuit modules, or multiple modules or steps among them can be made into a single integrated circuit module to implement. In this way, the present invention is not limited to any specific combination of hardware and software.

[0105] Those skilled in the art should understand that the embodiments of the present application can be provided as a method, a system, or a computer program product. Therefore, the present application can take the form of a complete hardware embodiment, a complete 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 memories, CD-ROMs, optical memories, etc.) containing computer-usable program codes.

[0106] This application is described with reference to the flowcharts and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the present application. It should be understood that each flow and / or block in the flowchart and / or block diagram can be implemented by computer program instructions, and the combination of the flows and / or blocks in the flowchart and / or block diagram can also be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to generate a machine, such that the instructions executed by the processor of the computer or other programmable data processing devices generate means for implementing the functions specified in one or more flows and / or blocks. Figure 1 one or more flows and / or blocks Figure 1 or means for implementing the functions specified in one or more blocks.

[0107] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, such that the instructions stored in the computer-readable memory generate a manufactured article including instruction means that implement the functions specified in one or more flows and / or blocks. Figure 1 one or more flows and / or blocks Figure 1 or means for implementing the functions specified in one or more blocks.

[0108] These computer program instructions can also be loaded onto a computer or other programmable data processing device, such that a series of operation steps are executed on the computer or other programmable device to generate a computer-implemented process, and thus the instructions executed on the computer or other programmable device provide steps for implementing the functions specified in one or more flows and / or blocks. Figure 1 one or more flows and / or blocks Figure 1 or means for implementing the functions specified in one or more blocks.

[0109] In a typical configuration, a computing device includes one or more processors (CPUs), an input / output interface, a network interface, and a memory.

[0110] The memory may include non-permanent memory in the form of computer-readable media, random access memory (RAM), and / or non-volatile memory such as read-only memory (ROM) or flash memory (flash RAM). The memory is an example of computer-readable media.

[0111] A computer-readable medium includes permanent and non-permanent, removable and non-removable media, and information storage can be implemented by any method or technology. The information can be computer-readable instructions, data structures, program modules, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, compact disc read-only memory (CD-ROM), digital versatile disc (DVD) or other optical storage, magnetic cassette tapes, disk storage or other magnetic storage devices, or any other non-transitory medium that can be used to store information accessible by a computing device. As defined herein, computer-readable media do not include transitory computer-readable media, such as modulated data signals and carrier waves.

[0112] It should also be noted that the term "comprising", "including" or any other variant thereof is intended to cover non-exclusive inclusion, such that a process, method, article or device comprising a series of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article or device. Without further limitation, an element defined by the statement "comprising an..." does not exclude the presence of additional identical elements in the process, method, article or device comprising the element.

[0113] From the above description, it can be seen that the above embodiments of the present application achieve the following technical effects:

[0114] 1), The fairness test method of the present application generates a current test result based on the above-mentioned current test unique identifier and the above-mentioned current test input, and uses a smart contract to determine whether the above-mentioned current test result and the above-mentioned current test input comply with the specification in a mapped manner, obtaining a judgment result, so as to accurately judge whether the performance of the tester meets the expectation. Finally, the score value of the target tester is adjusted according to the above judgment result. Compared with the existing solutions, it can quantify the test results and achieve the purpose of rewarding and punishing fair tests, thus solving the problem that the existing solutions need to achieve the quantification of test results through manual import or manual input for rewarding and punishing fair tests, and thus it is easy to fail to achieve the rewarding and punishing of fair tests.

[0115] 2) The fairness testing device of the present application generates a current test result based on the above-mentioned current test unique identifier and the above-mentioned current test input, and uses a smart contract to determine whether the above-mentioned current test result and the above-mentioned current test input comply with the specifications in a mapped manner, obtaining a judgment result, so as to accurately judge whether the performance of the tester meets the expectations. Finally, the score value of the target tester is adjusted according to the above-mentioned judgment result. Compared with the existing solutions, it can quantify the test results and achieve the purpose of rewarding and punishing fair testing, thus solving the problem that the existing solutions need to achieve the quantification of test results through manual import or manual input for rewarding and punishing fair testing, and thus it is easy to fail to achieve the rewarding and punishing of fair testing.

