CN111260133A - Optimization method and device for quality monitoring model for monitoring R&D quality - Google Patents

Abstract

In the optimization method, whether the software quality of published software of each research and development team is abnormal or not is judged based on a distribution curve and a control limit corresponding to a monitoring index of the software quality in a control chart, and the distribution curve is drawn based on a plurality of statistical values obtained by each research and development team according to statistics of the monitoring index. And if the software quality of the published software of any first research and development team is abnormal, selecting a target factor influencing the monitoring index from a plurality of quality factors contained in a quality monitoring model pre-configured by the first research and development team. The quality monitoring model is used for monitoring the development quality of a first development team in the process of developing software, and is determined based on the weighted combination result of a plurality of quality factors. And at least adjusting the weight value set by the first research and development team aiming at the target factor so as to realize the optimization of the quality monitoring model.

Description

Optimization method and device for quality monitoring model for monitoring R&D quality

technical field

One or more embodiments of this specification relate to the field of computer technology, and in particular, to a method and apparatus for optimizing a quality monitoring model for monitoring R&D quality.

Background technique

In the process of developing software by the R&D team, the R&D quality of the R&D team directly affects the software quality of the final released or released software. If the R&D quality of the R&D team does not meet the relevant standards, it will directly lead to the normal operation of the software after it is released, which will bring incalculable losses to the enterprise. Therefore, the monitoring of R&D quality in the software R&D process becomes the key.

In the R&D integrated R&D model, it is generally the R&D personnel themselves who control the quality of each stage of the R&D process. However, there will be a problem in this way. R&D personnel develop and test by themselves, and judge by themselves whether the research and development task can be advanced to the next stage, or even whether it can be released to the production environment. This has the potential to bring certain quality risks to the production environment. Therefore, there is a need to provide a more reliable R&D quality monitoring method.

SUMMARY OF THE INVENTION

One or more embodiments of this specification describe an optimization method and apparatus for a quality monitoring model for monitoring R&D quality, so that the optimized quality monitoring model can effectively monitor R&D quality.

In a first aspect, an optimization method for a quality monitoring model for monitoring R&D quality is provided, including:

Based on the distribution curve corresponding to the monitoring index of software quality in the control chart and the control limit, it is judged whether the software quality of the released software of each R&D team is abnormal; the distribution curve is based on the statistics of each R&D team for the monitoring index. The obtained multiple statistical values are drawn;

If the software quality of the released software of any first R&D team is abnormal, select the target factor that affects the monitoring index from several quality factors included in the quality monitoring model preconfigured by the first R&D team; The quality monitoring model is used to monitor the research and development quality of the first research and development team in the software development process; the quality monitoring model is determined based on the weighted combination result of the several quality factors;

At least the weight value set by the first R&D team for the target factor is adjusted to optimize the quality monitoring model preconfigured by the first R&D team.

In the second aspect, a monitoring method for R&D quality is provided, including:

After the current R&D stage of the R&D team ends, the respective values of several quality factors included in the quality monitoring model optimized by the R&D team are obtained; wherein, the quality monitoring model is used for the R&D team in the process of developing software. R&D quality is monitored, which is optimized by the method described in the first aspect above;

Input the respective values of the several quality factors into the quality monitoring model, and output the corresponding score value;

Assess whether there is any abnormality in the quality of research and development at the current research and development stage, based at least on the score value;

If there is an abnormality, according to a predetermined notification method, a notification message that the research and development quality of the current research and development stage is abnormal is sent to the predetermined person.

In a third aspect, an optimization device for a quality monitoring model for monitoring R&D quality is provided, including:

The judgment unit is used for judging whether the software quality of the released software of each R&D team is abnormal based on the distribution curve corresponding to the monitoring index of the software quality in the control chart and the control limit; It is drawn from the multiple statistical values obtained from the statistics of the monitoring indicators;

A selection unit, configured to select from several quality factors included in the quality monitoring model preconfigured by the first R&D team if the determination unit determines that the software quality of the released software of any first R&D team is abnormal the target factor affecting the monitoring index; the quality monitoring model is used to monitor the R&D quality of the first R&D team in the process of developing the software; the quality monitoring model is based on the weighted combination result of the several quality factors to determine;

The adjustment unit is configured to adjust at least the weight value set by the first R&D team for the target factor selected by the selection unit, so as to realize the optimization of the quality monitoring model pre-configured by the first R&D team.

