Test team work evaluation alarm method and device for information technology R&D projects

Abstract

The present application provides a test team work evaluation alarm method and device for an information-based R&D project, which is applied to a server, including: extracting multiple current work information of a target distributed node of a blockchain through a subscription function; statistically processing multiple current work information through multiple target statistical strategies to obtain multiple current statistical information; inputting multiple current statistical information and historical statistical information into a prediction model to obtain multiple current improvement measures; enabling the blockchain to generate alarm information for the target work team based on each current statistical information and the corresponding current improvement measures; sending the alarm information to a project management platform so that the project management platform completes the alarm prompt for the target work team. The above scheme predicts the current improvement measures by using a prediction model to predict the current work information extracted in real time, thereby reducing the delay existing in the manual method and improving the efficiency of the alarm prompt.

Description

Technical Field

[0001] The present application relates to the field of data processing technology, and in particular to a method and device for evaluating and warning the work of a test team of an information technology research and development project. Background Art

[0002] In information technology R&D projects, the testing team is responsible for the testing of tasks. The testing team tests the products developed by the development team according to the preset testing direction to evaluate whether the products meet expectations.

[0003] In actual applications, problems may occur when the test team performs the test work, resulting in the test work not meeting expectations and affecting the overall progress of the information technology R&D project. In order to make the test work meet expectations, in related technologies, the test work is regularly evaluated manually and alarms are issued, so that the test team can improve and optimize the test work according to the alarms.

[0004] However, there are delays in regular warning prompts, and the test work cannot be optimized in time, and problems in the test work cannot be solved in time, which affects the efficiency of the test work. Summary of the invention

[0005] The present application provides a method and device for warning the work evaluation of a test team of an information technology research and development project, so as to improve the efficiency of warning prompts.

[0006] In a first aspect, the present application provides a test team work evaluation alarm method for an information-based R&D project, which is applied to a server, and includes: extracting multiple current work information of a target distributed node of a blockchain through a subscription function, wherein the distributed nodes of the blockchain correspond one-to-one to the work teams; determining multiple target statistical strategies, and performing statistical processing on the multiple current work information through the multiple target statistical strategies to obtain multiple current statistical information, wherein the current statistical information is used to indicate the degree of work completion; determining the historical statistical information of the target distributed node, and inputting the multiple current statistical information and the historical statistical information into a prediction model to obtain multiple current improvement measures, wherein the current improvement measures are used to improve the degree of work completion; uploading each current statistical information and the corresponding current improvement measure to the blockchain, so that the blockchain generates an alarm information for the target work team according to each current statistical information and the corresponding current improvement measure; sending the alarm information to a project management platform, so that the project management platform completes the alarm prompt for the target work team.

[0007] In one possible implementation, multiple current working information of target distributed nodes of the blockchain are extracted through a subscription function, including: determining multiple subscription distributed nodes; extracting multiple data records corresponding to the multiple subscription distributed nodes; and extracting multiple current working information of target distributed nodes of the blockchain based on the multiple data records.

[0008] In one possible implementation, the multiple data records include multiple work information; based on the multiple data records, multiple current work information of the target distributed node of the blockchain is extracted, including: determining multiple generation times corresponding to the multiple work information in the multiple data records; based on the multiple generation times, determining the multiple current work information from the multiple work information, and the intervals between the multiple generation times corresponding to the multiple current work information and the current time are all less than a preset duration.

[0009] In one possible implementation, the multiple current working information are determined from the multiple working information according to the multiple generation times, including: determining multiple encrypted information from the multiple working information according to the multiple generation times, the intervals between the multiple generation times corresponding to the multiple encrypted information and the current time are all less than the preset duration; determining the key corresponding to the target distributed node; and decrypting the multiple encrypted information according to the multiple keys to obtain the multiple current working information.

[0010] In a possible implementation, determining multiple target statistical strategies includes: determining multiple statistical types and multiple current benchmark values ​​corresponding to the multiple statistical types; and determining multiple target statistical strategies corresponding to the multiple statistical types based on the multiple current benchmark values.

[0011] In a possible implementation, the method further includes: determining a weight corresponding to each current statistical information; performing weighted sum processing on each current statistical information according to the weight corresponding to each current statistical information to obtain target statistical information of the target work team; uploading each current statistical information, the corresponding current improvement measures, and the target statistical information to the blockchain, so that the blockchain generates warning information for the target work team.

[0012] In a possible implementation, the method further includes: acquiring sample data, the sample data including multiple groups of statistical information, each group of statistical information including first statistical information, second statistical information, and sample improvement measures, the time of the first statistical information being later than the time of the second statistical information; using the first statistical information and the second statistical information as inputs and the sample improvement measures as labels for model training to obtain the prediction model, the prediction model being used to obtain improvement measures by comparing the first statistical information and the second statistical information.

[0013] In a second aspect, the present application provides a test team work evaluation alarm device for an information-based R&D project, which is applied to a server and includes: an extraction module, which is used to extract multiple current work information of a target distributed node of a blockchain through a subscription function, wherein the distributed nodes of the blockchain correspond one-to-one to the work team; a statistical module, which is used to determine multiple target statistical strategies, and statistically process the multiple current work information through the multiple target statistical strategies to obtain multiple current statistical information, wherein the current statistical information is used to indicate the degree of work completion; a prediction module, which is used to determine the historical statistical information of the target distributed node, and input the multiple current statistical information and the historical statistical information into a prediction model to obtain multiple current improvement measures, wherein the current improvement measures are used to improve the degree of work completion; a generation module, which is used to upload each current statistical information and the corresponding current improvement measure to the blockchain, so that the blockchain generates an alarm information for the target work team according to each current statistical information and the corresponding current improvement measure; a sending module, which is used to send the alarm information to a project management platform, so that the project management platform completes the alarm prompt for the target work team.

