Software development evaluation method and device based on multiple dimensions and electronic equipment

Abstract

The invention discloses a software development evaluation method and device based on multiple dimensions and electronic equipment, and relates to the technical field of software development evaluation or other related technical fields, and the method comprises the following steps: obtaining predefined software development measurement dimensions and measurement indexes, and collecting software development data in a trusted environment; according to a predefined calculation rule, calculating an index value associated with each measurement index in the software development data; according to the index numerical values of all the measurement indexes, performing numerical value scoring on each measurement index to obtain an index score; and based on the index score of each measurement index and the score corresponding to the measurement dimension, generating a software development health degree report according to the report configuration template. The technical problems that a software development measurement mode in related technologies depends on manual operation, and the accuracy of a measurement result is low are solved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of software development processing or other related fields, in particular, to a multi-dimensional based software development evaluation method and device and electronic equipment. BACKGROUND

[0002] In the software development industry, continuous monitoring and evaluation of the health of the software development process is crucial to ensure the smooth progress of the project, improve software quality and team efficiency. Existing software development measurement methods often focus on a single or a few dimensions, such as code quality, defect quantity or time management, which leads to the fact that the measurement results cannot fully reflect the complexity of the software development process and the comprehensive ability of the team, and such measurement methods usually rely on the self-reported data of the developers or use post-processed, lagging indicators for evaluation, which has many limitations, for example: it may ignore the early stages of software development, such as requirement analysis and design, as well as the later stages of testing and deployment, which may lead to critical issues not being discovered and resolved in a timely manner; it may lack consideration of the structure of software team members, skill distribution and work hour utilization efficiency, so that the measurement results cannot accurately reflect the actual input and output of the team; it may not fully consider the economic benefits of software development, i.e. the comparison of software development cost and value.

[0003] In related technologies, the measurement method is inefficient in data collection and processing, relying on a large amount of manual operation, which not only consumes time but also easily introduces errors, affecting the accuracy and reliability of the measurement results. Moreover, due to the opacity of the data, the team members have low recognition of the measurement standards and results, which may reduce the team's enthusiasm and collaboration efficiency.

[0004] In view of the above problems, no effective solution has been proposed so far. SUMMARY

[0005] The embodiments of the present application provide a multi-dimensional based software development evaluation method and device and electronic equipment to at least solve the technical problem of low accuracy of the measurement results in the related art due to the dependence of the software development measurement method on manual operation.

[0006] According to an aspect of an embodiment of the present application, a multi-dimensional based software development evaluation method is provided, comprising: obtaining pre-defined software development measurement dimensions and measurement indicators, and collecting software development data in a trusted environment; calculating the indicator values associated with each of the measurement indicators in the software development data according to a pre-defined calculation rule; performing numerical scoring on each of the measurement indicators based on the indicator values of all the measurement indicators to obtain indicator scores; and generating a software development health report based on the indicator scores of each of the measurement indicators and the scores corresponding to the measurement dimensions according to a report configuration template.

[0007] Optionally, the step of acquiring the predefined software development metric dimensions and metric indicators comprises: reading a plurality of metric dimensions in a software development process from a configuration module, wherein the metric dimensions comprise at least one of the following: a requirement metric dimension, a development metric dimension, a test metric dimension, a release metric dimension, a resource metric dimension, and a cost metric dimension; and reading corresponding metric indicators under each of the metric dimensions, wherein the corresponding metric indicators under the requirement metric dimension comprise a requirement throughput and a requirement delivery cycle, the corresponding metric indicators under the development metric dimension comprise a task throughput and a task value ratio, the corresponding metric indicators under the test metric dimension comprise an automated test execution case ratio, the corresponding metric indicators under the release metric dimension comprise a release frequency score and an online success rate score, the corresponding metric indicators under the resource metric dimension comprise a plurality of level ratio scores, and the corresponding metric indicators under the resource metric dimension comprise a thousand-line code cost score.

[0008] Optionally, the step of collecting the software development data in a trusted environment comprises: connecting a requirement management system, a code management system, a test management system, a production management system, and an online work order system in a trusted environment, automatically pulling required data related to the metric indicators to obtain the software development data; and pre-processing the software development data, wherein the pre-processing operations comprise at least one of the following: data format unification, removal of abnormal values, and removal of duplicate values.

[0009] Optionally, the step of calculating the metric values associated with each of the metric indicators in the software development data according to a predefined calculation rule comprises: calling a pre-defined calculation formula corresponding to each metric indicator according to a predefined calculation rule; and calculating the data associated with each of the metric indicators in the pre-processed software development data using the pre-defined calculation formula to obtain the metric data.

[0010] Optionally, the step of performing numerical scoring on each of the metric indicators according to the metric values of all the metric indicators to obtain indicator scores comprises: calling an indicator scoring formula corresponding to each metric indicator based on a pre-configured scoring rule; and performing scoring processing on the calculated metric values of the metric indicators using the indicator scoring formula to obtain the indicator scores.

[0011] Optionally, based on the index score of each metric indicator and the score corresponding to the metric dimension, the step of generating a software development health report according to a report configuration template comprises: calculating a dimension score corresponding to each metric dimension based on the index scores corresponding to all metric indicators under the metric dimension; constructing a report data table based on the index scores corresponding to all metric indicators and the dimension scores corresponding to all metric dimensions; and entering the report data table into the predefined report configuration template to generate the software development health report.

[0012] Optionally, after generating the software development health report according to the report configuration template based on the index score of each metric indicator and the score corresponding to the metric dimension, the method further comprises: generating a multi-dimensional radar chart associated with the target software, using the multi-dimensional radar chart to display the score distribution of the target software in each metric dimension; determining a comprehensive development score of the target software according to the calculation rule of the multi-dimensional radar chart, and outputting the multi-dimensional radar chart and the comprehensive development score.

[0013] According to another aspect of the embodiments of the present application, a multi-dimensional based software development evaluation device is also provided, comprising: an index data acquisition unit configured to acquire a predefined software development metric dimension and metric indicator, and collect software development data in a trusted environment; an index value calculation unit configured to calculate an index value associated with each metric indicator in the software development data according to a predefined calculation rule; an index scoring unit configured to score each metric indicator according to the index value of all metric indicators to obtain an index score; and a software development evaluation unit configured to generate a software development health report according to a report configuration template based on the index score of each metric indicator and the score corresponding to the metric dimension.

[0014] Optionally, the index data acquisition unit comprises: a metric dimension reading module configured to read a plurality of metric dimensions in a software development process from a configuration module, wherein the metric dimensions comprise at least one of the following: a requirement metric dimension, a development metric dimension, a test metric dimension, a release metric dimension, a resource metric dimension, and a cost metric dimension; and a metric indicator reading module configured to read a corresponding metric indicator under each metric dimension, wherein the corresponding metric dimensions under the requirement metric dimension comprise a requirement throughput and a requirement delivery period, the corresponding metric dimensions under the development metric dimension comprise a task throughput and a task value ratio, the corresponding metric dimensions under the test metric dimension comprise an automated test execution case ratio, the corresponding metric dimensions under the release metric dimension comprise a release frequency score and an online one-time success rate score, the corresponding metric dimensions under the resource metric dimension comprise a plurality of level ratio scores, and the corresponding metric dimensions under the resource metric dimension comprise a thousand-line code cost score.

[0015] Optionally, the index data collection unit further comprises: a system docking module, configured to dock a demand management system, a code management system, a test management system, a production management system and an online work order system in a trusted environment, and automatically pull data required for the metric indicators to obtain the software development data; and a data preprocessing module, configured to preprocess the software development data, wherein the preprocessing operation comprises at least one of the following: data format unification, removal of abnormal values, and removal of duplicate values.

[0016] Optionally, the index value calculation unit comprises: a first formula retrieval module, configured to retrieve a pre-defined calculation formula corresponding to each metric indicator according to a pre-defined calculation rule; and a first calculation module, configured to calculate data associated with each metric indicator in the pre-processed software development data by using the pre-defined calculation formula to obtain the index data.

[0017] Optionally, the index scoring unit comprises: a second formula retrieval module, configured to retrieve an index scoring formula corresponding to the metric indicator based on a pre-configured scoring rule; and a scoring module, configured to perform scoring processing on the index value of the metric indicator calculated by using the index scoring formula to obtain the index score.

