CN118014451A

CN118014451A - Data processing method, device, equipment and storage medium of software project

Info

Publication number: CN118014451A
Application number: CN202410425597.8A
Authority: CN
Inventors: 杨光
Original assignee: CCB Finetech Co Ltd
Current assignee: CCB Finetech Co Ltd
Priority date: 2024-04-10
Filing date: 2024-04-10
Publication date: 2024-05-10

Abstract

The application provides a data processing method, a device, equipment and a storage medium of a software project. Relates to the technical field of software development. The method comprises the following steps: acquiring project data of a plurality of target software projects at preset time intervals, extracting files of a plurality of index dimensions in the project data for each target software project, inputting the files of each index dimension into a corresponding pre-trained evaluation model to output evaluation results corresponding to the files of each index dimension, calculating the evaluation values of each index dimension according to the evaluation results corresponding to the files of each index dimension for each target software project, obtaining the final evaluation value of each target software project according to the evaluation values of each index dimension, and generating a corresponding project processing scheme according to the final evaluation values of each target software project. The method provided by the embodiment of the application improves the accuracy and fineness of the quality assessment of the software project, is convenient for finding the problem of each dimension and improves in time.

Description

Data processing method, device, equipment and storage medium of software project

Technical Field

The present application relates to the field of big data technologies, and in particular, to a data processing method, apparatus, device and storage medium for a software project.

Background

After the software project is completed, the project completion quality is effectively assessed by processing the project related data, so that the quality problem can be found, the problem of quality can be effectively avoided in subsequent projects, and the aim of gradually improving the project quality is finally achieved.

In the related art, the project completion quality is generally assessed for project completion time, overall input cost, software test results, and the like.

However, in implementing the present application, the inventors found that at least the following problems exist in the prior art: the existing software project quality assessment mode has single dimension and poor accuracy and fineness.

Disclosure of Invention

The application provides a data processing method, device, equipment and storage medium of a software project, which are used for solving the problems of single dimension, poor accuracy and fineness of quality assessment of the software project in the prior art.

In a first aspect, the present application provides a data processing method of a software item, applied to a service device, including:

acquiring project data of a plurality of target software projects at intervals of preset time;

extracting files of a plurality of index dimensions in the project data for each target software project; inputting the file of each index dimension into a corresponding pre-trained evaluation model to output an evaluation result corresponding to the file of each index dimension;

Aiming at each target software project, calculating the evaluation value of each index dimension according to the evaluation result corresponding to the file of each index dimension; obtaining a final evaluation value of the target software project according to the evaluation values of the index dimensions;

Generating a corresponding project processing scheme according to the final evaluation value of each target software project; and sending each item processing scheme to corresponding terminal equipment corresponding to each corresponding manager identifier.

In one possible design, the file for the plurality of index dimensions includes: record files executed by the research and development specifications, record files used by tools and record files managed by the research and development process;

Correspondingly, the inputting the files of each index dimension into the corresponding pre-trained evaluation model to output the evaluation result corresponding to the files of each index dimension comprises the following steps:

Inputting a record file of the research and development specification execution into a pre-trained specification execution evaluation model to output a first evaluation result of the research and development specification execution dimension;

Inputting the record file of the tool use into a pre-trained tool use evaluation model to output a second evaluation result of the tool use dimension;

And inputting the record file of the research and development process management into a pre-trained research and development process management evaluation model to output a third evaluation result of the research and development process management dimension.

In one possible design, the calculating, for each target software item, the evaluation value of each index dimension according to the evaluation result corresponding to the file of each index dimension includes:

Identifying a plurality of first evaluation fields from the first evaluation result, converting the plurality of first evaluation fields into a plurality of first scores, and calculating according to the plurality of first scores to obtain a first evaluation value of the research and development specification execution dimension;

identifying a plurality of second evaluation fields from the second evaluation results; converting the plurality of second evaluation fields into a plurality of second scores, and calculating to obtain a second evaluation value of the tool use dimension according to the plurality of second scores;

identifying a plurality of third evaluation fields from the third evaluation results; and converting the plurality of third evaluation fields into a plurality of third scores, and calculating to obtain a third evaluation value of the tool use dimension according to the plurality of third scores.

In one possible design, the obtaining the final evaluation value of the target software item according to the evaluation value of each index dimension includes:

Acquiring a first weight parameter corresponding to a first evaluation value of the target software item, acquiring a second weight parameter corresponding to a second evaluation value of the target software item, and acquiring a third weight parameter corresponding to a third evaluation value of the target software item;

And carrying out weighted summation on the first evaluation value, the second evaluation value and the third evaluation value according to the first weight parameter, the second weight parameter and the third weight parameter to obtain a final evaluation value of the target software item.

In one possible design, the method further comprises:

Acquiring a first average value of a first evaluation value, a second average value of a second evaluation value and a third average value of a third evaluation value of each target software item with a final evaluation value smaller than a preset value;

And reducing the weight parameter corresponding to the maximum value of the first average value, the second average value and the third average value by a preset amplitude, and increasing the weight parameter corresponding to the minimum value of the first average value, the second average value and the third average value by the preset amplitude to obtain a new weight parameter so as to calculate the final evaluation value of the target software item based on the new weight parameter in a subsequent preset time interval.

Acquiring a first reference value corresponding to a first evaluation value of the target software item, and determining a first ratio between the first evaluation value and the first reference value; the first reference value is the average value of the first evaluation values of all the target software items, or the implementation state of all the software items in the database is identified as the average value of the first evaluation values of all the completed target software items;

Acquiring a second reference value corresponding to a second evaluation value of the target software item, and determining a second ratio between the second evaluation value and the second reference value; the second reference value is the average value of the second evaluation values of all the target software items, or the implementation state of all the software items in the database is identified as the average value of the second evaluation values of all the completed target software items;

Acquiring a third reference value corresponding to a third evaluation value of the target software item, and determining a third ratio between the third evaluation value and the third reference value; the third reference value is an average value of third evaluation values of all target software items, or an average value of third evaluation values of all completed target software items in the implementation state identification in all software items in the database;

and determining the sum of the first product of the first ratio and the first evaluation value, the second product of the second ratio and the second evaluation value and the third product of the third ratio and the third evaluation value as a final evaluation value of the target software item.