[0014] In one possible implementation, the extraction module is specifically used to determine a plurality of subscribing distributed nodes; the extraction module is specifically used to extract a plurality of data records corresponding to the plurality of subscribing distributed nodes; the extraction module is specifically used to extract a plurality of current working information of the target distributed nodes of the blockchain based on the plurality of data records.

[0015] In a possible implementation, the multiple data records include multiple work information; the extraction module is specifically used to determine multiple generation times corresponding to the multiple work information in the multiple data records; the extraction module is also specifically used to determine the multiple current work information from the multiple work information based on the multiple generation times, and the intervals between the multiple generation times corresponding to the multiple current work information and the current time are all less than a preset duration.

[0016] In a possible implementation, the extraction module is specifically used to determine multiple encrypted information from the multiple working information according to the multiple generation times, and the intervals between the multiple generation times corresponding to the multiple encrypted information and the current time are all less than the preset duration; the extraction module is also specifically used to determine the key corresponding to the target distributed node; the extraction module is also specifically used to decrypt the multiple encrypted information according to the multiple keys to obtain the multiple current working information.

[0017] In a possible implementation, the device further includes: a processing module for determining multiple statistical types and multiple current benchmark values ​​corresponding to the multiple statistical types; the processing module is also used to determine multiple target statistical strategies corresponding to the multiple statistical types based on the multiple current benchmark values.

[0018] In a possible implementation, the device also includes: an upload module, used to determine the weight corresponding to each current statistical information; the upload module is also used to perform weighted sum processing on each current statistical information according to the weight corresponding to each current statistical information to obtain the target statistical information of the target work team; the upload module is also used to upload each current statistical information, the corresponding current improvement measures, and the target statistical information to the blockchain, so that the blockchain generates an alarm information for the target work team.

[0019] In a possible implementation, the device also includes: a training module, used to obtain sample data, the sample data includes multiple groups of statistical information, each group of statistical information includes first statistical information, second statistical information, and sample improvement measures, the time of the first statistical information is later than the time of the second statistical information; the training module is also used to use the first statistical information and the second statistical information as input and the sample improvement measures as labels to perform model training to obtain the prediction model, and the prediction model is used to obtain improvement measures by comparing the first statistical information and the second statistical information.

[0020] In a third aspect, the present application provides an electronic device comprising: a processor, and a memory communicatively connected to the processor; the memory stores computer-executable instructions; the processor executes the computer-executable instructions stored in the memory to implement any method described in the first aspect.

[0021] In a fourth aspect, the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores computer-executable instructions, and the computer-executable instructions are executed by a processor as described in any one of the methods in the first aspect.

[0022] In a fifth aspect, the present application provides a computer program product, comprising a computer program, wherein the computer program is executed by a processor as in any one of the methods in the first aspect.

[0023] The test team work evaluation alarm method and device of the information technology research and development project provided by the present application are applied to the server, and the method includes: extracting multiple current work information of the target distributed node of the blockchain through the subscription function, wherein the distributed nodes of the blockchain correspond to the work team one by one; determining multiple target statistical strategies, and statistically processing the multiple current work information through the multiple target statistical strategies to obtain multiple current statistical information, wherein the current statistical information is used to indicate the degree of work completion; determining the historical statistical information of the target distributed node, and inputting the multiple current statistical information and the historical statistical information into the prediction model to obtain multiple current improvement measures, wherein the current improvement measures are used to improve the degree of work completion; uploading each current statistical information and the corresponding current improvement measures to the blockchain, so that the blockchain generates an alarm information for the target work team according to each current statistical information and the corresponding current improvement measures; sending the alarm information to the project management platform, so that the project management platform completes the alarm prompt for the target work team. The above scheme predicts the current improvement measures by predicting the current work information extracted in real time through the prediction model, reduces the delay existing in the manual method, and thus improves the efficiency of the alarm prompt. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0025] Figure 1 A schematic diagram of an application scenario of a test team work evaluation and alarm method for an information-based R&D project provided in an embodiment of the present application;

[0026] Figure 2 A flowchart of a test team work evaluation and alarm method for an information-based R&D project provided in an embodiment of the present application;

[0027] Figure 3 A flowchart of a test team work evaluation and alarm method for an information-based R&D project provided in an embodiment of the present application;

[0028] Figure 4 A schematic diagram of determining current information provided in an embodiment of the present application;

[0029] Figure 5 A schematic diagram of determining multiple current statistical information provided by an embodiment of the present application;

[0030] Figure 6 A schematic diagram of generating alarm information provided in an embodiment of the present application;

[0031] Figure 7 A schematic diagram of the structure of a test team work evaluation alarm device for an information-based R&D project provided in an embodiment of the present application;

[0032] Figure 8 A schematic diagram of the structure of a test team work evaluation alarm device for an information-based R&D project provided in an embodiment of the present application;

[0033] Fig. 9 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application.

[0034] The above drawings have shown clear embodiments of the present application, which will be described in more detail later. These drawings and text descriptions are not intended to limit the scope of the present application in any way, but to illustrate the concept of the present application to those skilled in the art by referring to specific embodiments. DETAILED DESCRIPTION

[0035] Exemplary embodiments will be described in detail herein, examples of which are shown in the accompanying drawings. When the following description refers to the drawings, the same numbers in different drawings represent the same or similar elements unless otherwise indicated. The implementations described in the following exemplary embodiments do not represent all implementations consistent with the present application. Instead, they are merely examples of devices and methods consistent with some aspects of the present application as detailed in the appended claims.