In a fourth aspect, a research and development quality monitoring device is provided, including:

The obtaining unit is used to obtain the respective values of several quality factors included in the quality monitoring model optimized by the research and development team after the current research and development stage of the research and development team is completed; wherein, the quality monitoring model is used for the research and development team in the research and development team. Monitoring the quality of research and development in the process of developing the software, which is optimized by the method as described in the first aspect above;

an input-output unit, configured to input the respective values of the several quality factors obtained by the obtaining unit into the quality monitoring model, and output corresponding score values;

An evaluation unit, configured to evaluate whether there is an abnormality in the research and development quality of the current research and development stage based on at least the score value output by the input and output unit;

The sending unit is configured to send a notification message that the research and development quality of the current research and development stage is abnormal according to a predetermined notification method if the assessment by the assessment unit is abnormal.

In a fifth aspect, a computer storage medium is provided on which a computer program is stored, and when the computer program is executed in a computer, the computer is made to execute the method of the first aspect or the second aspect.

In a sixth aspect, a computing device is provided, including a memory and a processor, the memory stores executable code, and when the processor executes the executable code, the method of the first aspect or the second aspect is implemented.

The optimization method and device for a quality monitoring model for monitoring R&D quality provided by one or more embodiments of this specification, by monitoring the monitoring indicators of software quality, to determine whether the software quality of the released software of each R&D team is abnormal, and When an abnormality is detected in the software quality of the released software of a R&D team, the weight value of the quality factor affecting the monitoring index is adjusted to optimize the quality monitoring model pre-configured by the R&D team. That is, in this solution, a method for optimizing the quality monitoring model based on online result data is proposed, which can greatly improve the accuracy of the quality monitoring model. In addition, the optimized quality monitoring model can effectively monitor the R&D quality, thereby effectively reducing the quality failure of online software.

Description of drawings

In order to illustrate the technical solutions of the embodiments of the present specification more clearly, the following briefly introduces the accompanying drawings used in the description of the embodiments. Obviously, the drawings in the following description are only some embodiments of the present specification. For those of ordinary skill in the art, other drawings can also be obtained from these drawings without any creative effort.

Figure 1 is a schematic diagram of the quality monitoring platform provided in this specification;

2 is a flowchart of an optimization method for a quality monitoring model for monitoring R&D quality provided by an embodiment of the present specification;

3 is a flowchart of a method for monitoring R&D quality provided by an embodiment of this specification;

4 is a schematic diagram of an optimization device for a quality monitoring model for monitoring R&D quality provided by an embodiment of the present specification;

FIG. 5 is a schematic diagram of a monitoring device for research and development quality provided by an embodiment of the present specification.

Detailed ways

The solution provided in this specification will be described below with reference to the accompanying drawings.

Before describing the solution provided by this specification, the inventive concept of the solution is described as follows.

As described in the background art, in the traditional technology, the R&D quality of the R&D team in the process of developing software is usually monitored manually. This monitoring method has the problems of low efficiency and inaccurate monitoring. To solve this problem, the applicant of the present application proposes the idea of monitoring R&D quality based on a quality monitoring model.

Specifically, the R&D team can pre-configure the quality monitoring model. The quality monitoring model is used to monitor the R&D quality in the R&D process after each R&D process, which can be determined based on a weighted combination result of several quality factors. The quality factor here can be extracted manually. In addition, the inventors of the present application also consider that the R&D quality in the R&D process can be monitored by combining the values of important factors among several quality factors. For example, it is judged whether the corresponding value of the above-mentioned important factor is greater than the corresponding threshold value, and if it is greater than the corresponding threshold value, it is judged that there is no abnormality in the research and development quality of the current research and development process.

It should be noted that, for the quality monitoring model pre-configured by a R&D team member, it can be optimized by the following methods: monitoring whether the R&D team has software released online, and if so, you can periodically monitor the monitoring indicators of software quality. If the monitoring index is abnormal, the software quality of the corresponding released software is abnormal. At this time, the target factors affecting the above monitoring indicators can be selected from several quality factors included in the quality monitoring model preconfigured by the R&D team. The weight value set by the R&D team for the target factor is adjusted to realize the optimization of the quality monitoring model pre-configured by the R&D team. It should be understood that the optimization process of the quality monitoring model is performed repeatedly. After obtaining the optimized quality monitoring model, the R&D team can monitor the R&D quality in the subsequent software R&D process based on the optimized quality monitoring model.