[0018] Optionally, the software development evaluation unit comprises: a second calculation module, configured to calculate a dimension score corresponding to each metric dimension based on the index scores corresponding to all the metric indicators under the metric dimension; a data table construction module, configured to construct a report data table based on the index scores corresponding to all the metric indicators and the dimension scores corresponding to all the metric dimensions; and a report generation module, configured to enter the report data table into a pre-defined report configuration template to generate the software development health degree report.

[0019] Optionally, the multi-dimensional software development evaluation apparatus further comprises: a radar chart generation unit, configured to generate a multi-dimensional radar chart associated with the target software after generating the software development health degree report according to the report configuration template based on the index score of each metric indicator and the dimension score corresponding to the metric dimension, and display the score distribution of the target software in each metric dimension by using the multi-dimensional radar chart; and a score output unit, configured to determine a comprehensive development score of the target software according to a calculation rule of the multi-dimensional radar chart, and output the multi-dimensional radar chart and the comprehensive development score.

[0020] According to another aspect of the embodiments of the present application, a computer readable storage medium is also provided, which comprises a stored computer program, wherein the computer readable storage medium controls a device where the computer readable storage medium is located to perform the multi-dimensional software development evaluation method according to any one of the above aspects when the computer program runs.

[0021] According to another aspect of the embodiments of the present application, an electronic device is also provided, comprising one or more processors and a memory, the memory being configured to store one or more programs, wherein the one or more programs, when executed by the one or more processors, cause the one or more processors to implement the multi-dimension based software development evaluation method of any one of the above.

[0022] According to another aspect of the embodiments of the present application, a computer program product is also provided, comprising a computer program, which, when executed by a processor, implements the steps of the multi-dimension based software development evaluation method of any one of the above.

[0023] In the present disclosure, a pre-defined software development metric dimension and metric indicator can be acquired, and software development data can be collected in a trusted environment; according to a pre-defined calculation rule, a metric value of each metric indicator in the software development data is calculated; according to the metric values of all metric indicators, a numerical score of each metric indicator is obtained; and based on the metric score of each metric indicator and the score corresponding to the metric dimension, a software development health degree report is generated according to a report configuration template.

[0024] According to the above disclosure, a software development whole-process health degree detection method is provided, which can automatically complete data indicator collection and comprehensive evaluation, automatically generate a software development health degree report, complete metric of key stages in the whole life cycle of software, significantly reduce the dependence on manual operation in software development metric, improve the accuracy of metric results, and at the same time, the automatic process also reduces the metric cost and improves the processing speed of metric data, thereby solving the technical problems of dependence on manual operation in software development metric and low accuracy of metric results in related technologies. BRIEF DESCRIPTION OF DRAWINGS

[0025] The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this application, illustrate embodiments of the application and together with the description serve to explain the application. In the drawings:

[0026] Figure 1 is a flowchart of an optional multi-dimension based software development evaluation method according to an embodiment of the present application;

[0027] Figure 2 is a schematic diagram of a system for detecting health degree of a research and development process based on multi-dimensions according to an embodiment of the present application;

[0028] Figure 3 is a functional internal logic flowchart of a definition module according to an embodiment of the present application;

[0029] Figure 4is a functional internal logic flow chart of the data collection module according to an embodiment of the present application;

[0030] Figure 5 is a functional internal logic flow chart of the calculation module according to an embodiment of the present application;

[0031] Figure 6 is a functional internal logic flow chart of the evaluation module according to an embodiment of the present application;

[0032] Figure 7 is a functional internal logic flow chart of the report module according to an embodiment of the present application;

[0033] Figure 8 is a schematic diagram of an optional multi-dimensional based software development evaluation device according to an embodiment of the present application;

[0034] Figure 9 is a hardware structure block diagram of an electronic device (or mobile device) for performing a multi-dimensional based software development evaluation method according to an embodiment of the present application. DETAILED DESCRIPTION

[0035] In order to make the personnel in the art better understand the present application scheme, the technical solutions in the embodiments of the present application will be described clearly and completely below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor should belong to the scope of protection of the present application.

[0036] It should be noted that the terms "first", "second", and the like in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and do not necessarily have to describe a specific order or sequence. It should be understood that the data thus used can be interchanged under appropriate circumstances, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "include" and "have" and any variations thereof are intended to cover non-exclusive inclusion, for example, a process, method, system, product or device including a series of steps or units does not have to be limited to those steps or units clearly listed, but can include other steps or units not clearly listed or inherent to these processes, methods, products or devices.

[0037] In order to facilitate those skilled in the art to understand the present application, the following explains some terms or names involved in each embodiment of the present application:

[0038] A Requirement Management System (RMS) is used to manage the requirements of software projects. It provides functions such as requirement collection, analysis, verification, and tracking to ensure that software development meets business objectives and user needs. This system helps ensure the integrity, consistency, and traceability of requirements, reducing development delays and cost waste caused by unclear or changing requirements.

[0039] A Test Management System (TMS) is used to plan, execute, and manage software testing, including test case design, test plan development, defect tracking, and report generation. Through a TMS, testers can effectively coordinate test resources, control test progress, and evaluate software quality, ensuring the efficiency of testing activities and the reliability of results.

[0040] A code management system (CMS) is responsible for code version control and code repository management, helping software development teams organize code, manage changes, track historical versions, and coordinate multi-person collaboration. It supports code submission, review, merging, and deployment processes through automated tools, reducing code conflicts and accelerating the software development cycle.

[0041] A Production Management System (PMS) is used to monitor and manage the production activities of software projects, including task allocation, time management, resource planning, and performance evaluation. Through integration with systems such as RMS, CMS, and TMS, it collects various production data to help project managers understand project progress, optimize resource allocation, and improve team productivity.

[0042] The Deployment Work Order System (DWOS) is used for software deployment and release management. Through automated and standardized deployment processes, it improves the efficiency and success rate of software launches. It records detailed information for each deployment ticket, including deployment time, results, and personnel involved, which helps to quickly locate problems and improve the ability to continuously deliver software.

[0043] It should be noted that the multi-dimensional software development evaluation method and apparatus disclosed herein can be used in the field of blockchain technology for health assessment during software development based on multi-dimensional detection, and can also be used in any field other than blockchain technology for health assessment during software development based on multi-dimensional detection. This disclosure does not limit the application areas of the multi-dimensional software development evaluation method and apparatus.

[0044] It should be noted that the information (including but not limited to user equipment information, user personal information, etc.) and data (including but not limited to data for analysis, stored data, displayed data, etc.) collected by the present disclosure are information and data authorized by the user or authorized by all parties, and the collection, storage, use, processing, transmission, provision, disclosure and application of related data comply with relevant laws, regulations and standards in the relevant region, necessary security measures are taken, do not violate public order and good customs, and provide corresponding operation portal for user selection authorization or refusal. For example, an interface is provided between the system and the related user or institution, and before obtaining the relevant information, the interface needs to send a request to the aforementioned user or institution, and after receiving the consent information feedback from the aforementioned user or institution, the relevant information is obtained.

[0045] It should be noted that in the present disclosure, the customer information is collected, the customer information is analyzed, and the corresponding operation portal is provided for the user to select to agree or refuse the automatic decision result; if the user chooses to refuse, the expert decision process is entered.

[0046] The following embodiments of the present application can be applied to various systems / applications / devices based on multi-dimensional software development evaluation. The present application can be applied to the scene of continuous monitoring and evaluation of software development process health in large-scale software projects or organizations, such as code development and version control scene, which can evaluate the productivity and code quality of the development team by monitoring task throughput, task value ratio and other indicators during the development process, and support the development team to improve the development efficiency; or applied to software testing automation and quality assurance scene, in the testing stage, evaluate the execution of automated testing, improve the coverage and efficiency of software testing, and ensure the quality and stability of the software before release.

[0047] The present application provides a comprehensive measurement framework covering the whole life cycle of software development, which can more comprehensively and objectively evaluate the health of the software development process, and through automatic data collection and processing, reduces manual intervention, and improves the efficiency and accuracy of data processing.

[0048] The present application will be described in detail below in conjunction with various embodiments.