[0036] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use, processing, transmission, provision, disclosure and application of the relevant data comply with the relevant laws, regulations and standards of the relevant countries and regions, take necessary confidentiality measures, do not violate public order and good customs, and provide corresponding operation entrances for users to choose to authorize or refuse.

[0037] In addition, this application involves conducting big data analysis of user information (including but not limited to personal biometrics, identity data, consumption data, asset data, electronic terminal operation data, etc.), and using artificial intelligence technology to make automated decisions, and making technical solutions that have a significant impact on personal rights and interests based on the results of automated decisions. The application provides users with corresponding operation entrances for them to choose to agree or reject the results of automated decisions; if the user chooses to reject, the expert decision-making process will be entered.

[0038] It should be noted that the test team work evaluation and alarm method and device of the information technology research and development project of the present application can be used in the field of data processing technology, and can also be used in any field other than data processing. The application field of the test team work evaluation and alarm method and device of the information technology research and development project of the present application is not limited.

[0039] Figure 1 A schematic diagram of an application scenario of a test team work evaluation and alarm method for an information-based R&D project provided in an embodiment of the present application is given as an example in combination with the scenario shown in the diagram: in an information-based R&D project, the development team executes project requirements to obtain an initial product, the test team tests the initial product, and optimizes it according to the test results to obtain the final product.

[0040] In actual applications, problems may occur when the testing team performs testing work, which may cause errors in the testing work or reduce the overall efficiency of the information technology R&D project.

[0041] In related technologies, the work of the test team is evaluated manually and regularly, and the test team is warned based on the evaluation results. The test team determines corresponding improvement measures based on the warnings to optimize the test work, so that the information technology R&D project can be executed normally.

[0042] However, there are delays in regular manual evaluations. For example, if an evaluation is conducted once a quarter or once a year, problems in the test work cannot be discovered in time. The problems can only be discovered and alarms can be issued during the evaluation cycle, resulting in low efficiency of alarms.

[0043] The method for evaluating and warning the work of a test team of an information technology research and development project provided in this application is intended to solve the above technical problems of the prior art.

[0044] The technical solution of the present application and how the technical solution of the present application solves the above-mentioned technical problems are described in detail below with specific embodiments. The following specific embodiments can be combined with each other, and the same or similar concepts or processes may not be repeated in some embodiments. The embodiments of the present application will be described below in conjunction with the accompanying drawings.

[0045] Figure 2 A flowchart of a test team work evaluation and alarm method for an information-based R&D project provided in an embodiment of the present application, the method comprising the following steps:

[0046] S201. Extract multiple current working information of the target distributed nodes of the blockchain through the subscription function.

[0047] Among them, the distributed nodes of the blockchain correspond one to one with the work teams.

[0048] Exemplarily, the evaluation alert is automatically performed by a server.

[0049] Among them, recording and managing work information through blockchain technology can improve the transparency and integrity of management.

[0050] The target distributed node is a distributed node for real-time evaluation.

[0051] Combined with the scenario example, in the information technology R&D project, the testing team is responsible for testing the developed products to determine whether the products meet the expected standards. In order to improve the transparency, reliability and traceability of the project, blockchain technology can be used to record and manage the work information of the work team. Specifically, a blockchain-based system can be designed in which multiple distributed nodes correspond to multiple work teams one by one.

[0052] Exemplarily, the work information of each work team is uploaded to the blockchain through the corresponding distributed nodes, and each node can access the work information of other nodes.

[0053] Optionally, an alarm node is designed, and the alarm node is used to obtain working information of multiple distributed nodes and issue alarm prompts.

[0054] S202: Determine a plurality of target statistical strategies, and perform statistical processing on a plurality of current working information using the plurality of target statistical strategies to obtain a plurality of current statistical information.

[0055] Among them, current statistics are used to indicate the degree of work completion.

[0056] Among them, the current work information is obtained based on the work records of the work team, and the current work information records do not directly reflect the problems in the work.

[0057] In the related art, existing problems are determined from target work information manually, which has the problem of low efficiency.

[0058] Exemplarily, the present application automatically performs statistical processing on target work information in a statistical manner to obtain a plurality of current statistical information, and reflects problems in the work through the plurality of current statistical information.

[0059] Exemplarily, a target statistical strategy is used to perform statistical processing on multiple pieces of current work information of the work team corresponding to the target distributed node.

[0060] Combined with the scenario example, multiple current work information corresponds to multiple indicator dimensions. Through the target statistical strategy, each indicator dimension is statistically processed to obtain the corresponding current statistical information. It can be understood that by statistically processing multiple indicator dimensions separately, interference between different indicator dimensions can be avoided, thereby improving the accuracy of statistical processing.

[0061] Exemplarily, the indicator dimensions include but are not limited to at least one of the following: weighted density of test defects, weighted density of test omission defects, on-time version release rate, team defect regression time, test case coverage, average test case design volume per person, average test case execution volume per person, or average workload per person, etc.

[0062] Combined with the scenario example, if the weighted density of test defects is low, it means that the work quality of the test team is low. The possible reasons are that the test does not cover enough test scenarios, the testing capabilities are low, or the testing tools are not advanced enough. The corresponding improvement measures are aimed at improving work quality.

[0063] If the weighted density of missed defects in the test is high and the remaining defects will affect the use of the product, the corresponding improvement measures are aimed at improving the accuracy of the test.

[0064] If the on-time release rate of versions is low, it will affect the progress of the R&D project. The corresponding improvement measures are aimed at improving the work efficiency of the testing team.

[0065] If the team's defect regression time is long, it will delay the product launch, and the corresponding improvement measures are aimed at improving the work efficiency of the testing team.