[0116] The foregoing are only the preferred embodiments of the present application and are not intended to limit the present application. For those skilled in the art, the present application may have various changes and modifications. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included within the protection scope of the present application.

Claims

1. A fair testing method, characterized in that: include: Receiving and responding to a current input operation to obtain current test information, wherein the current test information includes a current test unique identifier and a current test input; Generate a current test result based on the current test unique identifier and the current test input, and use a smart contract to determine whether the current test result and the current test input meet the specification in a mapping manner to obtain a judgment result; The score value of the target tester is adjusted according to the judgment result, and the score value represents the trustworthiness of the target tester.

2. The method according to claim 1, characterized in that Generating a current test result based on the current test unique identifier and the current test input includes: Locating a target test program from a program library based on the current test unique identifier; Calling the target test program from the program library; The current test input is used as the input of the target test program to run the target test program and obtain the current test result.

3. The method according to claim 1, characterized in that Before receiving and responding to the current input operation to obtain the current test information, the method further includes: Constructing an expected test mapping relationship, wherein the expected test mapping relationship is a mapping relationship between a test unique identifier, an expected test input, and an expected test result; The expected test mapping relationship is stored in a database.

4. The method according to claim 3, characterized in that: A smart contract is used to determine whether the current test result and the current test input meet the specification in a mapping manner, and a judgment result is obtained, including: Determine the target test result and the target test input according to the current test unique identifier and the expected test mapping relationship; When the current test result is the same as the target test result, and the current test input is the same as the target test input, determining that the score of the target tester needs to be improved; When the current test result is different from the target test result, and / or the current test input is different from the target test input, it is determined that the score of the target tester needs to be lowered.

5. The method according to claim 4, characterized in that After obtaining the current test information, the method further includes: determining a target honor correction value according to the test importance corresponding to the current test unique identifier in a mapping manner, wherein the target honor correction value is proportional to the test importance; After determining that the judgment result is that the score of the target tester needs to be increased, the method further includes: updating the score of the target tester to the sum of the original score and the target honor correction value; After determining that the judgment result is that the score of the target tester needs to be lowered, the method further includes: updating the score of the target tester to the difference between the original score and the target honor correction value.

6. The method according to claim 1, characterized in that After adjusting the score of the target tester according to the judgment result, the method further includes: In Honval∈(G t ,G t+1 ], according to Determine the gradient reward value; Generate a corresponding reward strategy at least according to the gradient reward value; Among them, ExtRew is the gradient reward value, Honval is the current score value, G t , G t+1 are the boundary values ​​of the tth honor gradient interval and the t+1th honor gradient interval, pt +1 、p i 、p i+1 They are the t+1th honor gradient interval coefficient, the i-th honor gradient interval coefficient, and the i+1th honor gradient interval coefficient respectively.

7. The method according to claim 6, characterized in that Generating a corresponding reward strategy at least according to the gradient reward value includes: The corresponding reward strategy is generated according to the test importance corresponding to the current test unique identifier and the size of the gradient reward value, or the corresponding reward strategy is generated according to the gradient reward value.

8. The method according to any one of claims 1 to 7, characterized in that The method further comprises: exist In the case of a test program being modified, an error message is generated, wherein the error message is used to prompt that the test program needs to be modified; Among them, Honval is the current score value, G t , G t+1 They are respectively the boundary value of the t-th honor gradient interval and the boundary value of the t+1-th honor gradient interval.

9. A fairness testing device, characterized in that: include: An acquisition unit, configured to receive and respond to a current input operation to acquire current test information, wherein the current test information includes a current test unique identifier and a current test input; A first processing unit, configured to generate a current test result based on the current test unique identifier and the current test input, and determine whether the current test result and the current test input meet the specification in a mapping manner using a smart contract to obtain a judgment result; The second processing unit is used to adjust the score value of the target tester according to the judgment result, and the score value represents the trustworthiness of the target tester.

10. A fair testing system, characterized in that: include: One or more processors, a memory, and one or more programs, wherein the one or more programs are stored in the memory and are configured to be executed by the one or more processors, and the one or more programs include methods for executing any one of claims 1 to 8.

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