It should be noted that, in this solution, the software quality monitoring of the released software of each R&D team can be implemented based on the control chart. The control chart is located in a rectangular coordinate system, wherein the horizontal axis of the rectangular coordinate system can be used to record each R&D team, and the vertical axis can be used to record a plurality of statistical values obtained by each R&D team for monitoring indicators. It is understandable that, based on a plurality of statistical values obtained by each R&D team for a monitoring indicator, a distribution curve corresponding to the monitoring indicator can be drawn.

It should be understood that, in one control chart, distribution curves corresponding to multiple monitoring indicators can usually be drawn. In the following description of this specification, a control chart including a distribution curve corresponding to only one monitoring index will be used as an example for description.

The above is the inventive concept provided in this specification, and the solution can be obtained based on the inventive concept. The solution is described in detail below.

Figure 1 is a schematic diagram of the quality monitoring platform provided in this specification. In Figure 1, a R&D team can extract several quality factors in advance, and the value of the quality factor here can be used to reflect the R&D quality of the R&D team in the process of developing software. For the above quality factors, the R&D team can also set corresponding weight values for them, so that the quality monitoring platform can build a quality monitoring model corresponding to the R&D team based on the extracted quality factors and the set weight values.

After that, after each R&D stage of the R&D team ends, the R&D quality of the R&D stage can be monitored based on the quality detection model. In addition, the R&D quality in the R&D process can be monitored by combining the values of important factors among several quality factors. If there is no abnormality in the monitoring, enter the next R&D stage; otherwise, send a notification message to the predetermined personnel that there is an abnormality in the current R&D stage.

It should be noted that, for the above-mentioned quality monitoring model, it is possible to judge whether there is an abnormality in the software quality of the R&D team by analyzing the distribution curve of the monitoring indicators in the control chart, and if there is an abnormality, adjust the parameters that affect the monitoring indicators. The weight value of the quality factor is used to realize the optimization of the above-mentioned quality monitoring model, thereby realizing the accurate monitoring of the R&D quality of the R&D team.

FIG. 2 is a flowchart of an optimization method for a quality monitoring model for monitoring R&D quality provided by an embodiment of the present specification. The execution body of the method may be a device with processing capability: a server or a system or an apparatus, for example, the quality monitoring platform in FIG. 1 . As shown in Figure 2, the method may specifically include:

Step 202 , based on the distribution curve corresponding to the monitoring index of the software quality in the control chart and the control limit, determine whether the software quality of the released software of each R&D team is abnormal.

The above-mentioned monitoring indicators of software quality may include, but are not limited to, release rollback rate and number of online failures. Through the fluctuation analysis of the statistical value of the monitoring index, abnormal monitoring of software quality can be realized.

In one example, the above control diagram may be as shown in FIG. 3 . In FIG. 3 , the control chart is located in a rectangular coordinate system. The horizontal axis of the rectangular coordinate system is used to record each R&D team, and the vertical axis is used to record a plurality of statistical values obtained by each R&D team for a monitoring indicator. It should be noted that a data point can be uniquely determined based on a R&D team and a statistical value obtained by the R&D team for the monitoring indicator. That is, each data point corresponds to an R&D team and one of multiple statistical values. It should be understood that, based on the determined multiple data points, a distribution curve corresponding to the monitoring index can be obtained by drawing.

In Figure 3, in addition to the above distribution curve, the control diagram also includes three straight lines parallel to the horizontal axis. , CentralLine), the bottom straight line is called the lower control limit (LCL, Lower Control Limit). The center line here is determined based on the average of the statistical values of the monitoring indicators. The upper and lower control limits are determined based on the mean and multiple (eg, ±3) standard deviations of the statistical values of the monitored indicators. The above-mentioned upper control limit and lower control limit may constitute a control region.

It should be understood that, as an example, only a distribution curve corresponding to one monitoring index is shown in FIG. 3 . In practical applications, multiple distribution curves corresponding to multiple monitoring indicators can be drawn in the control chart, which is not limited in this specification.

Returning to step 202, in an implementation manner, the above judgment process may specifically be: judging whether there is a target data point located outside the control area in the distribution curve corresponding to the monitoring index. If so, it is determined that there is an abnormality in the software quality of the released software of the research and development team corresponding to the target data point. Otherwise, the software quality of the released software of each R&D team is normal. Taking Figure 3 as an example, since there are no target data points outside the control area in the distribution curve, the software quality of the released software of each R&D team is normal.