In one possible design, the method further includes the pre-trained specification performing a training process of an assessment model, including:

acquiring record files of research and development specification execution of a plurality of target software projects; the record files executed by the development specifications comprise a plurality of record files of specification types;

labeling the record files executed by each research and development specification to obtain corresponding samples; the label is used for indicating whether the label meets the specification; the sample includes a plurality of canonical type subsamples;

classifying the plurality of sub-samples according to the specification types to obtain sample groups corresponding to the specification types respectively;

For each sample group of the specification type, performing iterative training on the first model based on the sample group of the specification type to obtain a convergence speed corresponding to the specification type and a second model corresponding to the specification type obtained by training;

determining initial parameters of the deep learning model according to model parameters of a second model corresponding to the standard type with the minimum convergence rate;

and performing iterative training on the deep learning model with the initial parameters according to the marked multiple samples to obtain the standard execution evaluation model.

In one possible design, the acquiring item data of a plurality of target software items at preset time intervals includes:

acquiring basic data of all software items in a database at intervals of preset time; wherein the underlying data for each item of software includes an implementation status identifier and an administrator identifier;

Extracting an implementation state identifier in each software item;

Screening out the implementation state identifier from all the software items as each target software item in implementation;

Extracting an administrator identifier of each target software item for each target software item;

according to the manager identifications of all target software items, sending an item data acquisition request to terminal equipment corresponding to each manager identification;

And receiving item data of corresponding target software items sent by each terminal device, wherein the item data of each terminal device is input by each administrator in response to the item data acquisition request through uploading operation on the terminal device.

In one possible design, after the final evaluation value of each target software item is obtained according to the evaluation value of each index dimension, the method further includes:

sorting the final evaluation values of a plurality of target software items from high to low to obtain ranking results corresponding to the current time interval;

determining a target software item corresponding to a rank before a preset rank in a ranking result corresponding to a current time interval as an advanced item, and sending the rank of the advanced item and manager information of the advanced item to all terminal devices;

and determining a target software item corresponding to the rank after the preset rank in the ranking result corresponding to the current time interval as a backward entry, and sending the rank of the backward entry to terminal equipment corresponding to the administrator identifier of the backward entry.

In one possible design, the underlying data for each of the target software items further includes item categories and/or item sizes,

Correspondingly, after obtaining the final evaluation value of each target software item according to the evaluation value of each index dimension, the method further comprises the following steps:

Grouping a plurality of target software items in a current time interval based on item categories to obtain a plurality of first groups; the classification of the item categories is related to at least one of: frequent occurrence, customer demand, and fund demand;

For each first group, sorting a plurality of target software items in the first group according to the final evaluation values of the plurality of target software items in the first group, and obtaining a ranking result corresponding to the first group;

And/or the number of the groups of groups,

Grouping a plurality of the target software items in the current time interval based on the item scale to obtain a plurality of second groups; the division of the project size is related to at least one of: item amount, code amount, item period;

And sequencing a plurality of target software items in the first group according to the final evaluation values of the plurality of target software items in the second group for each second group, and obtaining a ranking result corresponding to the second group.

In one possible design, the method further comprises:

Calculating an accumulated value of evaluation values of index dimensions of each target software item according to each target software item in each preset period; obtaining a final accumulated rating value of the target software item according to each accumulated value;

generating a corresponding item processing scheme according to the final accumulated rating value of each target software item; the preset period includes a plurality of preset time intervals.

In one possible design, the method further comprises:

sending feedback information acquisition interfaces to all terminal equipment; the acquisition interface comprises investigation problems related to the data processing method;

receiving reply content for the survey questions input at the survey interface;

optimizing the index dimension according to the reply content and final evaluation values of each target software item respectively corresponding to a plurality of preset time intervals; the optimization mode comprises the steps of adding index dimensions and/or adjusting the weight of each index dimension.

In a second aspect, the present application provides a data processing apparatus for an item of software, comprising: the acquisition module is used for acquiring project data of a plurality of target software projects at intervals of preset time.

And the model processing module is used for extracting files of a plurality of index dimensions in the item data for each target software item. And inputting the file of each index dimension into a corresponding pre-trained evaluation model to output an evaluation result corresponding to the file of each index dimension.

The determining module is used for calculating the evaluation value of each index dimension according to the evaluation result corresponding to the file of each index dimension aiming at each target software item; and obtaining the final evaluation value of the target software project according to the evaluation values of the index dimensions.

The generating module is used for generating a corresponding project processing scheme according to the final evaluation value of each target software project; and sending each item processing scheme to corresponding terminal equipment corresponding to each corresponding manager identifier.

In a third aspect, an embodiment of the present application provides an electronic device, including: at least one processor and memory; the memory stores computer-executable instructions; the at least one processor executes computer-executable instructions stored in the memory, causing the at least one processor to perform the data processing method of the software item as described above in the first aspect and the various possible designs of the first aspect.

In a fourth aspect, embodiments of the present application provide a computer-readable storage medium, in which computer-executable instructions are stored, which when executed by a processor, implement a data processing method for a software item according to the first aspect and the various possible designs of the first aspect.

In a fifth aspect, embodiments of the present application provide a computer program product comprising a computer program which, when executed by a processor, implements a data processing method for software items as described in the first aspect and the various possible designs of the first aspect.