[0049] Embodiment one

[0050] According to the embodiments of the present application, an embodiment of a multi-dimensional software development evaluation method is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although the logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from here.

[0051] Figure 1is a flow chart of an optional multi-dimension based software development evaluation method according to an embodiment of the present application, as shown in Figure 1 The method comprises the following steps:

[0052] In step S101, pre-defined software development metric dimensions and metric indicators are acquired, and software development data is collected in a trusted environment.

[0053] Optionally, the step of acquiring pre-defined software development metric dimensions and metric indicators comprises: reading a plurality of metric dimensions in a software development process from a configuration module, wherein the metric dimensions comprise at least one of the following: requirement metric dimension, development metric dimension, test metric dimension, release metric dimension, resource metric dimension, and cost metric dimension; and reading corresponding metric indicators under each metric dimension, wherein the corresponding metric indicators under the requirement metric dimension comprise requirement throughput and requirement delivery cycle, the corresponding metric indicators under the development metric dimension comprise task throughput and task value ratio, the corresponding metric indicators under the test metric dimension comprise automated test execution case ratio, the corresponding metric indicators under the release metric dimension comprise release frequency score and online success rate score, the corresponding metric indicators under the resource metric dimension comprise a plurality of level ratio scores, and the corresponding metric indicators under the resource metric dimension comprise thousand-line code cost score.

[0054] Among them, the configuration module is responsible for defining and managing the metric dimensions in the software development process. In the embodiment, the software development metric dimensions include but are not limited to the following six aspects: 1. Requirement metric dimension: used to evaluate the efficiency and quality of the software team in handling requirements, which can include requirement throughput and requirement delivery cycle, i.e. the number of requirement work orders accepted by the software per month and the average time period for completing the requirement work orders. Through these indicators, the requirement analysis and processing capacity can be measured. 2. Development metric dimension: monitors the efficiency and task processing capacity of the development stage. The indicators under the development metric dimension can include task throughput and task value ratio. The former calculates the number of tasks processed by each person per week in the software development stage, and the latter calculates the ratio of task value-added time to total time, reflecting the task benefit and resource consumption. 3. Test metric dimension: focuses on the automation level and test coverage of the software testing stage. The metric indicators under this dimension can include the proportion of automated test execution use cases, i.e. the proportion of automated test execution use cases to the total number of test cases, reflecting the automation level of the test process. 4. Release metric dimension: tracks the frequency and success rate of software system updates, including release frequency score and online success rate score. The former measures the continuous delivery capability of the software, and the latter evaluates the stability and deployment quality of the software online. 5. Resource metric dimension: evaluates the structure and work hour utilization efficiency of team members. This dimension can include multiple level proportion scores, such as junior proportion score, intermediate proportion score, senior proportion score and senior proportion score, to ensure reasonable resource allocation and effective utilization. 6. Cost metric dimension: monitors the overall input and output of software development. The metric indicator is the cost score of thousands of lines of code, which calculates the ratio of software development cost to code volume to evaluate the economic benefit of the software.

[0055] It should be noted that the embodiment is to collect software development data in a trusted environment, and the trusted environment ensures the accuracy and security of the data, which is a key prerequisite for successful data collection. Among them, the data collection can include the following steps: requirement data collection: reading requirement work order data from the requirement management system, including work order number, creation time, completion time, work order status, etc., which is used to calculate the requirement throughput and requirement delivery period. Code data collection: through interaction with the code management system, obtain code submission records, code modification line numbers, code review conditions, etc., which are used to calculate the task throughput and task value ratio. Test data collection: use the test management system interface to collect test case execution data, automatic test coverage, etc. Information is used to calculate the proportion of automatic test execution cases. Release data collection: interface with the online work order system to record detailed information of each online work order, including online time, online result, work order status, etc., which is used to calculate the release frequency score and the success rate score of one online. Resource and work time data collection: obtain team member composition, role allocation, work time input, etc. Information through the production management system is used to calculate the proportion of personnel input at different levels and the work time utilization efficiency. Cost data collection: combine the data of the code management system and the production management system to calculate the software development cost, including manpower cost, hardware and software cost, etc. It is used to calculate the cost score of thousands of lines of code.

[0056] Optionally, the step of collecting software development data in a trusted environment includes: interfacing the requirement management system, the code management system, the test management system, the production management system and the online work order system in the trusted environment, automatically pulling the data required for the metric indicators, obtaining the software development data; preprocessing the software development data, wherein the preprocessing operation includes at least one of the following: data format unification, removing outliers, removing duplicate values.

[0057] The system interfaces the requirement management system, the code management system, the test management system, the production management system and the online work order system in the trusted environment, and these systems are responsible for data management in different stages of software projects, including requirement analysis, code writing, test execution, production activities and deployment work order. Through interface communication with these systems, the embodiment can automatically pull data closely related to the metric indicators, such as requirement work order details, code submission records, test results, work time statistics and deployment information, etc., so as to obtain a comprehensive and detailed software development data set.

[0058] Next, to improve data quality and ensure the accuracy of subsequent analysis, the embodiment preprocesses the acquired software development data. That is, the data collection module cleans, transforms, and integrates the raw data to ensure its accuracy and consistency, which includes operations such as removing duplicates, filling in missing values, formatting dates and times, and standardizing measurement units. Preprocessing operations include but are not limited to: 1. Data format unification: Ensure that all data pulled from different systems is in the same format and encoding, laying the foundation for data merging and analysis. For example, all date fields will be converted to a uniform timestamp format, and all text fields will be case-normalized to eliminate errors caused by inconsistent data formats. 2. Remove outliers: There may be values in the data set that are outside the normal range, which may be caused by data entry errors, measurement errors, or other unexpected events. Through statistical analysis or pre-set rules, the embodiment can identify and remove these outliers to avoid misleading effects on the measurement results. 3. Remove duplicate values: During data collection, the same information may be inadvertently collected multiple times, especially when data is exchanged between systems. The embodiment can remove duplicate records by comparing unique identifiers (such as requirement IDs, code commit IDs, etc.) to ensure that each element in the data set is independent and valuable, further improving the purity of the data set.

[0059] Step S102, according to the pre-defined calculation rule, calculate the index value associated with each metric in the software development data.

[0060] Optionally, according to the pre-defined calculation rule, the step of calculating the index value associated with each metric in the software development data includes: according to the pre-defined calculation rule, calling the pre-designed calculation formula corresponding to each metric; using the pre-designed calculation formula to calculate the data associated with each metric in the pre-processed software development data to obtain the index data.

[0061] The embodiment first defines a series of measurement dimensions, including but not limited to requirement analysis, development efficiency, test level, release capability, resource allocation, and cost effectiveness. Under each measurement dimension, specific measurement indicators are set, such as requirement throughput, task value ratio, automated test execution case ratio, etc.

[0062] Next, the software physical examination system of the embodiment can retrieve the pre-designed calculation formula corresponding to each metric according to the pre-defined calculation rule. The pre-designed calculation formula is pre-set in the definition module to ensure that the calculation method of each metric is consistent. For example, for the demand throughput, the pre-designed calculation formula is: demand throughput = (Σ software accepted demand work orders + Σ software developed demand work orders) / the number of months in the statistical period. For the automation test execution case ratio, the pre-designed calculation formula is: automation test execution case ratio = Σ the number of execution automation test cases in each work order / Σ the number of execution test cases in each work order * 100%.

[0063] After obtaining the pre-designed calculation formula, the embodiment will use these formulas to calculate the data associated with each metric in the pre-processed software development data to obtain the metric data. The original software development data can be collected from multiple external systems or internal services such as demand management systems, code management systems, test management systems, online work order systems, and production management systems.

[0064] The pre-processed data is then passed to the calculation module, where the pre-designed calculation formula is applied to the data to perform the specific calculation process and obtain the numerical result of each metric. For example, when calculating the demand throughput, the system will add up the number of demand work orders accepted and completed by the software in the specified statistical period, and then divide by the number of months in the period to obtain the specific value of the demand throughput.

[0065] Similarly, for other metrics such as the task value ratio automation test execution case ratio, the system will also automatically calculate the corresponding metric value according to the pre-designed calculation formula. During the calculation process, the system uses standardized interfaces and data mapping technology to ensure the compatibility of data from different sources and the accuracy of the calculation.