In another implementation manner, it is also possible to judge whether there is any abnormality in the software quality of the released software of each R&D team based on other criteria of the control chart, for example, a certain data point is too close to the center line, which is not limited in this specification. .

Step 204 , if the software quality of the released software of any first R&D team is abnormal, select the target factor affecting the monitoring index from several quality factors included in the quality monitoring model preconfigured by the first R&D team.

The quality monitoring model here is used to monitor the R&D quality of the first R&D team in the process of developing the software, and the quality monitoring model is determined based on a weighted combination result of several quality factors. The value of the quality factor here can reflect the R&D quality of the first R&D team in the process of developing the software. The above-mentioned quality factors may include, but are not limited to, unit test coverage, functional test coverage, code specification, and the number of black-and-white box security scans.

For the important factors in the above quality factors (selected by the first R&D team in combination with the product form), the corresponding thresholds can usually be set, so that the quality monitoring platform can combine the thresholds of the important factors and the monitoring results of the quality monitoring model to jointly evaluate Whether there is any abnormality in R&D quality. In one example, an evaluation rule may be set, which at least indicates that the value of the important factor needs to exceed a threshold. After that, it can be combined with the evaluation rules and the monitoring results of the quality monitoring model to jointly evaluate whether there is any abnormality in the R&D quality.

It should be noted that there may be a many-to-many relationship between the above-mentioned quality factors and monitoring indicators. Specifically, one quality factor can affect multiple monitoring indicators, and one monitoring indicator can be affected by multiple quality factors. It should be understood that the corresponding relationship between the quality factor and the monitoring index can be set by each R&D team based on its own situation. That is to say, different R&D teams have different correspondences between the quality factors set by them and the monitoring indicators. Therefore, after the first R&D team is determined, the target factor affecting the monitoring index can be selected from several quality factors included in the quality monitoring model preconfigured by the first R&D team. The number of target factors can be one or more.

For example, when the monitoring indicator is the release rollback rate, the target factor affecting the release rollback rate can be selected from several quality factors included in the quality monitoring model preconfigured by the first R&D team.

Step 206 , at least adjust the weight value set by the first R&D team for the target factor, so as to realize the optimization of the quality monitoring model preconfigured by the first R&D team.

In an implementation manner, the weight value corresponding to the target factor may be adjusted according to the experience value.

In another implementation manner, the adjustment process of the weight value corresponding to the target factor may also be as follows: other data points except the target data point are selected from the distribution curve corresponding to the monitoring index. Several reference R&D teams were identified from the respective R&D teams corresponding to the other data points. Among them, each quality factor that affects the above-mentioned monitoring indicators set by the reference R&D team includes the above-mentioned target factors. Based on the weight values set by each reference R&D team for the target factor, the weight value set by the first R&D team for the target factor is adjusted. For example, the weight values set by each reference R&D team for the target factor can be averaged or weighted average, and then the averaged result or the weighted average result can be taken as the adjusted weight value of the target factor of the first R&D team.

For another example, the target R&D team can also be selected from each reference R&D team. Wherein, the weight value set by the target R&D team for the target factor is not lower than the weight value set by the first R&D team for the target factor. From the weight values set by the target R&D team for the target factor, select the maximum weight value and the minimum weight value. Based on the maximum weight value and the minimum weight value, the weight value set by the first R&D team for the target factor is adjusted. Specifically, an intermediate value between the maximum weight value and the minimum weight value can be taken as the adjusted weight value of the target factor of the first R&D team.

It can be understood that, since the quality monitoring model preconfigured by the first R&D team is determined based on the weighted combination results of several quality factors, when the weight values of some quality factors (eg, target factors) in the several quality factors are adjusted, The corresponding quality monitoring model is optimized.

It should be understood that the above steps 202 to 206 are performed periodically and repeatedly, that is, the optimization process of the quality monitoring model is performed iteratively.

In addition to the above optimization methods, the quality monitoring model pre-configured by the first R&D team can also be optimized in the following way: For each reference R&D team in the several reference R&D teams determined above, from the reference R&D team set by the reference R&D team Among the quality factors affecting the above monitoring indicators, other factors other than the target factor are selected. Obtain the weight value set by the reference R&D team for the other factor. Based on other factors and the weight values corresponding to the other factors, the quality monitoring model preconfigured by the first R&D team is optimized. For example, the other factors and the corresponding weight values can be added to the quality monitoring model preconfigured by the first R&D team, and the optimization can be realized based on this.