According to the data processing method, device and equipment and storage medium of the software project, project data of a plurality of target software projects are obtained at intervals of preset time, files of a plurality of index dimensions in the project data are extracted for each target software project, the files of each index dimension are input into a corresponding pre-trained evaluation model for the files of the plurality of index dimensions, evaluation results corresponding to the files of each index dimension are output, evaluation values of each index dimension are calculated for each target software project according to the evaluation results corresponding to the files of each index dimension, final evaluation values of the target software project are obtained according to the evaluation values of each index dimension, corresponding project processing schemes are generated according to the final evaluation values of each target software project, and each project processing scheme is sent to terminal equipment corresponding to each corresponding administrator identifier. According to the method and the device for evaluating the software project, the files of the multiple index dimensions of each target software project in implementation are obtained, the files of the multiple index dimensions are identified through the evaluation model, the evaluation value of each index dimension is obtained, the software project can be evaluated from the multiple dimensions, the accuracy and the fineness of the quality evaluation of the software project are improved, the problem of each dimension can be found conveniently, and the method and the device are improved in time.

Drawings

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

Fig. 1 is an application scenario schematic diagram of a data processing method of a software project according to an embodiment of the present application;

FIG. 2 is a flowchart of a data processing method for a software project according to an embodiment of the present application;

FIG. 3 is a schematic diagram of a data processing method of a software project according to an embodiment of the present application;

FIG. 4 is a second flowchart of a data processing method of a software project according to an embodiment of the present application;

FIG. 5 is a schematic diagram of a data processing apparatus for a software project according to an embodiment of the present application;

Fig. 6 is a schematic structural diagram of an electronic device according to an embodiment of the present application.

Specific embodiments of the present application have been shown by way of the above drawings and will be described in more detail below. The drawings and the written description are not intended to limit the scope of the inventive concepts in any way, but rather to illustrate the inventive concepts to those skilled in the art by reference to the specific embodiments.

Detailed Description

Reference will now be made in detail to exemplary embodiments, examples of which are illustrated in the accompanying drawings. When the following description refers to the accompanying drawings, the same numbers in different drawings refer to the same or similar elements, unless otherwise indicated. The implementations described in the following exemplary examples do not represent all implementations consistent with the application. Rather, they are merely examples of apparatus and methods consistent with aspects of the application as detailed in the accompanying claims.

In the technical scheme of the application, the related processes of collecting, storing, using, processing, transmitting, providing, disclosing and the like of the information such as financial data or user data are in accordance with the regulations of related laws and regulations, and the public welfare is not violated.

It should be noted that, in the embodiments of the present application, some existing solutions in the industry such as software, components, models, etc. may be mentioned, and they should be regarded as exemplary, only for illustrating the feasibility of implementing the technical solution of the present application, but it does not mean that the applicant has or must not use the solution.

Aiming at the technical problems of single dimension and poor accuracy and fineness of the existing evaluation mode of the quality of the software project, the inventor researches and discovers that the monitoring indexes of a plurality of dimensions can be established for the operation flow and the operation quality in the software research and development process, the index data of the software project in each dimension are obtained, and the index data of each dimension are analyzed, so that the software project is accurately evaluated, and the problems in the software project are discovered so as to improve pertinence. Based on the above, the embodiment of the application provides a data processing method of a software project.

Fig. 1 is an application scenario schematic diagram of a data processing method of a software project according to an embodiment of the present application. As shown in fig. 1, a server 101 is connected to a database server 102 via a network, and a plurality of terminal devices 103 are connected to the server 101 via a network.

In a specific implementation process, the server 101 acquires basic data of all software items in the database server 102 at preset time intervals, wherein the basic data of each software item comprises an implementation state identifier and an administrator identifier, the implementation state identifier in each software item is extracted, the implementation state identifier is screened out from all the software items as each target software item in implementation, the administrator identifier of each target software item is extracted for each target software item, according to the administrator identifier of each target software item, an item data acquisition request is sent to a terminal device 103 corresponding to each administrator identifier, item data of the corresponding target software item sent by each terminal device 103 is received, wherein the item data of each terminal device 103 is input by each administrator in response to the item data acquisition request on the terminal device, files of a plurality of index dimensions in the item data are extracted for each target software item, the files of each index dimension are input into a corresponding pre-trained evaluation model for each target software item, so as to output a corresponding evaluation result of the file of each index dimension, the corresponding evaluation value is calculated for each corresponding evaluation item, the corresponding evaluation item is calculated for each corresponding evaluation item dimension, and the corresponding evaluation item is processed according to each evaluation item dimension, and the final evaluation value is generated according to a corresponding evaluation value of each target item, and the final evaluation value is generated. According to the data processing method for the software project, provided by the embodiment of the application, the files of the multiple index dimensions of each target software project in implementation are obtained, and the files of the multiple index dimensions are identified and processed through the evaluation model to obtain the evaluation value of each index dimension, so that the software project can be evaluated from the multiple dimensions, the accuracy and fineness of the quality evaluation of the software project are improved, the problem of each dimension is conveniently found, and the problem is timely improved.

The following describes the technical scheme of the present application and how the technical scheme of the present application solves the above technical problems in detail with specific embodiments. The following embodiments may be combined with each other, and the same or similar concepts or processes may not be described in detail in some embodiments. Embodiments of the present application will be described below with reference to the accompanying drawings.

Based on the application scenario shown in fig. 1, the embodiment of the application further provides a data processing method of the software project. Fig. 2 is a flowchart of a data processing method of a software project according to an embodiment of the present application. As shown in fig. 2, the data processing method of the software project includes:

201. And acquiring project data of a plurality of target software projects at preset time intervals.

Specifically, every predetermined time interval, for example, two weeks, the software items in progress recorded in the database in two weeks are screened out as target software items, and evaluation values are calculated by the method according to the present embodiment. The target software item may be obtained based on a preset condition screening, such as an item started in a current time interval, or an item in progress, or an item whose progress delay exceeds a preset value, or the like. The project data may include written code, conducted test data, and the like.