[0066] If the test case coverage is small, it means that the test is insufficient and the requirements have not been fully tested. The corresponding improvement measure is to improve the test plan.

[0067] If the number of test case designs per capita is small, it means that the design task allocation is unreasonable. The corresponding target improvement measure is to improve the rationality of the allocated work.

[0068] If the number of test cases executed per capita is small, it means that the execution task allocation is unreasonable. The corresponding target improvement measure is to improve the rationality of the allocated work.

[0069] If the average workload per person is high, it means that the work distribution is unreasonable. The corresponding target improvement measure is to improve the rationality of the work distribution.

[0070] S203: Determine historical statistical information of the target distributed node, and input multiple current statistical information and historical statistical information into a prediction model to obtain multiple current improvement measures.

[0071] Among them, current improvement measures are used to improve the degree of work completion.

[0072] Among them, the current statistical information and the historical statistical information are both statistical information of the work team corresponding to the target distributed node.

[0073] Exemplarily, the time corresponding to the historical statistical information is earlier than the current statistical information. The historical statistical information is used as a reference standard. The prediction model evaluates the current statistical information according to the reference standard to automatically obtain an evaluation result, and automatically determines the current improvement measures corresponding to the evaluation result.

[0074] S204. Upload each current statistical information and the corresponding current improvement measure to the blockchain, so that the blockchain generates warning information to the target work team according to each current statistical information and the corresponding current improvement measure.

[0075] Combined with the scenario example, by uploading current statistical information and current improvement measures to the blockchain, the integrity and immutability of the information can be ensured.

[0076] Optionally, the distributed nodes corresponding to the work team can subscribe to the alarm node, so as to obtain the information of the alarm node in a timely manner, thereby improving the efficiency of work optimization.

[0077] S205: Send the warning information to the project management platform so that the project management platform can complete the warning prompt to the target work team.

[0078] Exemplarily, the project management platform establishes a communication connection with each work team and issues an alarm prompt based on the communication connection.

[0079] Optionally, the project management platform establishes a correspondence between each work team and the communication connection, and issues an alarm prompt based on the correspondence.

[0080] Combined with the scenario example, when the project management platform receives alarm information, it immediately and automatically determines the corresponding communication connection according to the work team corresponding to the alarm information, and sends the alarm information to the corresponding work team through the communication connection, so that the work team can optimize the work in time according to the alarm information and improve the efficiency of the alarm prompt.

[0081] The test team work evaluation alarm method of the information research and development project provided by the embodiment of the present application is applied to the server, and the method includes: extracting multiple current work information of the target distributed node of the blockchain through the subscription function, wherein the distributed nodes of the blockchain correspond to the work team one by one; determining multiple target statistical strategies, and statistically processing multiple current work information through multiple target statistical strategies to obtain multiple current statistical information, wherein the current statistical information is used to indicate the degree of work completion; determining the historical statistical information of the target distributed node, and inputting multiple current statistical information and historical statistical information into the prediction model to obtain multiple current improvement measures, wherein the current improvement measures are used to improve the degree of work completion; uploading each current statistical information and the corresponding current improvement measures to the blockchain, so that the blockchain generates an alarm information for the target work team according to each current statistical information and the corresponding current improvement measures; sending the alarm information to the project management platform, so that the project management platform completes the alarm prompt for the target work team. The above scheme predicts the current improvement measures by predicting the current work information extracted in real time through the prediction model, reduces the delay existing in the manual method, and thus improves the efficiency of the alarm prompt.

[0082] Based on any of the above embodiments, Figure 3 , explains the detailed process of work evaluation and alarm of the test team of information technology R&D projects.

[0083] Figure 3 A flowchart of a test team work evaluation and alarm method for an information-based R&D project provided in an embodiment of the present application. Figure 3 As shown, the method includes:

[0084] S301. Determine multiple subscription distributed nodes.

[0085] The subscribed distributed node is a distributed node subscribed by the alarm node.

[0086] Exemplarily, through the subscription function, the alarm node can promptly respond to the work information of the subscribed distributed nodes and process the work information.

[0087] S302: Extract multiple data records corresponding to multiple subscription distributed nodes.

[0088] Exemplarily, the data record includes work information of subscribing to distributed nodes.

[0089] Combined with the scenario example, for example, when a distributed node has newly uploaded work information by a work team, the change will be displayed in the data record. Therefore, the real-time work information of multiple work teams can be obtained at the same time through multiple data records.

[0090] S303. Extract multiple current working information of the target distributed nodes of the blockchain based on multiple data records.

[0091] The current work information is work information generated in real time, and the target distributed node is a subscribed distributed node that currently generates work information in real time.

[0092] A feasible implementation method is that multiple data records include multiple work information; multiple current work information can be extracted by the following method: determine multiple generation times corresponding to multiple work information in multiple data records; determine multiple current work information from multiple work information based on the multiple generation times, and the intervals between the multiple generation times corresponding to the multiple current work information and the current time are all less than a preset duration.

[0093] Exemplarily, when each piece of work information is uploaded to a distributed node, the generation time corresponding to the work information is also uploaded.

[0094] Combined with the scenario example description, whether each piece of work information is the current work information can be judged by the generation time, thereby accurately determining multiple pieces of current work information.

[0095] Exemplarily, the preset duration is used as a criterion for judging the current work information.

[0096] In combination with the scenario example, if the preset duration is 1 hour, all work information within 8 hours before the current moment will be determined as the current work information.

[0097] Optionally, the current work information is verified through a duplicate checking mechanism. If the current work information has not been processed, the verification passes, thus avoiding duplicate processing of information.