It should be noted that the above-mentioned second optimization method is also performed iteratively. In addition, in practical applications, one of the above two optimization methods can be selected to optimize the quality monitoring model pre-configured by the first R&D team. Of course, the quality monitoring model preconfigured by the first R&D team can also be optimized by combining the above two optimization methods, which is not limited in this specification.

It should also be noted that when the first R&D team also evaluates its R&D quality based on the thresholds of important factors, it can also obtain multiple thresholds set by each reference R&D team for important factors, and then, based on the multiple thresholds , and adjust the thresholds set by the first R&D team for important factors. For example, multiple thresholds can be averaged or weighted averaged, and the averaged or weighted average result can be used as the adjusted threshold of the important factor of the first R&D team.

It should be understood that, as an example, the embodiments of this specification take a monitoring index as an example to describe the optimization process of the quality monitoring model preconfigured by the first research and development team. In practical applications, the quality monitoring model can usually be optimized by combining multiple monitoring indicators, which is not limited in this description. In addition, for other R&D teams other than the first R&D team, the optimization process of the corresponding quality monitoring model is the same as that described above, which will not be repeated here.

To sum up, the embodiments of this specification propose a method for optimizing a quality monitoring model for monitoring R&D quality based on online index results, thereby greatly improving the accuracy of the optimized quality monitoring model. In addition, the quality monitoring model based on the optimization can realize the effective monitoring of R&D quality, and then can improve the software quality.

FIG. 3 is a flowchart of a method for monitoring R&D quality provided by an embodiment of the present specification. The execution body of the method may be a device with processing capability: a server or a system or an apparatus, for example, the quality monitoring platform in FIG. 1 . As shown in Figure 3, the method may specifically include:

Step 302 , after the current R&D stage of the R&D team ends, obtain the respective values of several quality factors included in the quality monitoring model optimized by the R&D team.

The above-mentioned R&D team may be any one of the aforementioned R&D teams. In addition, the above-mentioned quality monitoring model is used to monitor the R&D quality of the R&D team in the process of developing the software, which can be optimized by the method shown in FIG. 2 .

In addition, the quality factor here may be as described in step 204, that is, it may include but not limited to unit test coverage, functional test coverage, code specification, number of black and white box security scans, and the like. Taking unit test coverage as an example, its value may be, for example, 80% or 50%, and so on. It can be understood that, for a certain R&D stage, for each quality factor, there can be a unique value corresponding to it.

Step 304: Input the respective values of several quality factors into the quality monitoring model, and output the corresponding score values.

As mentioned above, the quality monitoring model is determined based on the weighted combination result of several quality factors, so after determining the corresponding value for each quality factor, based on the values of these quality factors and the corresponding weight value, the A fractional value can be calculated.

Step 306, at least based on the output score value, assess whether there is any abnormality in the research and development quality of the current research and development stage.

For example, it can be determined whether the output score value is greater than the predetermined score, and if it is greater than the predetermined score, it is estimated that there is an abnormality in the research and development quality of the current research and development stage, otherwise there is no abnormality.

Of course, in practical applications, it can also be combined with evaluation rules to determine whether there is any abnormality in the R&D quality at the current R&D stage. The evaluation rule at least indicates that the value of the important factor among the several quality factors needs to exceed the corresponding threshold.

For example, if the output score is not greater than the predetermined score, it is also judged whether the value of the important factor indicated in the evaluation rule is greater than the corresponding threshold. The threshold value here can be preset manually, or it can be determined in the process of optimizing the quality monitoring model. Only when the value of the important factor is greater than the corresponding threshold can it be determined that there is no abnormality in the R&D quality at the current R&D stage. Otherwise, it is still determined that there is an exception.

Step 308 , if there is an abnormality, send a notification message that the R&D quality in the current R&D stage is abnormal according to a predetermined notification method to a predetermined person.

In one example, when it is determined that the R&D quality in the current R&D stage is abnormal, a notification message that the R&D quality in the current R&D stage is abnormal may be sent to the predetermined personnel according to a predetermined notification method (eg, SMS, email, or internal communication tool, etc.). .