In some embodiments, acquiring item data of a plurality of target software items at preset time intervals may include: acquiring basic data of all software items in a database at intervals of preset time; wherein the underlying data for each item of software includes an implementation status identifier and an administrator identifier; extracting an implementation state identifier in each software item; and screening out the implementation state identification from all the software items as each target software item in the implementation. Extracting an administrator identifier of each target software item for each target software item; according to the manager identifications of all target software items, sending an item data acquisition request to terminal equipment corresponding to each manager identification; and receiving item data of corresponding target software items sent by each terminal device, wherein the item data of each terminal device is input by each administrator in response to the item data acquisition request through uploading operation on the terminal device.

In this embodiment, the implementation status identifier may be an identifier that is not implemented, is completed, etc.

Specifically, different target software items correspond to different administrators, for example, an item responsible person, and the item responsible person can manage item data of the responsible software item through own interrupt equipment, so after determining the target software item, the terminal equipment of the administrator can be determined based on the administrator identification of the item recorded in the database, so as to send a request of the item data to the corresponding terminal equipment, and the administrator can upload the corresponding item data based on the request.

202. For each target software project, a file of a plurality of index dimensions in the project data is extracted. And inputting the file of each index dimension into a corresponding pre-trained evaluation model to output an evaluation result corresponding to the file of each index dimension.

Specifically, in order to control quality of a software project in different stages such as a requirement stage, a framework design stage and a test stage, the staged results (such as a business requirement specification, a software specification, various version codes and the like) in the different stages can be divided into dimensions such as a research and development specification execution index dimension, a tool use index dimension, a research and development process management effect and the like.

In some embodiments, wherein the file of the plurality of index dimensions comprises: record files executed by the research and development specifications, record files used by tools and record files managed by the research and development process; accordingly, as shown in fig. 3, the inputting the file of each index dimension into the corresponding pre-trained evaluation model for the file of a plurality of index dimensions to output the evaluation result corresponding to the file of each index dimension may include: inputting a record file of the research and development specification execution into a pre-trained specification execution evaluation model to output a first evaluation result of the research and development specification execution dimension; inputting the record file of the tool use into a pre-trained tool use evaluation model to output a second evaluation result of the tool use dimension; and inputting the record file of the research and development process management into a pre-trained research and development process management evaluation model to output a third evaluation result of the research and development process management dimension.

In particular, record files executed by the development specification may include code specification record files, document asset specification record files, and the like. For the coding specification, a script tool can be adopted to detect various items such as code logic, statement use correctness and the like of the code written specification, and a coding specification record file is obtained. Aiming at document asset specifications, corresponding delivery piece templates can be established for documents to be delivered in the development process of business requirement specifications, software specifications and the like, and detection of whether the submitted delivery pieces accord with the delivery piece templates, whether filling content is complete and the like is carried out aiming at each submitted delivery piece, so that the obtained document specification records files.

The record files used by the tool can comprise the use conditions of various tools such as code submission version management tools, test stage case execution progress tracking tools, defect resolution progress tracking tools and the like, and particularly, the login information of a tool menu can be obtained from a system log of each management platform (such as a code management platform, a test management platform, a defect management platform and the like) and used as the record files used by the tool.

The record file for the development process management may include: the system comprises a record file for demand analysis management, a record file for code walk management, a record file for integrated test submission management and a record file for production scheme management. The record file of the requirement analysis management can comprise the contents of the planning time, the actual execution time, the number of reviews, the review result of each review and the like of the requirement analysis; the record file of the code walking management can comprise the content such as the qualification rate of the code; the record file integrating the test submission management can comprise the contents of test planning time, actual execution time and the like; the record file of the production scheme management can comprise the contents of each production stage task, the execution time of each stage task and the like.

In this embodiment, the evaluation models corresponding to the index dimensions may be obtained by training separately, and specifically, a supervised training mode may be adopted. For each index dimension, a relevant record file of the historical software project can be obtained, the record file is labeled, a sample set is constructed, and the corresponding neural network model is trained based on the sample set to obtain an evaluation model under the corresponding index dimension.

The training process of the evaluation model will be exemplarily described below by taking the specification execution of the evaluation model as an example.

In some embodiments, the pre-trained specification performs a training process of the assessment model, which may include: acquiring record files of research and development specification execution of a plurality of target software projects; the record files executed by the development specifications comprise a plurality of record files of specification types; labeling the record files executed by each research and development specification to obtain corresponding samples; the label is used for indicating whether the label meets the specification; the sample includes a plurality of canonical type subsamples; classifying the plurality of sub-samples according to the specification types to obtain sample groups corresponding to the specification types respectively; for each sample group of the specification type, performing iterative training on the first model based on the sample group of the specification type to obtain a convergence speed corresponding to the specification type and a second model corresponding to the specification type obtained by training; determining initial parameters of the deep learning model according to model parameters of a second model corresponding to the standard type with the minimum convergence rate; and performing iterative training on the deep learning model with the initial parameters according to the marked multiple samples to obtain the standard execution evaluation model.

Specifically, the specification execution index dimension includes a plurality of sub-indexes, and considering that the contents of the record files of different indexes are different, and meanwhile, the record files of different types are used as samples to perform model training, so that the model training is not easy to converge, therefore, different types of sample sets can be firstly constructed, the sample sets of corresponding types are adopted to perform training for different types, further, different types of convergence speeds are obtained, the convergence speed can be determined based on iteration times or training time, the slow convergence speed indicates that the model training is not easy to converge, and therefore, model parameters of a second model with the slowest convergence speed can be adopted as initial parameters of a deep learning model, so that the training speed can be improved when the deep learning model is trained, and the training efficiency is improved.