[0066] Step S103, according to the metric value of all metrics, numerical scoring is performed on each metric to obtain the metric score.

[0067] Optionally, the step of scoring each metric according to the metric value of all metrics to obtain the metric score includes: based on the pre-configured scoring rule, retrieving the metric scoring formula corresponding to the metric; using the metric scoring formula to score the calculated metric value of the metric to obtain the metric score.

[0068] The embodiment supports user-defined scoring rules, which are stored in the definition module. The scoring rules involve scoring criteria, thresholds, and weights of the metric indicators, and are used to guide how to convert the indicator values of the metric indicators into indicator scores. For example, for the demand throughput, the scoring rules can stipulate that 5 points are given when the demand throughput is higher than the median value of the software in the same level by 10%, 4 points are given when the demand throughput is lower than the median value by 10% and higher than the median value by 5%, and so on.

[0069] The evaluation module retrieves the corresponding scoring formulas from the definition module according to the types of the metric indicators. The scoring formulas are customized according to the actual situation and goals of software development, to ensure the accuracy of the scoring. For example, for the task value ratio, the scoring formula that can be used is the ratio of the value-added time to the total time multiplied by 100%, and then the score is obtained according to the comparison of the ratio with the preset threshold.

[0070] After the calculation module processes the raw data and obtains the indicator values of each metric indicator, the evaluation module applies the indicator scoring formula to score the values. The scoring process is a process of converting the metric indicator values into specific score values, which comprehensively considers the quantitative performance of the indicators and the pre-defined scoring logic. For example, for the proportion of automated test execution cases, the scoring formula that can be used in the embodiment is: if the value of the proportion of automated test execution cases reaches or exceeds 95%, 5 points are given; if it is between 80% and 95%, 4 points are given; and so on.

[0071] In addition, the embodiment also takes into account the particularity and diversity of software development. For different software categories and levels, the scoring rules can be different. For example, for the release frequency and the success rate of online once, for a software with high transaction volume and high availability requirements, the scoring rules can be set more strictly to reflect its demand for stability and frequent iteration.

[0072] In step S104, based on the indicator scores of each metric indicator and the scores corresponding to the metric dimensions, a software development health report is generated according to the report configuration template.

[0073] Optionally, the step of generating a software development health report based on the indicator scores of each metric indicator and the scores corresponding to the metric dimensions according to the report configuration template includes: calculating the dimension score corresponding to each metric dimension based on the indicator scores corresponding to all metric indicators under the metric dimension; constructing a report data table based on the indicator scores corresponding to all metric indicators and the dimension scores corresponding to all metric dimensions; and entering the report data table into the pre-defined report configuration template to generate the software development health report.

[0074] The embodiment will first calculate the dimension score corresponding to the metric dimension based on the indicator score corresponding to all metric indicators under each metric dimension. For the demand dimension score, the embodiment will average the scores of the demand throughput and the demand delivery period to obtain the final score of the demand dimension. For the development dimension score, the scores of the task throughput and the task value ratio are averaged to obtain the score of the development dimension. For the test dimension score, under the test dimension, the embodiment directly takes the score of the automated test execution case ratio as the score of the test dimension. For example, if the score of the automated test execution case ratio is 5 points, the score of the test dimension is also 5 points.

[0075] In addition, for the release dimension score, the release dimension score is the product of the release frequency and the online success rate score. If the release frequency score is 3 points and the online success rate score is 5 points, the score of the release dimension is 15 points, but it needs to be converted into a five-point system score, for example, 3 points (3*5 / 5). For the resource dimension score, under the resource dimension, the embodiment will calculate the average value of the proportion scores of the primary, intermediate, senior, and experienced personnel to obtain the resource dimension score. For the cost dimension score, the score of the cost dimension is based on the score of the cost per thousand lines of code, reflecting the economic efficiency of software development.

[0076] Finally, the report data table constructed is entered into the pre-defined report configuration template to generate the software development health report. The report configuration template supports customization and can be in the form of page view, report download, or system push. In addition, the embodiment can also provide a mail subscription function to allow users to receive regular software health reports.

[0077] The report module of the embodiment can automatically generate a report for each software, including a five-point system score, a percentage system score, and a multi-dimensional radar chart, which can clearly and intuitively show the performance of the software in each dimension. For the dimensions that do not participate in scoring, the system will ignore the corresponding score points when generating the report and will not interfere with the radar chart.

[0078] Optionally, after generating the software development health report based on the indicator score of each metric indicator and the score corresponding to the metric dimension according to the report configuration template, the method further includes: generating a multi-dimensional radar chart associated with the target software, using the multi-dimensional radar chart to show the score distribution of the target software in each metric dimension; determining a comprehensive development score of the target software according to the calculation rule of the multi-dimensional radar chart, and outputting the multi-dimensional radar chart and the comprehensive development score.

[0079] The embodiment identifies six metric dimensions related to the target software, namely the demand metric dimension, the development metric dimension, the test metric dimension, the release metric dimension, the resource metric dimension, and the cost metric dimension, and then reads the score of each metric dimension from the report.

[0080] With the obtained metric dimension scores, a multi-dimensional radar chart is generated, where the multi-dimensional radar chart is a chart used to display multivariate data, which can intuitively compare and display the performance of the target software in multiple dimensions. In this embodiment, the six axes of the radar chart correspond to the six metric dimensions respectively, and the numerical value on the axis represents the score of the dimension, with the highest score being 5 and the lowest score being 0. The calculation rule of the multi-dimensional radar chart displays each metric dimension score in the form of a radar chart, where each point represents a metric dimension score, and the farther the point is from the center, the higher the score. In order to calculate the comprehensive development score of the target software, the calculation rule of the radar chart defines the area calculation method of the score area, that is, the ratio of the polygon area formed by the six metric dimension score points to the total area of the radar polygon, and then the ratio is converted to a percentage score. Figure Six

[0081] In determining the comprehensive development score of the target software, first, the polygon area formed by the six metric dimension score points is calculated, that is, the size of the score area of the target software on the multi-dimensional radar chart, and then the area is compared with the total area of the radar polygon to determine the area ratio. Based on the area ratio, the percentage comprehensive development score of the target software is calculated, specifically, the area ratio multiplied by 100 is the percentage score, which reflects the overall performance level of the target software in all metric dimensions. After calculating the percentage comprehensive score, this embodiment will apply a pre-defined scoring rule, such as rounding to the nearest integer, to ensure the consistency and readability of the score. Figure Six

[0082] Finally, the multi-dimensional radar chart and the comprehensive development score are output to the report for reference by management and software team. The report can be output in various formats such as PDF, HTML or Word document, which is convenient for different users to read and analyze.

[0083] ​​By the above steps, the pre-defined software development metric dimensions and metric indicators can be obtained, and the software development data can be collected in a trusted environment; according to the pre-defined calculation rules, the indicator values associated with each metric indicator in the software development data are calculated; according to the indicator values of all the metric indicators, the numerical score of each metric indicator is obtained; and based on the indicator score of each metric indicator and the score corresponding to the metric dimension, the software development health degree report is generated according to the report configuration template. In this embodiment, a software development whole-process health degree detection method is provided, which can automatically complete data indicator collection and comprehensive evaluation, automatically generate a software development health degree report, complete the measurement at key stages of the software life cycle, can significantly reduce the dependence on manual operation in software development measurement, improve the accuracy of the measurement results, at the same time, the automatic process also reduces the measurement cost and improves the processing speed of the measurement data, thereby solving the technical problems of the related art that the software development measurement method depends on manual operation and the measurement result accuracy is low.

[0084] The following will be described in detail in combination with another optional specific embodiment.

[0085] Figure 2 is a schematic diagram of a system for measuring the health degree of a research and development process according to an embodiment of the application, as shown in Figure 2 , the system comprises a definition module, a data collection module, a calculation module, an evaluation module and a report module, which will be described in detail below. Figure 2

[0086] 2.1, the definition module.

[0087] The definition module builds the main measurement framework of the research and development process health degree detection, and this embodiment defines the definition and related rules of six measurement dimensions and 12 measurement indicators belonging to the six dimensions. This patent supports user-defined creation of measurement dimensions and measurement indicators.