[0098] In this feasible implementation, through multiple generation moments, it is possible to accurately determine from multiple work information which work information is generated in real time and which work information is generated historically, so as to timely process the current work information generated in real time.

[0099] A feasible implementation method can determine multiple current working information by the following method: determine multiple encrypted information from multiple working information according to multiple generation times, and the intervals between the multiple generation times corresponding to the multiple encrypted information and the current time are all less than a preset duration; determine the key corresponding to the target distributed node; decrypt the multiple encrypted information according to the multiple keys to obtain multiple current working information.

[0100] Exemplarily, the multiple pieces of work information are all encrypted information.

[0101] Next, combine Figure 4 Describes determining current information.

[0102] Figure 4 A schematic diagram of determining current information provided in an embodiment of the present application. Figure 4 As shown, multiple corresponding generation moments are determined according to multiple work information, and multiple encrypted information is determined from the multiple work information according to the multiple generation moments, the current moment, and the preset duration, and the encrypted information cannot directly read the information content. The multiple encrypted information is decrypted by the key to obtain multiple current work information, and the multiple current work information can be read.

[0103] Optionally, there is a one-to-one correspondence between distributed nodes and keys, and each key can only be used for decryption processing of a corresponding subscribed distributed node.

[0104] In this feasible implementation, encrypted storage can improve the integrity and tamper-proofness of work information, thereby improving the accuracy of alarm prompts.

[0105] S304: Determine multiple statistical types and multiple current reference values ​​corresponding to the multiple statistical types.

[0106] Among them, the benchmark value serves as a reference standard for performing statistical calculations.

[0107] Optionally, multiple statistical information of multiple work teams corresponding to any indicator dimension is determined, and the benchmark value may be a maximum value or an average value among the multiple statistical information.

[0108] Optionally, the benchmark value is a dynamically changing value, and the benchmark value is determined by integrating statistical information of multiple work teams.

[0109] S305: Determine multiple target statistical strategies corresponding to multiple statistical types according to multiple current benchmark values.

[0110] The target statistical strategy is used to determine the current statistical information of the target work team based on the statistical values ​​and benchmark values ​​of the target work team.

[0111] Combined with the scenario example, the statistical values ​​of different indicator dimensions correspond to different statistical calculation methods. For example, the calculation method corresponding to the test defect weighted density indicator dimension can be the ratio of the number of defects found to the number of released third-level requirements.

[0112] The calculation method corresponding to the weighted density index of test missed defects can be the ratio of the number of defects left over from the test to the number of released third-level requirements. The number of defects left over can be obtained by weighted summing according to the severity of each defect.

[0113] The calculation method corresponding to the dimension of the indicator dimension of on-time version release rate can be the ratio of the number of versions released on plan to the number of confirmed version release plans.

[0114] The calculation method corresponding to the team defect regression time indicator dimension can be the ratio of the time between the defect closure time and the defect resolution time to the total number of internal testing defects.

[0115] The calculation method corresponding to the test case coverage indicator dimension can be: the ratio of the total number of test cases (number of passed test cases) under the integrated test suite corresponding to the iteration (development version number) of the released third-level requirements to the total number of released third-level requirements.

[0116] The calculation method corresponding to the indicator dimension of per capita test case design quantity can be the ratio of the total number of test cases designed (which can be newly created and / or modified) by the test team to the number of people in the test team.

[0117] The calculation method corresponding to the indicator dimension of per capita test case execution volume can be the ratio of the total number of executed test cases to the number of people in the test team.

[0118] The calculation method corresponding to the average workload indicator dimension may be the ratio of the total working hours of each staff member in the test team to the standard workload.

[0119] Combined with the scenario example, taking the test defect weighted density indicator dimension as an example, the calculation formula for calculating the statistical information of the target work team can be:

[0120]

[0121] Among them, T represents statistical information, A represents the standard score, which corresponds to the indicator type, B represents the benchmark value, C represents the statistical value of the target work team, D represents the minimum value of the statistical values ​​of multiple work teams, γ1 is the first coefficient, γ2 is the second coefficient, the first coefficient and the second coefficient correspond to the indicator type respectively, and the sum of the first coefficient and the second coefficient is 1.

[0122] Taking the on-time release rate as an example, the calculation formula for the statistical information of the target work team can be:

[0123]

[0124] Among them, T represents statistical information, A represents the standard score, the standard score corresponds to the indicator type, γ3 is the third coefficient, if the statistical value, that is, the on-time release rate of the version = 100%, the third coefficient is set to 1, if the on-time test rate < 100%, the third coefficient is set according to the proportion interval, specifically, if 90% ≤ on-time test rate < 100%, the third coefficient is set to 0.9, if 80% ≤ on-time test rate < 90%, the third coefficient is set to 0.8, and so on until the third coefficient is set to 0.

[0125] Taking the average workload per person as an example, the calculation formula for calculating the statistical information of the target work team can be:

[0126]

[0127] Among them, T represents statistical information, A represents standard score, which corresponds to the indicator type, C represents the statistical value of the target work team, and E represents the maximum value of the statistical values ​​of multiple work teams. It should be noted that this application does not limit the specific calculation process of the statistical strategy.

[0128] S306. Perform statistical processing on multiple current working information using multiple target statistical strategies to obtain multiple current statistical information.

[0129] Next, combine Figure 5 Determining multiple current statistics is described.

[0130] Figure 5 A schematic diagram of determining multiple current statistical information provided by an embodiment of the present application. Figure 5 As shown, multiple current working information of the target distributed node is determined, statistical processing is performed according to multiple indicator dimensions to obtain multiple statistical values, and statistical processing is performed through the target statistical strategy corresponding to each statistical value to obtain multiple current statistical information.