The first model may be a text classification model such as Fasttext, textCNN, DPCNN, textRCNN, textBiLSTM + Attention, HAN, BERT. The first model and the deep learning model are the same type of model.

In this embodiment, when performing iterative training on the first model or performing iterative training on the deep learning model, a gradient descent mode may be adopted, and the loss function may be the following formula:

（1）

Wherein K is the number of categories, and K categories are shared; x _ib is a sign function (0 or 1), taking 1 if the prediction class of sample i is equal to b, otherwise taking 0; q _ib is the predicted probability that the observation i belongs to class b, typically the softmax value.

203. Aiming at each target software project, calculating the evaluation value of each index dimension according to the evaluation result corresponding to the file of each index dimension; and obtaining the final evaluation value of the target software project according to the evaluation values of the index dimensions.

Specifically, the file of each index dimension may include a plurality of sub-indexes, and the evaluation result obtained after inputting the file of each index dimension into the corresponding evaluation model may include the sub-results of the plurality of sub-indexes, and further, after the evaluation result output by the model is obtained, the plurality of sub-results may be identified to obtain a plurality of evaluation fields, so that the evaluation value corresponding to the index dimension may be determined based on the plurality of evaluation fields.

In some embodiments, for each target software item, calculating the evaluation value of each index dimension according to the evaluation result corresponding to the file of each index dimension may include: identifying a plurality of first evaluation fields from the first evaluation result, converting the plurality of first evaluation fields into a plurality of first scores, and calculating according to the plurality of first scores to obtain a first evaluation value of the research and development specification execution dimension; identifying a plurality of second evaluation fields from the second evaluation results; converting the plurality of second evaluation fields into a plurality of second scores, and calculating to obtain a second evaluation value of the tool use dimension according to the plurality of second scores; identifying a plurality of third evaluation fields from the third evaluation results; and converting the plurality of third evaluation fields into a plurality of third scores, and calculating to obtain a third evaluation value of the tool use dimension according to the plurality of third scores.

Specifically, the development specification execution index dimension may correspond to an encoding specification evaluation field and a document asset specification record file evaluation field. The tool usage index dimension may correspond to a code submission version management tool usage assessment field, a test phase case execution progress tracking tool usage assessment field, and a defect resolution progress tracking tool usage assessment field. The research and development process management index dimension can correspond to a demand analysis management evaluation field, a code walk management evaluation field, an integrated test submission management evaluation field and a production scheme management evaluation field.

In some embodiments, the weight of each index dimension may be set according to a management direction (for example, the supervision degree of a certain index dimension needs to be improved in management), so as to adjust the influence degree of different index dimensions on the final evaluation value. Specifically, as shown in fig. 3, the obtaining the final evaluation value of the target software item according to the evaluation value of each index dimension may include: acquiring a first weight parameter corresponding to a first evaluation value of the target software item, acquiring a second weight parameter corresponding to a second evaluation value of the target software item, and acquiring a third weight parameter corresponding to a third evaluation value of the target software item; and carrying out weighted summation on the first evaluation value, the second evaluation value and the third evaluation value according to the first weight parameter, the second weight parameter and the third weight parameter to obtain a final evaluation value of the target software item.

In some embodiments, the weight parameter may be automatically adjusted according to the evaluation value of each index dimension of the previous software item, so as to increase the weight of the index dimension with low evaluation value and decrease the weight of the index dimension with high evaluation value. The method may further comprise: acquiring a first average value of a first evaluation value, a second average value of a second evaluation value and a third average value of a third evaluation value of each target software item with a final evaluation value smaller than a preset value; and reducing the weight parameter corresponding to the maximum value of the first average value, the second average value and the third average value by a preset amplitude, and increasing the weight parameter corresponding to the minimum value of the first average value, the second average value and the third average value by the preset amplitude to obtain a new weight parameter so as to calculate the final evaluation value of the target software item based on the new weight parameter in a subsequent preset time interval.

Specifically, since the index dimension with a high evaluation value indicates that there are few problems and the index dimension with a low evaluation value indicates that there are many problems, the weight of the index dimension with a low evaluation value can be increased to raise the importance of the related personnel, and the weight of the index dimension with a high evaluation value can be decreased to reach the conventional average level with a small input.

In some embodiments, to prevent the occurrence of a step back, the evaluation value of the current item may be scaled based on the average value of each item to achieve the objective of enhancing the overall level of incentive, where the obtaining the final evaluation value of the target software item according to the evaluation value of each index dimension may include: acquiring a first reference value corresponding to a first evaluation value of the target software item, and determining a first ratio between the first evaluation value and the first reference value; the first reference value is the average value of the first evaluation values of all the target software items, or the implementation state of all the software items in the database is identified as the average value of the first evaluation values of all the completed target software items; acquiring a second reference value corresponding to a second evaluation value of the target software item, and determining a second ratio between the second evaluation value and the second reference value; the second reference value is the average value of the second evaluation values of all the target software items, or the implementation state of all the software items in the database is identified as the average value of the second evaluation values of all the completed target software items; acquiring a third reference value corresponding to a third evaluation value of the target software item, and determining a third ratio between the third evaluation value and the third reference value; the third reference value is an average value of third evaluation values of all target software items, or an average value of third evaluation values of all completed target software items in the implementation state identification in all software items in the database; and determining the sum of the first product of the first ratio and the first evaluation value, the second product of the second ratio and the second evaluation value and the third product of the third ratio and the third evaluation value as a final evaluation value of the target software item.