[0088] Figure 3 is a functional internal logic flowchart of the definition module according to an embodiment of the application, as shown in Figure 3 , the definition module is defined in two layers, first the measurement dimensions are defined, then the indicators under the measurement dimensions are defined, and the indicator description, data source, calculation rule, scoring rule, threshold rule, etc. are set for each indicator to provide support for data processing and evaluation of subsequent modules.

[0089] 2.2, the data collection module.

[0090] The main function of the data collection module is to interface with external systems, collect external raw data and perform data cleaning on the raw data, so that the raw data is transformed into a data source that meets the current system. ​

[0091] Figure 4 is a functional internal logic flow chart of the data collection module according to an embodiment of the present application, as shown in Figure 4 The data collection module is a process of standardizing externally collected data, and the module collects data from external data sources, pre-processes the data through data parsing rules, performs data verification, including cleaning, conversion and integration, to improve data quality. The data collection module maps data from different sources to a unified model through a standardized interface and stores it in a database for subsequent processing and analysis.

[0092] The data collection module interfaces with multiple different systems, including a requirement management system (to obtain requirement data), a software management system (to obtain software information), a test management system (to obtain test output data), a code management system (to obtain code output data), a production management system (to obtain work hour data, resource data and task data), and an online work order (to obtain software online work order data).

[0093] 2.3, the calculation module.

[0094] The calculation module automatically calculates the data obtained by the data collection module according to the calculation rules configured in the definition module, to obtain relevant metric dimension indicator values.

[0095] Figure 5 is a functional internal logic flow chart of the calculation module according to an embodiment of the present application, as shown in Figure 5 The implementation flow of the calculation module is to execute the calculation task according to the data processed by the data collection module and in combination with various rules of the definition module. The calculation module verifies the calculation results and processes abnormal data in the calculation process to ensure accuracy and reliability. Finally, the verified data is stored in a database or a file system for subsequent access and use, as shown in Figure 5 The processing mode process includes collecting data, defining rules, pre-processing data, executing a calculation process, a verification process and storing data.

[0096] 2.4, the evaluation module.

[0097] The evaluation module automatically calculates the score of each indicator according to the indicator values obtained by the calculation module and the relevant scoring rules configured in the definition module.

[0098] Figure 6 is a functional internal logic flow chart of the evaluation module according to an embodiment of the present application, as shown in Figure 6As shown, the implementation process of the evaluation module first obtains various types of index data from the calculation module, then analyzes and calculates according to the scoring rules, and obtains the digital evaluation results of each metric index and metric dimension of each software. For each software, a comprehensive evaluation result is obtained, including a five-point system, an average score taken from each metric dimension; a multi-dimensional radar chart, which shows the distribution of each dimension, and intuitively shows the excellent, good and poor levels of each dimension and the weak links that need to be provided from the radar chart; a software comprehensive score, which adopts a percentage system, and the score is calculated by the area ratio of the software radar chart (the polygon area formed by connecting the six dimension score points / total area of the radar chart * 100). For the dimensions that do not participate in scoring, the score point does not participate in the connection. Finally, the evaluation results are stored in the database for subsequent query and use. Figure Six

[0099] 2.5, report module.

[0100] The report module automatically generates reports for each software (five-point system score, percentage system score, radar chart distribution) and the evaluation report of the department where the software is located according to the score, and provides optimization and improvement decision-making to drive the software team to improve itself.

[0101] Figure 7 The functional internal logic flowchart of the report module according to the embodiment of the application is shown in Figure 7 As shown, the report module can provide report download function, page view function, system push function and mail subscription function. The report module can display the results obtained by the above modules through different dimensions, such as software reports, department reports, and management reports. It can be displayed and consulted through pages or emails, etc., to promote the optimization and improvement of the software team.

[0102] According to the technical scheme provided by the embodiment, a set of R&D process health detection method and device / system can be formed, which mainly implements from three aspects of definition of metric dimension and index, calculation and evaluation of metric index, and generation of metric report. It should be noted that the system is referred to as a software physical examination system in the embodiment.

[0103] First, the definition of metric dimension and index.

[0104] The software physical examination system can define the metric dimension and the metric index. Six metric dimensions are defined in the system, and metric indexes are defined under each metric dimension.

[0105] First, the demand metric dimension.

[0106] The score of the demand metric dimension is selected by rounding off the average score of the demand throughput and the demand delivery cycle to the nearest integer.

[0107] Metric index 1: demand throughput (pieces / month).​

[0108] Indicator Description: The number of development type requirements accepted or developed by the software each month (duplicates are removed for requirement tickets).

[0109] Data Source: Requirement Ticket System.

[0110] Threshold Rule: The data must be a positive integer.

[0111] Calculation Rule: Requirement Throughput = (∑Requirement Tickets accepted by the software + ∑Requirement Tickets developed by the software) / the number of months in the statistical period.

[0112] Scoring Rule:

[0113] 5 points: Higher than 10% (including 10%) of the median value of the same level software;

[0114] 4 points: Less than 10% of the median value of the same level software and higher than 5% (including 5%) of the median value of the same level software;

[0115] 3 points: Between the positive and negative 5% of the median value of the same level software;

[0116] 2 points: Lower than 5%-10% (including 10%) of the median value of the same level software;

[0117] 1 point: Lower than 10% (including 10%) of the median value of the same level software;

[0118] 0 points: - or 0;

[0119] (Software with a requirement throughput of - or 0 does not participate in the ranking of the same layer software).

[0120] Metric Indicator 2: Requirement Delivery Period (days).

[0121] Indicator Description: The number of development type requirements accepted or developed by the software each month (duplicates are removed for requirement tickets).

[0122] Data Source: Requirement Ticket System.

[0123] Threshold Rule: The data must be a positive integer.

[0124] Calculation Rule: Requirement Delivery Period = ∑Requirement Ticket Delivery Period / ∑Total Number of Requirement Tickets.

[0125] Evaluation Rule:

[0126] 5 points: Lower than 10% (including 10%) of the median value of the same level software;

[0127] 4 points: Lower than 5%-10% (including 10%) of the median value of the same level software;

[0128] 3 points: between the positive and negative 5% of the median value in the same level software;

[0129] 2 points: lower than the median value of the same level software 10% and higher than the median value of the same level software 5% (including 5%);

[0130] 1 point: higher than the median value of the same level software 10% (including 10%);

[0131] 0 points: - or 0;

[0132] (The software with task throughput of - or 0 does not participate in the same layer software ranking).

[0133] Second, develop the metric dimension.

[0134] The score of the development metric dimension is the average score of the task throughput and the task value ratio, rounded to an integer.

[0135] Metric 1: Task throughput (pieces / person / week).

[0136] Explanation of the index: calculate the task throughput per person per week in the software development stage.

[0137] Data source: production management system.

[0138] Threshold rule: require data to be positive.

[0139] Calculation rule: ∑[(∑ tasks in progress per week + ∑ completed tasks per week) / number of development task hanging resources per week] / number of weeks in the statistical period.

[0140] Scoring rules:

[0141] 5 points: higher than the median value of the same level software 10% (including 10%);

[0142] 4 points: less than the median value of the same level software 10% and higher than the median value of the same level software 5% (including 5%);

[0143] 3 points: between the positive and negative 5% of the median value in the same level software;

[0144] 2 points: lower than the median value of the same level software 5%-10% (including 10%);

[0145] 1 point: lower than the median value of the same level software 10% (including 10%);

[0146] 0 points: - or 0;

[0147] (The software with task throughput of - or 0 does not participate in the same layer software ranking).

[0148] Metric 2: Task value ratio.

[0149] Indicator Description: The value of the software development task per week in the statistical period is compared with the average value (weeks without tasks are not included in the calculation).

[0150] Data Source: Production Management System.

[0151] Threshold Rule: Requires data to be positive.

[0152] Calculation Rule: The time of the issue task associated with the L4 layer development class task in the week is counted as the total time, the time on the issue task is counted as the value-added time, and the time without reporting on the issue task is counted as the consumption time. Value ratio = value-added time / total time * 100%.

[0153] Scoring Rule:

[0154] 5 points: greater than or equal to 60%;

[0155] 4 points: greater than or equal to 40% and less than 60%;

[0156] 3 points: greater than or equal to 30% and less than 40%;

[0157] 2 points: greater than or equal to 10% and less than 30%;

[0158] 1 point: greater than 0 and less than 10%;

[0159] 0 points: 0;

[0160] Third, test measurement dimension.