In addition, when it is determined that the R&D quality in the current R&D stage is abnormal, a quality factor whose corresponding value is lower than the corresponding threshold value can also be output. Afterwards, the evaluation rule is adjusted based on the predefined modification suggestion corresponding to the selected quality factor and the corresponding threshold value. For example, the modification suggestion may be: adding the selected quality factor to the evaluation rule must exceed the limit of the corresponding threshold; or, increasing the threshold corresponding to the selected quality factor, and then adding the selected quality factor to the evaluation rule The factor needs to exceed the limit of the increased threshold.

To sum up, the R&D quality monitoring method provided by the embodiments of this specification can accurately monitor the R&D quality of the R&D team at each R&D stage in the process of developing software, thereby improving the software quality of the software developed by the R&D team.

In a word, the solutions provided by the embodiments of this specification have the following advantages:

First, in the process of iterative development of research and development, the quality monitoring platform can be used to automatically control quality risks and recommend improvement plans, which solves the untimely risk disclosure and inconsistency of quality standards during manual control.

Second, provide a basis and method for the improvement of the overall quality strategy of the R&D team, and improve the overall R&D quality of the R&D team.

Corresponding to the above-mentioned optimization method for a quality monitoring model for monitoring R&D quality, an embodiment of the present specification further provides an optimization device for a quality monitoring model for monitoring R&D quality, as shown in FIG. 4 , the device may include: :

The judging unit 402 is configured to judge whether the software quality of the released software of each R&D team is abnormal based on the distribution curve corresponding to the monitoring index of the software quality in the control chart and the control limit. The distribution curve is drawn based on a plurality of statistical values obtained by each R&D team for the monitoring indicator.

The distribution curve may include a plurality of data points, wherein each data point corresponds to a research and development team of the research and development teams and a statistical value of the plurality of statistical values. The above-mentioned control limits may include an upper control limit and a lower control limit, and the upper control limit and the lower control limit constitute a control area.

The judging unit 402 can be specifically used for:

Determine whether there are target data points outside the control area in the distribution curve corresponding to the monitoring index.

If so, it is determined that there is an abnormality in the software quality of the released software of the research and development team corresponding to the target data point.

In addition, the above monitoring indicators may include any of the following: release rollback rate and number of online failures.

The selecting unit 404 is configured to select the influence from several quality factors included in the quality monitoring model preconfigured by the first research and development team if the judgment unit 402 judges that the software quality of the released software of any first research and development team is abnormal. The target factor for this monitoring indicator. The quality monitoring model is used to monitor the R&D quality of the first R&D team in the process of developing the software, and the quality monitoring model is determined based on a weighted combination result of several quality factors.

The aforementioned quality factor may include several of unit test coverage, functional test coverage, code specification, and number of black and white box security scans.

The adjustment unit 406 is configured to adjust at least the weight value set by the first R&D team for the target factor selected by the selection unit 404, so as to realize the optimization of the quality monitoring model preconfigured by the first R&D team.

The adjustment unit 406 can be specifically used for:

From the distribution curve corresponding to the monitoring index, select other data points except the target data point.

A number of reference R&D teams are determined from the respective R&D teams corresponding to other data points, wherein the quality factors of the impact monitoring indicators set by each reference R&D team include target factors.

Based on the weight values set by each reference R&D team for the target factor, the weight value set by the first R&D team for the target factor is adjusted.

The adjustment unit 406 can also be specifically used for:

A target R&D team is selected from each reference R&D team, wherein the weight value set by the target R&D team for the target factor is not lower than the weight value set by the first R&D team for the target factor.

From the weight values set by the target R&D team for the target factor, select the maximum weight value and the minimum weight value.

Based on the maximum weight value and the minimum weight value, the weight value set by the first R&D team for the target factor is adjusted.

Optionally, the apparatus may further include: an acquisition unit (not shown in the figure) and an optimization unit (not shown in the figure).

The selecting unit 404 is further configured to, for each reference R&D team in the several reference R&D teams, select other factors except the target factor from the quality factors affecting the monitoring index set by the reference R&D team.

The obtaining unit is configured to obtain the weight values set by the reference R&D team for other factors selected by the selecting unit 404 .

The optimization unit is configured to optimize the quality monitoring model preconfigured by the first research and development team based on the other factors selected by the selection unit 404 and the corresponding weight values of the other factors obtained by the acquisition unit.

The functions of each functional module of the apparatus in the above-mentioned embodiment of the present specification can be realized through the steps of the above-mentioned method embodiment. Therefore, the specific working process of the apparatus provided in an embodiment of this specification is not repeated here.