204. Generating a corresponding project processing scheme according to the final evaluation value of each target software project; and sending each item processing scheme to corresponding terminal equipment corresponding to each corresponding manager identifier.

Specifically, after the final evaluation value of the target software project is obtained, a processing scheme of the project may be determined based on the final evaluation value, where the processing scheme may include whether adjustment or rework is required for the corresponding job, for example, if the delivery document does not use a template or has incomplete filling content, the delivery document may need to be reworked and reissued. After the processing scheme is formed, the processing scheme may be sent to the terminal device corresponding to the administrator identifier to execute the project processing scheme.

According to the data processing method for the software project, provided by the embodiment of the application, the files of the multiple index dimensions of each target software project in implementation are obtained, and the files of the multiple index dimensions are identified and processed through the evaluation model to obtain the evaluation value of each index dimension, so that the software project can be evaluated from the multiple dimensions, the accuracy and fineness of the quality evaluation of the software project are improved, the problem of each dimension is conveniently found, and the problem is timely improved.

Fig. 4 is a flowchart of a data processing method of a software project according to an embodiment of the present application. As shown in fig. 4, the data processing method of the software project includes the following steps:

401. Acquiring basic data of all software items in a database at intervals of preset time; wherein the underlying data for each item of software includes an implementation status identifier and an administrator identifier; extracting an implementation state identifier in each software item; and screening out the implementation state identification from all the software items as each target software item in the implementation.

402. Extracting an administrator identifier of each target software item for each target software item; according to the manager identifications of all target software items, sending an item data acquisition request to terminal equipment corresponding to each manager identification; and receiving item data of corresponding target software items sent by each terminal device, wherein the item data of each terminal device is input by each administrator in response to the item data acquisition request through uploading operation on the terminal device.

403. For each target software project, a file of a plurality of index dimensions in the project data is extracted. And inputting the file of each index dimension into a corresponding pre-trained evaluation model to output an evaluation result corresponding to the file of each index dimension.

404. Aiming at each target software project, calculating the evaluation value of each index dimension according to the evaluation result corresponding to the file of each index dimension; and obtaining the final evaluation value of the target software project according to the evaluation values of the index dimensions.

405. Generating a corresponding project processing scheme according to the final evaluation value of each target software project; and sending each item processing scheme to corresponding terminal equipment corresponding to each corresponding manager identifier.

406. And sending the ranking results of the target software items with the final evaluation values larger than the first preset value to all terminal devices, and respectively sending the ranking results of the target software items with the final evaluation values smaller than the second preset value to the corresponding terminal devices.

In some embodiments, the final evaluation values of the multiple target software items may be ranked from high to low, so as to obtain a ranking result corresponding to the current time interval; determining a target software item corresponding to a rank before a preset rank in a ranking result corresponding to a current time interval as an advanced item, and sending the rank of the advanced item and manager information of the advanced item to all terminal devices; and determining a target software item corresponding to the rank after the preset rank in the ranking result corresponding to the current time interval as a backward entry, and sending the rank of the backward entry to terminal equipment corresponding to the administrator identifier of the backward entry.

407. And determining ranking results under different item categories and ranking results under different item scales according to the final evaluation value of each target software item.

The underlying data for each target software project also includes project categories and/or project sizes.

In some embodiments, a plurality of the target software items within the current time interval may be grouped based on item category, obtaining a plurality of first groupings; the classification of the item categories is related to at least one of: frequent occurrence, customer demand, and fund demand; for each first group, sorting a plurality of target software items in the first group according to the final evaluation values of the plurality of target software items in the first group, and obtaining a ranking result corresponding to the first group; and/or grouping a plurality of the target software items within the current time interval based on the item scale to obtain a plurality of second groupings; the division of the project size is related to at least one of: item amount, code amount, item period; and sequencing a plurality of target software items in the first group according to the final evaluation values of the plurality of target software items in the second group for each second group, and obtaining a ranking result corresponding to the second group.

408. And for each preset period, determining the accumulated rating value of each target software item in the preset period according to the final rating value of each target software item in each preset time interval included in the preset period.

In some embodiments, for each target software item in each preset period, an accumulated value of the evaluation values of the index dimensions of the target software item may be calculated; obtaining a final accumulated rating value of the target software item according to each accumulated value; generating a corresponding item processing scheme according to the final accumulated rating value of each target software item; the preset period includes a plurality of preset time intervals.

409. And acquiring feedback data aiming at the data processing method and final evaluation values of all target software items in a plurality of preset time intervals, and optimizing the data processing method.

In some embodiments, a feedback information collection interface may be sent to all terminal devices; the acquisition interface comprises investigation problems related to the data processing method; receiving reply content for the survey questions input at the survey interface; optimizing the index dimension according to the reply content and final evaluation values of each target software item respectively corresponding to a plurality of preset time intervals; the optimization mode comprises the steps of adding index dimensions and/or adjusting the weight of each index dimension.

According to the data processing method for the software project, the files of the multiple index dimensions of each target software project in implementation are obtained, the files of the multiple index dimensions are identified through the evaluation model, the evaluation value of each index dimension is obtained, the software project can be evaluated from the multiple dimensions, accuracy and fineness of quality evaluation of the software project are improved, problems of the various dimensions are found conveniently, the problems are improved in time, in addition, a user can know the management and control conditions of the software project from the multiple dimensions by applying the final evaluation value of the target software project from the multiple dimensions, the problems can be found timely, and the project quality is improved.

Fig. 5 is a schematic structural diagram of a data processing device for a software project according to an embodiment of the present application. As shown in fig. 5, the data processing apparatus 50 of the software item includes: an acquisition module 501, a model processing module 502, a determination module 503, and a generation module 504;

The acquiring module 501 is configured to acquire project data of a plurality of target software projects at preset time intervals.