[0161] The score of the test measurement dimension is the score of the proportion of automated test execution cases.

[0162] Measurement Indicator 1: Proportion of Automated Test Execution Cases

[0163] Indicator Description: Calculate the proportion of automated test execution cases data.

[0164] Data Source: Test Management System.

[0165] Threshold Rule: Requires data to be positive.

[0166] Calculation Rule: ∑ Number of automated test cases executed in each ticket / ∑ Number of test cases executed in each ticket * 100%.

[0167] Scoring Rule: Software automated test coverage score = Σ (module number of internal test passed tickets in the month × module health) ÷ software number of internal test passed tickets in the month; Software score is rounded to integer.

[0168] Fourth, release measurement dimension.

[0169] The score of the publishing dimension is the publishing frequency score * the success rate of publishing once.

[0170] Metric indicator 1: publishing frequency.

[0171] Indicator description: the average number of online times per month and the number of online times per month in the statistical period.

[0172] Data source: online work order system.

[0173] Threshold rule: requires data to be a positive integer.

[0174] Calculation rule: each successful online is counted as one online.

[0175] Scoring rules:

[0176] 1 point: 1 or more times per month;

[0177] 0.5 points: an average of 1 time per month;

[0178] 0 points: an average of less than 1 time per month.

[0179] Metric indicator 2: success rate of publishing once.

[0180] Indicator description: calculate the success rate of publishing in the statistical period.

[0181] Data source: online work order system.

[0182] Threshold rule: requires data to be between 0 and 1.

[0183] Calculation rule: the number of successful online of each software in the statistical period / the total number of online of each software * 100%.

[0184] Scoring rules: 5 points: 100%;

[0185] 4 points: greater than or equal to 95% and less than 100%;

[0186] 3 points: greater than or equal to 90% and less than 95%;

[0187] 2 points: greater than or equal to 80% and less than 90%;

[0188] 1 point: greater than 0 and less than 80%;

[0189] 0 points: 0 or -.

[0190] Fifth, resource dimension.

[0191] The score of the resource dimension is the average of the scores of junior, intermediate, senior and experienced proportions, rounded to an integer.

[0192] Metric indicator 1: resource proportion, including junior, intermediate, senior and experienced.

[0193] Indicator Explanation: Junior level 20% is considered the optimal proportion, intermediate level 40% is considered the optimal proportion, advanced level 30% is considered the optimal proportion, senior level 10% is considered the optimal proportion.

[0194] Data Source: Production Management System.

[0195] Threshold Rule: Requires data to be between 0-1.

[0196] Calculation Formula: The ratio of personnel at each level to the total number of personnel.

[0197] Scoring Rules:

[0198] 5 points: The deviation of the proportion of this level compared to the optimal proportion of this level is less than or equal to 5%;

[0199] 4 points: The deviation of the proportion of this level compared to the optimal proportion of this level is greater than 5% and less than or equal to 10%;

[0200] 3 points: The deviation of the proportion of this level compared to the optimal proportion of this level is greater than 10% and less than or equal to 20%;

[0201] 2 points: The deviation of the proportion of this level compared to the optimal proportion of this level is greater than 20% and less than or equal to 30%;

[0202] 1 point: The deviation of the proportion of this level compared to the optimal proportion of this level is greater than 30%;

[0203] 0 points: -(Software has no manual labor input).

[0204] Sixth, cost measurement dimension.

[0205] Cost measurement dimension score is thousand line code cost score.

[0206] Measurement Indicator 1: Thousand Line Code Cost Score.

[0207] Indicator Explanation: Score based on cost per thousand lines of code.

[0208] Data Source: Code Management System and Production Management System.

[0209] Threshold Rule: Requires data to be between 0-100.

[0210] Calculation Rule: Sort the thousand line code cost by software category, layer, and development language, assign scores (0-100 points), and evaluate the final score according to the 5-point system.

[0211] Scoring Rules:

[0212] 5 points: 100-90;

[0213] 4 points: 89-75;

[0214] 3 points: 74-60;

[0215] 2 points: 59-45;

[0216] 1 point: 44 and below;

[0217] 0 points: -(software code modification lines or software input manual labor hours is 0).

[0218] Secondly, the calculation and evaluation of the metric need to be done.

[0219] First, configure data collection parameters.

[0220] Determine the data requirements of each sub-module, including data type, format, and collection frequency, design data collection architecture, plan data flow and interface. For each sub-module, implement interface connection with external systems or internal services. Configure necessary authentication information to ensure the security of data transmission.

[0221] Second, perform data collection and data cleaning.

[0222] Configure data collection tasks according to requirements, including scheduled collection and real-time collection. Implement data collection logic to obtain raw data from each sub-module.

[0223] Define data cleaning rules, including data format conversion, deduplication, and filtering. Implement data cleaning processes to ensure data accuracy and consistency.

[0224] Third, calculate the rules.

[0225] According to business requirements and calculation targets, define data parsing and processing rules. Rules include data format, calculation logic, and threshold key elements.

[0226] Fourth, execute the calculation.

[0227] According to the pre-defined rules, calculate the pre-processed data. The calculation process is automated and does not require human intervention, improving calculation efficiency and accuracy.

[0228] Fifth, configure the scoring rules.

[0229] Pre-configure scoring rules in the definition module, including scoring standards, weights, and calculation formulas. Ensure that the scoring rules can be flexibly adjusted to adapt to different evaluation requirements.

[0230] Sixth, apply the scoring rules to calculate the score.

[0231] According to the configured scoring rules, the numerical value of each indicator is automatically scored and calculated, and the calculation process is based on the weight and correlation between indicators. According to each indicator, the corresponding scoring formula is applied to calculate the final scoring result.

[0232] Example 1: Data collection and calculation of A and B software requirement throughput indicators in the requirement dimension and scoring process.

[0233] 1) According to the "data source" configured in the definition module, the system interacts with the connected requirement work order system to obtain data, calls the configured authentication information to obtain the requirement work order data through the interface, and processes the received data to perform operations such as de-duplication, data conversion, threshold range verification, etc. The processed data is saved in a unified format to the database.

[0234] 2) Next, according to the defined calculation rule, the formula (∑ software accepted requirement work orders + ∑ software development completed requirement work orders) / number of months in the statistical period is used to calculate the data in the database to obtain the requirement throughput of each software.

[0235] For example, A software and B software belong to the same level of classified software and have accepted related requirement orders. The final requirement throughput and requirement delivery cycle indicators are calculated as follows:

[0236] A software has accepted a total of 184 requirement orders from January to September and has completed 179. According to the formula, the requirement throughput is 40.3 per month, and the delivery cycle is 1.05 days on average.

[0237] B software has accepted a total of 84 requirement orders from January to September and has completed 80. According to the formula, the current requirement throughput is 18.2 per month, and the delivery cycle is 1 day.

[0238] 3) Finally, the system calculates the 5-point results of each software according to the defined scoring rules and saves the results to the database for future use.

[0239] The median value of the same level software where A software is located is 19.1 per month, and the requirement throughput of A software exceeds the median value by 111%. According to the scoring standard, more than 10% above the median value, A software's requirement throughput dimension gets 5 points. The average delivery cycle of A software is 1.05 days, and the median value of the same level is 1.1 days, which is 4% less than the median value, so A software's requirement delivery cycle dimension gets 3 points, and the final score of the requirement dimension is 4 points.

[0240] The requirement throughput dimension of B software is less than the median value by 4%, according to the scoring standard, which is between the median value of the same level software and the median value of the same level software, so the requirement throughput dimension of B software gets 3 points, and the average delivery cycle is less than the median value of the same level by 9% to get 4 points, and the final score of the requirement dimension is 3.5 points.

[0241] Example 2: Collection and calculation of cost score data of thousands of lines of code under the statistical cost dimension and the process of obtaining the score.

[0242] 1) The system interacts with the connected code management system to obtain data according to the "data source" configured in the definition module, calls the configured authentication information to obtain the requirement work order data through the interface, pre-processes and cleanses the data, and saves the processed data in a unified format to the database.