[0131] S307: Determine historical statistical information of the target distributed node, and input multiple current statistical information and historical statistical information into a prediction model to obtain multiple current improvement measures.

[0132] Among them, the prediction model determines the problems that occur in the work team based on current statistical information and historical statistical information, and determines the corresponding current improvement measures based on the problems.

[0133] A feasible implementation method, a training method for a prediction model may include: obtaining sample data, the sample data including multiple groups of statistical information, each group of statistical information including first statistical information, second statistical information, and sample improvement measures, the time of the first statistical information is later than the time of the second statistical information; using the first statistical information and the second statistical information as input, and using the sample improvement measures as labels to perform model training to obtain a prediction model, the prediction model being used to obtain improvement measures by comparing the first statistical information and the second statistical information.

[0134] The second statistical information is used as a reference standard for the first statistical information for model training.

[0135] Optionally, information is extracted from historical information, data cleaning is performed, and useful features are extracted to obtain multiple sets of statistical information.

[0136] Optionally, the prediction model is continuously iterated and optimized through the newly generated information of each subscribing distributed node to improve the prediction accuracy of the prediction model.

[0137] In this feasible implementation, by training the first statistical information and the second statistical information model, the prediction model can accurately learn the relationship between the statistical information at different times, thereby improving the prediction accuracy of the prediction model.

[0138] S308: Determine the weight corresponding to each current statistical information.

[0139] Optionally, the weights are adjusted dynamically based on the actual work content.

[0140] Combined with the scenario example, weights are used to indicate the degree of influence of each current statistical information on the overall evaluation.

[0141] S309: Perform weighted sum processing on each current statistical information according to the weight corresponding to each current statistical information to obtain the target statistical information of the target work team.

[0142] Combined with the scenario example, multiple current statistical information can be fused through weights to obtain target statistical information, which evaluates the real-time work information of the target work team as a whole.

[0143] Optionally, the overall work completion degree of the target work team is determined by comparing the target statistical information with a preset threshold.

[0144] S310, uploading each current statistical information, the corresponding current improvement measures, and the target statistical information to the blockchain, so that the blockchain generates warning information for the target work team.

[0145] For example, generating warning information through blockchain can improve the transparency and integrity of the warning information.

[0146] Next, combine Figure 6 Describes the generation of alarm information.

[0147] Figure 6 This is a schematic diagram of generating alarm information provided by an embodiment of the present application. Figure 6 As shown, a weighted summation process is performed on multiple current statistical information according to corresponding weights to obtain target statistical information, and alarm information is generated through multiple current statistical information, multiple current improvement measures, and multiple target statistical information.

[0148] S311. Send the warning information to the project management platform so that the project management platform can complete the warning prompt to the target work team.

[0149] It should be noted that the execution process of S311 refers to S205 and will not be repeated here.

[0150] Figure 7A schematic diagram of a test team work evaluation alarm device for an information-based R&D project provided in an embodiment of the present application. Figure 7 As shown, the test team work evaluation alarm device 70 of the information technology R&D project may include: an extraction module 71, a statistical module 72, a prediction module 73, a generation module 74, and a sending module 75, wherein:

[0151] The extraction module 71 is used to extract multiple current work information of the target distributed nodes of the blockchain through the subscription function, wherein the distributed nodes of the blockchain correspond one-to-one to the work teams.

[0152] The statistical module 72 is used to determine multiple target statistical strategies, and perform statistical processing on multiple current work information through the multiple target statistical strategies to obtain multiple current statistical information, wherein the current statistical information is used to indicate the degree of work completion.

[0153] The prediction module 73 is used to determine the historical statistical information of the target distributed node, input multiple current statistical information and historical statistical information into the prediction model to obtain multiple current improvement measures, wherein the current improvement measures are used to improve the degree of work completion.

[0154] The generation module 74 is used to upload each current statistical information and the corresponding current improvement measures to the blockchain, so that the blockchain generates warning information to the target work team according to each current statistical information and the corresponding current improvement measures.

[0155] The sending module 75 is used to send the warning information to the project management platform so that the project management platform can complete the warning prompt to the target work team.

[0156] Optionally, the extraction module 71 may execute Figure 2 S201 in the embodiment.

[0157] Optionally, the statistics module 72 may execute Figure 2 S202 in the embodiment.

[0158] Optionally, the prediction module 73 may execute Figure 2 S203 in the embodiment.

[0159] Optionally, the generation module 74 may execute Figure 2 S204 in the embodiment.

[0160] Optionally, the sending module 75 may execute Figure 2 S205 in the embodiment.

[0161] It should be noted that the test team work evaluation alarm device for the information-based R&D project shown in the embodiment of the present application can execute the technical solution shown in the above method embodiment, and its implementation principle and beneficial effects are similar, which will not be repeated here.

[0162] In one possible implementation, the extraction module 71 is specifically used to: determine multiple subscribing distributed nodes; extract multiple data records corresponding to the multiple subscribing distributed nodes; and extract multiple current working information of the target distributed nodes of the blockchain based on the multiple data records.

[0163] In a possible implementation, multiple data records include multiple work information; the extraction module 71 is specifically used to: determine multiple generation times corresponding to multiple work information in the multiple data records; determine multiple current work information from the multiple work information based on the multiple generation times, and the intervals between the multiple generation times corresponding to the multiple current work information and the current time are all less than a preset duration.

[0164] In one possible implementation, the extraction module 71 is specifically used to: determine multiple encrypted information from multiple working information according to multiple generation times, wherein the intervals between the multiple generation times corresponding to the multiple encrypted information and the current time are all less than a preset duration; determine the key corresponding to the target distributed node; and decrypt the multiple encrypted information according to the multiple keys to obtain multiple current working information.