An apparatus for optimizing a quality monitoring model for monitoring R&D quality provided by an embodiment of the present specification can greatly improve the accuracy of the optimized quality monitoring model.

The optimization apparatus for a quality monitoring model for monitoring R&D quality provided by an embodiment of the present specification may be a module or unit of the quality monitoring platform in FIG. 1 .

Corresponding to the above-mentioned monitoring method of R&D quality, an embodiment of this specification also provides a R&D quality monitoring device, as shown in FIG. 5 , the device may include:

The obtaining unit 502 is configured to obtain the respective values of several quality factors included in the quality monitoring model optimized by the research and development team after the current research and development stage of the research and development team ends. Among them, the quality monitoring model is used to monitor the R&D quality of the R&D team in the process of developing the software, which is optimized by the method shown in FIG. 2 .

The input and output unit 504 is configured to input the respective values of several quality factors obtained by the obtaining unit 502 into the quality monitoring model, and output the corresponding score value.

The evaluating unit 506 is configured to evaluate whether there is an abnormality in the research and development quality of the current research and development stage based on at least the score value output by the input and output unit 504 .

The evaluation unit 506 can be specifically used for:

Based on a predefined evaluation rule, it is evaluated whether the R&D quality of the current R&D stage is abnormal, and the evaluation rule at least indicates that the value of an important factor among several quality factors needs to exceed a corresponding threshold.

The sending unit 508 is configured to send a notification message that the research and development quality of the current research and development stage is abnormal according to a predetermined notification method if the assessment unit 506 assesses that there is an abnormality.

Optionally, the device may also include:

A selection unit (not shown in the figure) is used to select a quality factor whose corresponding value is lower than the corresponding threshold from several quality factors.

The adjustment unit (not shown in the figure) is used to adjust the evaluation rule based on the quality factor selected by the selection unit and the corresponding threshold value.

The functions of each functional module of the apparatus in the above-mentioned embodiment of the present specification can be realized through the steps of the above-mentioned method embodiment. Therefore, the specific working process of the apparatus provided in an embodiment of this specification is not repeated here.

The R&D quality monitoring device provided by an embodiment of this specification can accurately monitor the R&D quality of the R&D team in each R&D stage in the process of developing software, thereby improving the software quality of the software developed by the R&D team.

The R&D quality monitoring device provided by an embodiment of the present specification may be a module or unit of the quality monitoring platform in FIG. 1 .

On the other hand, the embodiments of this specification provide a computer-readable storage medium on which a computer program is stored, and when the computer program is executed in a computer, causes the computer to execute the method shown in FIG. 2 or FIG. 3 .

On the other hand, an embodiment of the present specification provides a computing device, including a memory and a processor, the memory stores executable codes, and when the processor executes the executable codes, the embodiment shown in FIG. 2 or FIG. 3 is implemented. method shown.

Each embodiment in this specification is described in a progressive manner, and the same and similar parts between the various embodiments may be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the device embodiments, since they are basically similar to the method embodiments, the description is relatively simple, and reference may be made to the partial descriptions of the method embodiments for related parts.

The steps of the method or algorithm described in conjunction with the disclosure of this specification may be implemented in a hardware manner, or may be implemented in a manner in which a processor executes software instructions. The software instructions can be composed of corresponding software modules, and the software modules can be stored in RAM memory, flash memory, ROM memory, EPROM memory, EEPROM memory, registers, hard disk, removable hard disk, CD-ROM, or any other form of storage known in the art in the medium. An exemplary storage medium is coupled to the processor, such that the processor can read information from, and write information to, the storage medium. Of course, the storage medium can also be an integral part of the processor. The processor and storage medium may reside in an ASIC. Alternatively, the ASIC may be located in a server. Of course, the processor and storage medium may also exist in the server as discrete components.

Those skilled in the art should appreciate that, in one or more of the above examples, the functions described in the present invention may be implemented in hardware, software, firmware, or any combination thereof. When implemented in software, the functions may be stored on or transmitted over as one or more instructions or code on a computer-readable medium. Computer-readable media includes both computer storage media and communication media including any medium that facilitates transfer of a computer program from one place to another. A storage medium can be any available medium that can be accessed by a general purpose or special purpose computer.