The model processing module 502 is configured to extract, for each target software project, a file of multiple index dimensions in the project data. And inputting the file of each index dimension into a corresponding pre-trained evaluation model to output an evaluation result corresponding to the file of each index dimension.

A determining module 503, configured to calculate, for each target software item, an evaluation value of each index dimension according to an evaluation result corresponding to the file of each index dimension; and obtaining the final evaluation value of the target software project according to the evaluation values of the index dimensions.

The generating module 504 is configured to generate a corresponding project processing scheme according to the final evaluation value of each target software project; and sending each item processing scheme to corresponding terminal equipment corresponding to each corresponding manager identifier.

According to the data processing device for the software project, provided by the embodiment of the application, the files of the multiple index dimensions of each target software project in implementation are obtained, and the files of the multiple index dimensions are identified and processed through the evaluation model to obtain the evaluation value of each index dimension, so that the software project can be evaluated from the multiple dimensions, the accuracy and fineness of the quality evaluation of the software project are improved, the problem of each dimension is conveniently found, and the problem is timely improved.

In some embodiments, the files of the plurality of index dimensions include: record files executed by the research and development specifications, record files used by tools and record files managed by the research and development process;

The model processing module 502 is specifically configured to:

In some embodiments, the determining module 503 is specifically configured to:

In some embodiments, the determining module 503 is further configured to:

In some embodiments, the determining module 503 is specifically configured to:

In some embodiments, the apparatus 50 further comprises a model training module for:

In some embodiments, the determining module 503 is further configured to:

In some embodiments, wherein the underlying data for each target software project further includes project category and/or project size,

Accordingly, the determining module 503 is further configured to:

And/or the number of the groups of groups,

In some embodiments, the determining module 503 is further configured to: calculating an accumulated value of evaluation values of index dimensions of each target software item according to each target software item in each preset period; obtaining a final accumulated rating value of the target software item according to each accumulated value;

In some embodiments, the determining module 503 is further configured to: sending feedback information acquisition interfaces to all terminal equipment; the acquisition interface comprises investigation problems related to the data processing method;

receiving reply content for the survey questions input at the survey interface;

The data processing device for a software item provided in the embodiment of the present application may be used to execute the technical scheme of the data processing method for a software item in the above embodiment, and its implementation principle and technical effects are similar, and are not described herein again.

It should be noted that, it should be understood that the division of the modules of the above apparatus is merely a division of a logic function, and may be fully or partially integrated into a physical entity or may be physically separated. And these modules may all be implemented in software in the form of calls by the processing element; or can be realized in hardware; the method can also be realized in a form of calling software by a processing element, and the method can be realized in a form of hardware by a part of modules. For example, the model processing module 502 may be a processing element that is set up separately, may be implemented in a chip of the above-described apparatus, or may be stored in a memory of the above-described apparatus in the form of program codes, and the functions of the model processing module 502 may be called and executed by a processing element of the above-described apparatus. The implementation of the other modules is similar. In addition, all or part of the modules can be integrated together or can be independently implemented. The processing element here may be an integrated circuit with signal processing capabilities. In implementation, each step of the above method or each module above may be implemented by an integrated logic circuit of hardware in a processor element or an instruction in a software form.

Fig. 6 is a schematic structural diagram of an electronic device according to an embodiment of the present application. As shown in fig. 6, the electronic device may include: processor 601, memory 602.

The processor 601 executes computer-executable instructions stored in the memory, causing the processor 601 to execute the arrangements of the embodiments described above. The processor 601 may be a general-purpose processor including a central processing unit CPU, a network processor (network processor, NP), etc.; but may also be a digital signal processor DSP, an application specific integrated circuit ASIC, a field programmable gate array FPGA or other programmable logic device, a discrete gate or transistor logic device, a discrete hardware component.

The memory 602 is coupled to the processor 601 via a system bus and communicates with each other, the memory 602 being adapted to store computer program instructions.

The system bus may be a peripheral component interconnect (PERIPHERAL COMPONENT INTERCONNECT, PCI) bus, or an extended industry standard architecture (extended industry standard architecture, EISA) bus, among others. The system bus may be classified into an address bus, a data bus, a control bus, and the like. For ease of illustration, the figures are shown with only one bold line, but not with only one bus or one type of bus. The transceiver is used to enable communication between the database access device and other computers (e.g., clients, read-write libraries, and read-only libraries). The memory may include random access memory (random access memory, RAM) and may also include non-volatile memory (non-volatile memory).

The electronic device provided by the embodiment of the application can be the terminal device of the embodiment.

The embodiment of the application also provides a chip for running the instruction, and the chip is used for executing the technical scheme of the data processing method of the software project in the embodiment.

The embodiment of the application also provides a computer readable storage medium, wherein the computer readable storage medium stores computer instructions, and when the computer instructions run on a computer, the computer is caused to execute the technical scheme of the data processing method of the software project in the embodiment.

The embodiment of the application also provides a computer program product, which comprises a computer program, wherein the computer program is stored in a computer readable storage medium, and at least one processor can read the computer program from the computer readable storage medium, and the technical scheme of the data processing method of the software items in the embodiment can be realized when the at least one processor executes the computer program.

In the several embodiments provided by the present application, it should be understood that the disclosed apparatus and method may be implemented in other ways. For example, the above-described device embodiments are merely illustrative, e.g., the division of modules is merely a logical function division, and there may be additional divisions of actual implementation, e.g., multiple modules may be combined or integrated into another system, or some features may be omitted or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be an indirect coupling or communication connection via some interfaces, devices or modules, which may be in electrical, mechanical, or other forms.

The modules illustrated as separate components may or may not be physically separate, and components shown as modules may or may not be physical units, may be located in one place, or may be distributed over multiple network units. Some or all of the modules may be selected according to actual needs to implement the solution of this embodiment.