[0165] Figure 8 A schematic diagram of a test team work evaluation alarm device for an information-based R&D project provided in an embodiment of the present application. Figure 7 Based on the embodiment shown, Figure 8 As shown, the test team work evaluation alarm device 80 of the information technology R&D project also includes: a processing module 76, an uploading module 77, and a training module 78, wherein:

[0166] The processing module 76 is used to: determine a plurality of statistical types and a plurality of current reference values ​​corresponding to the plurality of statistical types; and determine a plurality of target statistical strategies corresponding to the plurality of statistical types according to the plurality of current reference values.

[0167] The upload module 77 is used to: determine the weight corresponding to each current statistical information; perform weighted sum processing on each current statistical information according to the weight corresponding to each current statistical information to obtain the target statistical information of the target work team; upload each current statistical information, the corresponding current improvement measures, and the target statistical information to the blockchain, so that the blockchain generates warning information for the target work team.

[0168] The training module 78 is used to: obtain sample data, the sample data includes multiple groups of statistical information, each group of statistical information includes first statistical information, second statistical information, and sample improvement measures, the time of the first statistical information is later than the time of the second statistical information; use the first statistical information and the second statistical information as input, and use the sample improvement measures as labels to perform model training to obtain a prediction model, the prediction model is used to obtain improvement measures by comparing the first statistical information and the second statistical information.

[0169] Fig. 9 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application is shown in FIG. Fig. 9 As shown, the electronic device includes:

[0170] The electronic device includes a processor 291 and a memory 292; it may also include a communication interface 293 and a bus 294. The processor 291, the memory 292, and the communication interface 293 may communicate with each other through the bus 294. The communication interface 293 may be used for information transmission. The processor 291 may call the logic instructions in the memory 292 to execute the method of the above embodiment.

[0171] In addition, the logic instructions in the above-mentioned memory 292 can be implemented in the form of software functional units and can be stored in a computer-readable storage medium when sold or used as an independent product.

[0172] The memory 292 is a computer-readable storage medium that can be used to store software programs and computer executable programs, such as program instructions / modules corresponding to the methods in the embodiments of the present application. The processor 291 executes functional applications and data processing by running the software programs, instructions, and modules stored in the memory 292, that is, implementing the methods in the above method embodiments.

[0173] The memory 292 may include a program storage area and a data storage area, wherein the program storage area may store an operating system and an application required for at least one function; the data storage area may store data created according to the use of the terminal device, etc. In addition, the memory 292 may include a high-speed random access memory and may also include a non-volatile memory.

[0174] An embodiment of the present application provides a non-temporary computer-readable storage medium, in which computer-executable instructions are stored. When the computer-executable instructions are executed by a processor, they are used to implement the method as described in the above embodiment.

[0175] An embodiment of the present application provides a computer program product, including a computer program, which implements the method of the above embodiment when the computer program is executed by a processor.

[0176] It should be noted that, for the aforementioned method embodiments, for the sake of simplicity, they are all expressed as a series of action combinations, but those skilled in the art should be aware that the present application is not limited by the described order of actions, because according to the present application, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all optional embodiments, and the actions and modules involved are not necessarily required by the present application.

[0177] It should be further noted that, although the various steps in the flowchart are displayed in sequence according to the indication of the arrows, these steps are not necessarily executed in sequence in the order indicated by the arrows. Unless there is a clear description in this article, the execution of these steps is not strictly limited in order, and these steps can be executed in other orders. Moreover, at least a portion of the steps in the flowchart may include multiple sub-steps or multiple stages, and these sub-steps or stages are not necessarily executed at the same time, but can be executed at different times, and the execution order of these sub-steps or stages is not necessarily to be carried out in sequence, but can be executed in turn or alternately with other steps or at least a portion of the sub-steps or stages of other steps.

[0178] It should be understood that the above-mentioned device embodiments are only illustrative, and the device of the present application can also be implemented in other ways. For example, the division of units / modules in the above-mentioned embodiments is only a logical function division, and there may be other division methods in actual implementation. For example, multiple units, modules or components can be combined, or can be integrated into another system, or some features can be ignored or not executed.

[0179] In addition, unless otherwise specified, each functional unit / module in each embodiment of the present application may be integrated into one unit / module, each unit / module may exist physically separately, or two or more units / modules may be integrated together. The above-mentioned integrated unit / module may be implemented in the form of hardware or in the form of a software program module.

[0180] If the integrated unit / module is implemented in the form of hardware, the hardware may be a digital circuit, an analog circuit, etc. The physical implementation of the hardware structure includes but is not limited to transistors, memristors, etc. The processor may be any appropriate hardware processor, such as CPU, GPU, FPGA, DSP, and ASIC, etc. The storage unit may be any appropriate magnetic storage medium or magneto-optical storage medium, such as Resistive Random Access Memory (RRAM), Dynamic Random Access Memory (DRAM), Static Random Access Memory (SRAM), Enhanced Dynamic Random Access Memory (EDRAM), High-Bandwidth Memory (HBM), Hybrid Memory Cube (HMC), etc.

[0181] If the integrated unit / module is implemented in the form of a software program module and sold or used as an independent product, it can be stored in a computer-readable memory. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product. The computer software product is stored in a memory, including a number of instructions to enable a computer device (which can be a personal computer, server or network device, etc.) to execute all or part of the steps of the various embodiments of the present application. The aforementioned memory includes: U disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), mobile hard disk, disk or optical disk and other media that can store program codes.