[0243] 2) Next, according to the defined calculation rules, the thousands of lines of code cost are sorted and calculated according to the software class, layer and development language. The thousands of lines of code percentage score of each software is calculated from the data in the database.

[0244] 3) Finally, the system calculates the 5-point results of each software according to the defined scoring rules using the percentage results, and saves the results to the database for future use.

[0245] Example 3: Radar chart comprehensive scoring process of A software.

[0246] 1) According to the scores of each dimension of A software calculated by the system, the requirement dimension gets 3 points, the development dimension gets 4 points, the test dimension gets 5 points, the release dimension gets 5 points, the resource dimension gets 3 points, and the cost dimension gets 4 points.

[0247] 2) Calculate the software comprehensive score according to the results of each dimension, which is equal to the area of the polygon formed by connecting the score points of the six dimensions of the software / total area of the radar polygon * 100 (rounded to the nearest integer) Figure Six For dimensions that do not participate in scoring, the scoring points do not participate in the connection. According to the formula, the comprehensive score is 69.

[0248] Finally, the generation of the measurement report and the improvement need to be carried out.

[0249] First, data preparation.

[0250] Obtain scoring data from the evaluation module, including five-point scores and percentage scores, to provide a basis for report generation.

[0251] Second, report configuration.

[0252] Configure the report template according to the requirements, including page views, report downloads, etc. It should be noted that the template in this embodiment supports customization to adapt to different reporting needs.

[0253] Third, report generation and display.

[0254] According to the configured template, the report of each software is automatically generated, and the report is combined and generated according to different dimensions, such as software dimension report, department dimension report, management layer report and the like.

[0255] The mail subscription function is realized, the user is allowed to subscribe to a specific report, and periodic sending is supported. The mail sending parameters are configured, including sending time and frequency. According to the mail subscription configuration, the report is automatically sent to the relevant personnel.

[0256] The page browsing function is provided, and the user is allowed to view the report online. Various display modes are supported, such as a webpage and a PDF.

[0257] Example 4: Software report view of different dimensions.

[0258] Each software can be optimized and improved by percentage or 5-point scoring to improve the work of some dimensions, or by radar chart distribution to intuitively detect the indicators that need to be improved. From the five-point scoring, generally 1-2 is a poor level and needs to be improved in time; 3-4 is a medium level and still has room for improvement; and 5 is an excellent level and continues to maintain the existing level.

[0259] In the background of the digital era, the embodiment of the application jumps out of the original thinking that the software development health degree evaluation is limited to a certain dimension. The system realizes intelligent evaluation of the software development process from multiple angles such as the demand analysis and design, development, testing, release and other key stages of software, and the composition and input-output of software team capability by constructing a "radar chart scoring model".

[0260] Meanwhile, the embodiment of the application realizes full-process automation of data collection and processing, and reduces manual intervention. In the execution process of each indicator, the system can automatically record the completion time and related indicator value, to ensure that the software physical examination is efficiently performed.

[0261] The following will be described in detail in combination with another embodiment.

[0262] Embodiment two

[0263] The multi-dimensional software development evaluation device provided in the embodiment includes a plurality of implementation units, and each implementation unit corresponds to each implementation step in the above embodiment one.

[0264] Figure 8 It is a schematic diagram of an optional multi-dimensional software development evaluation device according to the embodiment of the application, as shown in Figure 8 The multi-dimensional software development evaluation device can include an indicator data acquisition unit 81, an indicator value calculation unit 82, an indicator scoring unit 83 and a software development evaluation unit 84.

[0265] The index data acquisition unit 81 is configured to acquire the pre-defined software development metric dimensions and metric indexes, and collect software development data in a trusted environment.

[0266] The index value calculation unit 82 is configured to calculate the index values associated with each metric index in the software development data according to a pre-defined calculation rule.

[0267] The index scoring unit 83 is configured to score each metric index according to the index values of all metric indexes to obtain an index score.

[0268] The software development evaluation unit 84 is configured to generate a software development health report according to a report configuration template based on the index score of each metric index and the score corresponding to the metric dimension.

[0269] The above-mentioned multi-dimensional software development evaluation device can acquire the pre-defined software development metric dimensions and metric indexes through the index data acquisition unit, and collect software development data in a trusted environment. The index value calculation unit is configured to calculate the index values associated with each metric index in the software development data according to a pre-defined calculation rule. The index scoring unit is configured to score each metric index according to the index values of all metric indexes to obtain an index score. The software development evaluation unit is configured to generate a software development health report according to a report configuration template based on the index score of each metric index and the score corresponding to the metric dimension. In this embodiment, a software development health detection method is provided, which can automatically collect data indexes and comprehensively evaluate, automatically generate a software development health report, measure the key stages in the whole life cycle of software, significantly reduce the dependence on manual operation in software development measurement, improve the accuracy of measurement results, and reduce the measurement cost and improve the processing speed of measurement data through automatic process, thereby solving the technical problems of software development measurement method depending on manual operation and low accuracy of measurement results in the related art.

[0270] Optionally, the index data collection unit comprises: a metric dimension reading module, configured to read a plurality of metric dimensions in the software development process from the configuration module, wherein the metric dimensions comprise at least one of the following: a requirement metric dimension, a development metric dimension, a test metric dimension, a release metric dimension, a resource metric dimension, and a cost metric dimension; and a metric index reading module, configured to read corresponding metric indexes under each metric dimension, wherein the corresponding metric indexes under the requirement metric dimension comprise a requirement throughput and a requirement delivery cycle, the corresponding metric indexes under the development metric dimension comprise a task throughput and a task value ratio, the corresponding metric indexes under the test metric dimension comprise an automated test execution case ratio, the corresponding metric indexes under the release metric dimension comprise a release frequency score and an online success rate score, the corresponding metric indexes under the resource metric dimension comprise a plurality of level ratio scores, and the corresponding metric indexes under the resource metric dimension comprise a thousand-line code cost score.

[0271] Optionally, the index data collection unit further comprises: a system interfacing module, configured to interface a requirement management system, a code management system, a test management system, a production management system, and an online work order system in a trusted environment, automatically pull data required for the metric indexes, and obtain software development data; and a data preprocessing module, configured to preprocess the software development data, wherein the preprocessing operations comprise at least one of the following: data format unification, removal of abnormal values, and removal of duplicate values.

[0272] Optionally, the index value calculation unit comprises: a first formula calling module, configured to call pre-defined calculation formulas corresponding to the metric indexes according to pre-defined calculation rules; and a first calculation module, configured to calculate data associated with each metric index in the preprocessed software development data by using the pre-defined calculation formulas, and obtain the index data.

[0273] Optionally, the index score unit comprises: a second formula calling module, configured to call index score formulas corresponding to the metric indexes based on pre-configured scoring rules; and a scoring module, configured to perform scoring processing on the index values of the calculated metric indexes by using the index score formulas, and obtain the index scores.

[0274] Optionally, the software development evaluation unit comprises: a second calculation module, configured to calculate a dimension score corresponding to each metric dimension based on the index scores corresponding to all the metric indexes under the metric dimension; a data table construction module, configured to construct a report data table based on the index scores corresponding to all the metric indexes and the dimension scores corresponding to all the metric dimensions; and a report generation module, configured to input the report data table into a pre-defined report configuration template, and generate a software development health degree report.

[0275] Optionally, the multi-dimension based software development evaluation apparatus further comprises: a radar chart generation unit, configured to generate a multi-dimension radar chart of the target software according to the report configuration template after generating the software development health degree report based on the metric score of each metric indicator and the score corresponding to the metric dimension, and display the score distribution of the target software in each metric dimension by using the multi-dimension radar chart; and a score output unit, configured to determine a comprehensive development score of the target software according to a calculation rule of the multi-dimension radar chart, and output the multi-dimension radar chart and the comprehensive development score.

[0276] The multi-dimension based software development evaluation apparatus can further comprise a processor and a memory, and the index data acquisition unit 81, the index value calculation unit 82, the index scoring unit 83, and the software development evaluation unit 84 are stored in the memory as program units, and the corresponding functions are realized by the processor executing the program units stored in the memory.

[0277] The processor comprises a core, and the core retrieves the corresponding program units from the memory. The core can be one or more, and the health degree evaluation in the software development process based on multiple metric dimensions is realized by adjusting the core parameters.