In addition, each functional module in the embodiments of the present application may be integrated in one processing unit, or each module may exist alone physically, or two or more modules may be integrated in one unit. The units formed by the modules can be realized in a form of hardware or a form of hardware and software functional units.

The integrated modules, which are implemented in the form of software functional modules, may be stored in a computer readable storage medium. The software functional modules described above are stored in a storage medium and include instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) or processor to perform some of the steps of the methods of the various embodiments of the application.

It should be appreciated that the Processor may be a central processing unit (Central Processing Unit, abbreviated as CPU), or may be other general purpose Processor, digital signal Processor (DIGITAL SIGNAL Processor, abbreviated as DSP), application SPECIFIC INTEGRATED Circuit (ASIC), or the like. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like. The steps of a method disclosed in connection with the present invention may be embodied directly in a hardware processor for execution, or in a combination of hardware and software modules in a processor for execution.

The memory may comprise a high-speed RAM memory, and may further comprise a non-volatile memory NVM, such as at least one magnetic disk memory, and may also be a U-disk, a removable hard disk, a read-only memory, a magnetic disk or optical disk, etc.

The bus may be an industry standard architecture (Industry Standard Architecture, ISA) bus, an external device interconnect (PERIPHERAL COMPONENT INTERCONNECT, PCI) bus, or an extended industry standard architecture (Extended Industry Standard Architecture, EISA) bus, among others. The buses may be divided into address buses, data buses, control buses, etc. For ease of illustration, the buses in the drawings of the present application are not limited to only one bus or to one type of bus.

The storage medium may be implemented by any type or combination of volatile or nonvolatile memory devices such as Static Random Access Memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic or optical disk. A storage media may be any available media that can be accessed by a general purpose or special purpose computer.

An exemplary storage medium is coupled to the processor such the processor can read information from, and write information to, the storage medium. In the alternative, the storage medium may be integral to the processor. The processor and the storage medium may reside in an Application SPECIFIC INTEGRATED Circuits (ASIC). Of course, the processor and the storage medium may reside as discrete components in an electronic control unit or master control device.

Those of ordinary skill in the art will appreciate that: all or part of the steps for implementing the method embodiments described above may be performed by hardware associated with program instructions. The foregoing program may be stored in a computer readable storage medium. The program, when executed, performs steps including the method embodiments described above; and the aforementioned storage medium includes: various media that can store program code, such as ROM, RAM, magnetic or optical disks.

Finally, it should be noted that: the above embodiments are only for illustrating the technical solution of the present application, and not for limiting the same; although the application has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some or all of the technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit of the application.

Claims

1. A data processing method of a software item, characterized by being applied to a service device, comprising:

Extracting files of a plurality of index dimensions in the project data for each target software project; inputting the file of each index dimension into a corresponding pre-trained evaluation model to output an evaluation result corresponding to the file of each index dimension; the pre-trained evaluation model is a neural network model obtained based on a supervised training mode;

Generating a corresponding project processing scheme according to the final evaluation value of each target software project; transmitting each item processing scheme to corresponding terminal equipment corresponding to each corresponding manager identifier;

Wherein the file of the plurality of index dimensions comprises: record files executed by the research and development specifications, record files used by tools and record files managed by the research and development process;

2. The method according to claim 1, wherein for each target software item, calculating the evaluation value of each index dimension according to the evaluation result corresponding to the file of each index dimension includes:

3. The method according to claim 2, wherein the obtaining the final evaluation value of the target software item according to the evaluation value of each index dimension includes:

4. A method according to claim 3, characterized in that the method further comprises:

5. The method according to claim 2, wherein the obtaining the final evaluation value of the target software item according to the evaluation value of each index dimension includes:

6. The method of claim 1, further comprising the pre-trained specification performing a training process of an assessment model, comprising:

7. The method according to any one of claims 1 to 6, wherein obtaining item data of a plurality of target software items at preset time intervals includes:

Extracting an implementation state identifier in each software item;

8. The method according to any one of claims 1 to 6, wherein after obtaining the final evaluation value of each target software item according to the evaluation value of each index dimension, the method further comprises:

9. The method according to any of the claims 1 to 6, wherein the basic data of each target software item further comprises item categories and/or item scales,

And/or the number of the groups of groups,

10. The method according to any one of claims 1 to 6, further comprising:

11. The method according to any one of claims 1 to 6, further comprising:

Receiving reply content for the survey questions input at the acquisition interface;

12. A data processing apparatus of a software item, comprising:

the acquisition module is used for acquiring project data of a plurality of target software projects at intervals of preset time;

The model processing module is used for extracting files of a plurality of index dimensions in the project data for each target software project; inputting the file of each index dimension into a corresponding pre-trained evaluation model to output an evaluation result corresponding to the file of each index dimension; the pre-trained evaluation model is a neural network model obtained based on a supervised training mode;

The determining module is used for calculating the evaluation value of each index dimension according to the evaluation result corresponding to the file of each index dimension aiming at each target software item; obtaining a final evaluation value of the target software project according to the evaluation values of the index dimensions;

The generating module is used for generating a corresponding project processing scheme according to the final evaluation value of each target software project; transmitting each item processing scheme to corresponding terminal equipment corresponding to each corresponding manager identifier;

Correspondingly, the model processing module is specifically configured to:

13. An electronic device, comprising: a processor, and a memory communicatively coupled to the processor;

The memory stores computer-executable instructions;

the processor executes computer-executable instructions stored in the memory to implement the method of any one of claims 1-11.

14. A computer readable storage medium having stored therein computer executable instructions which when executed by a processor are adapted to carry out the method of any one of claims 1-11.

15. A computer program product comprising a computer program which, when executed by a processor, implements the method of any of claims 1-11.