[0182] In the above embodiments, the description of each embodiment has its own emphasis. For the part not described in detail in a certain embodiment, please refer to the relevant description of other embodiments. The technical features of the above embodiments can be combined arbitrarily. In order to make the description concise, all possible combinations of the technical features in the above embodiments are not described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0183] Those skilled in the art will readily appreciate other embodiments of the present application after considering the specification and practicing the invention disclosed herein. The present application is intended to cover any modification, use or adaptation of the present application, which follows the general principles of the present application and includes common knowledge or customary techniques in the art that are not disclosed in the present application. The specification and examples are intended to be exemplary only, and the true scope and spirit of the present application are indicated by the following claims.

[0184] It should be understood that the present application is not limited to the precise structures that have been described above and shown in the drawings, and that various modifications and changes may be made without departing from the scope thereof. The scope of the present application is limited only by the appended claims.

Claims

1. A test team work evaluation and warning method for an information technology R&D project, characterized in that: Applicable to servers, including: Extracting multiple current work information of the target distributed node of the blockchain through the subscription function specifically includes: determining multiple subscription distributed nodes of the blockchain through the subscription function; extracting multiple data records corresponding to the multiple subscription distributed nodes, wherein the multiple data records include multiple work information; determining multiple generation moments corresponding to the multiple work information in the multiple data records; determining multiple encryption information from the multiple work information according to the multiple generation moments, wherein the intervals between the multiple generation moments corresponding to the multiple encryption information and the current moment are all less than a preset time length; determining multiple keys corresponding to the multiple subscription distributed nodes; decrypting the multiple encryption information according to the multiple keys to obtain the multiple current work information, wherein the multiple subscription distributed nodes of the blockchain correspond to the work teams one by one; Determine a plurality of target statistical strategies, and perform statistical processing on the plurality of current work information by using the plurality of target statistical strategies to obtain a plurality of current statistical information, wherein the current statistical information is used to indicate the degree of completion of the work; Acquire sample data, the sample data including multiple groups of statistical information, each group of statistical information including first statistical information, second statistical information, and sample improvement measures, the time of the first statistical information being later than the time of the second statistical information; use the first statistical information and the second statistical information as input, use the sample improvement measures as labels to perform model training, and obtain a prediction model, the prediction model is used to obtain the improvement measures by comparing the first statistical information and the second statistical information; Determine historical statistical information of the target distributed node, input the multiple current statistical information and the historical statistical information into a prediction model to obtain multiple current improvement measures, wherein the current improvement measures are used to improve the degree of work completion; Uploading each current statistical information and the corresponding current improvement measure to the blockchain, so that the blockchain generates warning information for the target work team according to each current statistical information and the corresponding current improvement measure; The warning information is sent to the project management platform so that the project management platform can complete the warning prompt to the target work team.

2. The method according to claim 1, characterized in that Identify multiple target statistical strategies, including: Determine a plurality of statistical types and a plurality of current reference values ​​corresponding to the plurality of statistical types; A plurality of target statistical strategies corresponding to the plurality of statistical types are determined according to the plurality of current reference values.

3. The method according to claim 1 or 2, characterized in that: The method further comprises: Determine a weight corresponding to each current statistical information; By using the weight corresponding to each current statistical information, weighted summing processing is performed on each current statistical information to obtain target statistical information of the target work team; Upload each current statistical information, the corresponding current improvement measures, and the target statistical information to the blockchain, so that the blockchain generates warning information for the target work team.

4. A test team work evaluation alarm device for an information technology R&D project, characterized in that: Applicable to servers, including: An extraction module is used to extract multiple current work information of a target distributed node of a blockchain through a subscription function, specifically comprising: determining multiple subscription distributed nodes of the blockchain through a subscription function; extracting multiple data records corresponding to the multiple subscription distributed nodes, wherein the multiple data records include multiple work information; determining multiple generation moments corresponding to the multiple work information in the multiple data records; determining multiple encryption information from the multiple work information according to the multiple generation moments, wherein the intervals between the multiple generation moments corresponding to the multiple encryption information and the current moment are all less than a preset time length; determining multiple keys corresponding to the multiple subscription distributed nodes; decrypting the multiple encryption information according to the multiple keys to obtain the multiple current work information, wherein the multiple subscription distributed nodes of the blockchain correspond to the work teams one by one; A statistical module, used for determining a plurality of target statistical strategies, and performing statistical processing on the plurality of current work information by using the plurality of target statistical strategies to obtain a plurality of current statistical information, wherein the current statistical information is used for indicating the degree of completion of the work; A training module is used to obtain sample data, wherein the sample data includes multiple groups of statistical information, each group of statistical information includes first statistical information, second statistical information, and sample improvement measures, and the time of the first statistical information is later than the time of the second statistical information; the first statistical information and the second statistical information are used as input, and the sample improvement measures are used as labels for model training to obtain a prediction model, wherein the prediction model is used to obtain the improvement measures by comparing the first statistical information and the second statistical information; A prediction module, used to determine the historical statistical information of the target distributed node, input the multiple current statistical information and the historical statistical information into a prediction model to obtain multiple current improvement measures, wherein the current improvement measures are used to improve the degree of work completion; A generation module, used to upload each current statistical information and the corresponding current improvement measure to the blockchain, so that the blockchain generates warning information for the target work team according to each current statistical information and the corresponding current improvement measure; The sending module is used to send the alarm information to the project management platform so that the project management platform can complete the alarm prompt to the target work team.

5. An electronic device, characterized in that: include: A processor, and a memory communicatively connected to the processor; The memory stores computer-executable instructions; The processor executes the computer-executable instructions stored in the memory to implement the method according to any one of claims 1 to 3.

6. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer-executable instructions, which are used to implement the method according to any one of claims 1 to 3 when executed by a processor.

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