[0278] The memory can comprise a non-permanent memory in a computer readable medium, a random access memory (RAM), and / or a non-volatile memory such as a read-only memory (ROM) or a flash memory (flash RAM), and the memory comprises at least one memory chip.

[0279] According to another aspect of the embodiments of the present application, a computer readable storage medium is also provided, which comprises a stored computer program, wherein the computer readable storage medium controls the device where the computer readable storage medium is located to perform the multi-dimension based software development evaluation method in any one of the above-mentioned embodiments one when the computer program is running.

[0280] According to another aspect of the embodiments of the present application, an electronic device is also provided, which comprises one or more processors and a memory, and the memory is configured to store one or more programs, wherein the one or more programs, when executed by the one or more processors, cause the one or more processors to implement the multi-dimension based software development evaluation method in any one of the above-mentioned embodiments one.

[0281] The present application also provides a computer program product comprising a computer program, which, when executed by a processor, implements the steps of the multi-dimension based software development evaluation method in the embodiments of the present application.

[0282] This application also provides a computer program product, including a non-volatile computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of the multi-dimensional software development evaluation method described in various embodiments of this application.

[0283] Figure 9 This is a hardware structure block diagram of an electronic device (or mobile device) implementing a multi-dimensional software development evaluation method according to an embodiment of the present invention. Figure 9 As shown, an electronic device may include one or more ( Figure 9 The processor 902 (which may include, but is not limited to, a microprocessor MCU or a programmable logic device FPGA, etc.) and a memory 904 for storing data are also included. In addition, the device may include: a display, an input / output interface (I / O interface), a universal serial bus (USB) port (which may be included as one of the ports in the I / O interface), a network interface, a keyboard, a power supply, and / or a camera. Those skilled in the art will understand that... Figure 9 The structure shown is for illustrative purposes only and does not limit the structure of the electronic device described above. For example, the electronic device may also include components that are more... Figure 9 The more or fewer components shown, or having the same Figure 9 The different configurations shown.

[0284] The sequence numbers of the above embodiments of the present invention are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0285] In the above embodiments of the present invention, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0286] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. The device embodiments described above are merely illustrative; for example, the division of units can be a logical functional division, and in actual implementation, there may be other division methods. For instance, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the displayed or discussed mutual coupling, direct coupling, or communication connection may be through some interfaces; the indirect coupling or communication connection between units or modules may be electrical or other forms.

[0287] The units described as separate components may or may not be physically separate, and the components displayed as units may or may not be physical units, that is, may be located in one place, or may be distributed to multiple units. Part or all of the units can be selected according to actual needs to achieve the purpose of the embodiment scheme.

[0288] In addition, each functional unit in each embodiment of the present application can be integrated in one processing unit, or each unit can exist physically, or two or more units can be integrated in one unit. The integrated unit can be realized in the form of hardware or in the form of a software functional unit.

[0289] The integrated unit, if realized in the form of a software functional unit and sold or used as an independent product, can be stored in a computer readable storage medium. Based on such understanding, the technical scheme of the present application or the part of the present application which contributes to the prior art or the whole or part of the technical scheme can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes a plurality of instructions for causing a computer device (which can be a personal computer, a server or a network device, etc.) to execute all or part of the steps of the method described in each embodiment of the present application. The foregoing storage medium includes a U disk, a read-only memory (ROM), a random access memory (RAM), a mobile hard disk, a magnetic disk or an optical disk, and various program code storage media.

[0290] The above is only the preferred embodiment of the present application, and it should be pointed out that for ordinary skilled in the art, without departing from the principles of the present application, a number of improvements and refinements can be made, and these improvements and refinements should be considered as the protection scope of the present application.

Claims

1. A multi-dimensional based software development evaluation method, comprising: The method comprises the following steps: acquiring pre-defined software development metric dimensions and metric indicators, and collecting software development data in a trusted environment; calculating metric values associated with each of the metric indicators in the software development data according to pre-defined calculation rules; performing numerical scoring on each of the metric indicators according to the metric values of all the metric indicators to obtain indicator scores; generating a software development health degree report according to a report configuration template based on the indicator scores of each of the metric indicators and the scores corresponding to the metric dimensions.

2. The software development evaluation method of claim 1, wherein, The step of acquiring pre-defined software development metric dimensions and metric indicators comprises: reading multiple metric dimensions in a software development process from a configuration module, wherein the metric dimensions comprise at least one of the following: a requirement metric dimension, a development metric dimension, a test metric dimension, a release metric dimension, a resource metric dimension, and a cost metric dimension; reading corresponding metric indicators under each of the metric dimensions, wherein the corresponding metric dimensions under the requirement metric dimension comprise requirement throughput and requirement delivery period, the corresponding metric dimensions under the development metric dimension comprise task throughput and task value ratio, the corresponding metric dimensions under the test metric dimension comprise automated test execution case ratio, the corresponding metric dimensions under the release metric dimension comprise release frequency score and online success rate score, the corresponding metric dimensions under the resource metric dimension comprise multiple level ratio scores, and the corresponding metric dimensions under the resource metric dimension comprise thousand-line code cost score.

3. The software development evaluation method of claim 1, wherein, The step of collecting software development data in a trusted environment comprises: connecting a requirement management system, a code management system, a test management system, a production management system, and an online work order system in a trusted environment, automatically pulling data required for the metric indicators to obtain the software development data; performing preprocessing on the software development data, wherein the preprocessing operations comprise at least one of the following: data format unification, abnormal value removal, and duplicate value removal.

4. The software development evaluation method of claim 1, wherein, The step of calculating metric values associated with each of the metric indicators in the software development data according to pre-defined calculation rules comprises: calling pre-defined calculation formulas corresponding to each metric indicator according to pre-defined calculation rules; calculating data associated with each of the metric indicators in the preprocessed software development data by using the pre-defined calculation formulas to obtain the metric data. The step of performing numerical scoring on each of the metric indicators according to the metric values of all the metric indicators to obtain indicator scores comprises:

5. The software development evaluation method of claim 1, wherein, calling an indicator scoring formula corresponding to the metric indicator based on a pre-configured scoring rule; performing scoring processing on the calculated metric values of the metric indicators by using the indicator scoring formula to obtain the indicator scores. The step of generating a software development health degree report according to a report configuration template based on the indicator scores of each of the metric indicators and the scores corresponding to the metric dimensions comprises:

6. The software development evaluation method of claim 1, wherein, calculating a dimension score corresponding to each of the metric dimensions based on the indicator scores of all the metric indicators corresponding to the metric dimensions; and generating the software development health degree report according to the report configuration template based on the dimension scores corresponding to the metric dimensions. constructing a report data table based on the index scores corresponding to all the metric indicators and the dimension scores corresponding to all the metric dimensions; entering the report data table into the predefined report configuration template to generate the software development health report.

7. The software development evaluation method of claim 1, wherein, After generating the software development health report according to the report configuration template based on the index scores corresponding to each of the metric indicators and the dimension scores corresponding to the metric dimensions, the method further includes: generating a multi-dimensional radar chart associated with the target software, and displaying the score distribution of the target software in each metric dimension by using the multi-dimensional radar chart; determining a comprehensive development score of the target software according to a calculation rule of the multi-dimensional radar chart, and outputting the multi-dimensional radar chart and the comprehensive development score.

8. A multi-dimensional based software development evaluation apparatus, comprising: The method includes: an index data collection unit configured to acquire predefined software development metric dimensions and metric indicators, and collect software development data in a trusted environment; an index value calculation unit configured to calculate index values associated with each of the metric indicators in the software development data according to a predefined calculation rule; an index scoring unit configured to score each of the metric indicators according to the index values of all the metric indicators to obtain index scores; a software development evaluation unit configured to generate a software development health report according to a report configuration template based on the index scores corresponding to each of the metric indicators and the dimension scores corresponding to the metric dimensions.

9. An electronic device, comprising: One or more processors and a memory are included, and the memory is configured to store one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors are caused to implement the multi-dimensional based software development evaluation method of any one of claims 1 to 7.

10. A computer program product comprising a computer program, characterized in that, The computer program is executed by the processor to implement the steps of the multi-dimensional based software development evaluation method of any one of claims 1 to 7.

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