The foregoing describes specific embodiments of the present specification. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recited in the claims can be performed in an order different from that in the embodiments and still achieve desirable results. Additionally, the processes depicted in the figures do not necessarily require the particular order shown, or sequential order, to achieve desirable results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

The specific embodiments described above further describe the purpose, technical solutions and beneficial effects of this specification in detail. It should be understood that the above descriptions are only specific implementations of this specification, and are not intended to limit the scope of this specification. The protection scope, any modification, equivalent replacement, improvement, etc. made on the basis of the technical solutions in this specification shall be included within the protection scope of this specification.

Claims (20)

1. A method for optimizing a quality monitoring model for monitoring R&D quality, the method comprising: Based on the distribution curve corresponding to the monitoring index of software quality in the control chart and the control limit, it is judged whether the software quality of the released software of each R&D team is abnormal; the distribution curve is based on the statistics of each R&D team for the monitoring index. The obtained multiple statistical values are drawn; If the software quality of the released software of any first R&D team is abnormal, select the target factor that affects the monitoring index from several quality factors included in the quality monitoring model preconfigured by the first R&D team; The quality monitoring model is used to monitor the research and development quality of the first research and development team in the software development process; the quality monitoring model is determined based on the weighted combination result of the several quality factors; At least the weight value set by the first R&D team for the target factor is adjusted to optimize the quality monitoring model preconfigured by the first R&D team. 2. The method of claim 1, the distribution curve comprising a plurality of data points, wherein each data point corresponds to a research and development team of the research and development teams and a statistic of the plurality of statistical values value; the control limit includes an upper control limit and a lower control limit; the upper control limit and the lower control limit constitute a control area; Based on the distribution curves and control limits corresponding to the monitoring indicators of software quality in the control chart, it is determined whether the software quality of the released software of each R&D team is abnormal, including: Judging whether there are target data points located outside the control area in the distribution curve corresponding to the monitoring index; If so, it is determined that there is an abnormality in the software quality of the released software of the R&D team corresponding to the target data point. 3. The method according to claim 2, wherein at least adjusting the weight value set by the first R&D team for the target factor, comprising: From the distribution curve corresponding to the monitoring index, select other data points except the target data point; A number of reference R&D teams are determined from the respective R&D teams corresponding to the other data points; wherein, the target factors are included in the quality factors that affect the monitoring indicators set by each reference R&D team; Based on the weight values set by each reference R&D team for the target factor, the weight value set by the first R&D team for the target factor is adjusted. 4. The method according to claim 3, wherein adjusting the weight value set by the first R&D team for the target factor based on the weight value set by each reference R&D team for the target factor, comprising: : A target R&D team is selected from the reference R&D teams; wherein, the weight value set by the target R&D team for the target factor is not lower than the weight value set by the first R&D team for the target factor ; From the weight values set by the target R&D team for the target factor, select the maximum weight value and the minimum weight value; Based on the maximum weight value and the minimum weight value, the weight value set by the first research and development team for the target factor is adjusted. 5. The method of claim 3, further comprising: For each reference R&D team in the several reference R&D teams, select other factors other than the target factor from the quality factors set by the reference R&D team that affect the monitoring index; Obtain the weight values set by the reference R&D team for the other factors; Based on the other factors and the weight values corresponding to the other factors, the quality monitoring model preconfigured by the first research and development team is optimized. 6. The method according to claim 1, wherein the monitoring indicators include any one of the following: a release rollback rate and a number of online failures; the quality factors include unit test coverage, functional test coverage, code specification, and Several of the number of black and white box security scans. 7. A method for monitoring R&D quality, comprising: After the current R&D stage of the R&D team ends, the respective values of several quality factors included in the quality monitoring model optimized by the R&D team are obtained; wherein, the quality monitoring model is used for the R&D team in the process of developing software. R&D quality is monitored, which is optimized by the method of any one of claims 1-6; Input the respective values of the several quality factors into the quality monitoring model, and output the corresponding score values; Assess whether there is any abnormality in the quality of research and development at the current research and development stage, based at least on the score value; If there is an abnormality, according to a predetermined notification method, a notification message that the research and development quality of the current research and development stage is abnormal is sent to the predetermined person. 8. The method according to claim 7, the evaluation of whether there is abnormality in the research and development quality of the current research and development stage, comprising: Based on a predefined evaluation rule, it is evaluated whether the R&D quality of the current R&D stage is abnormal; the evaluation rule at least indicates that the value of the important factor among the several quality factors needs to exceed the corresponding threshold. 9. The method of claim 8, further comprising: selecting a quality factor whose corresponding value is lower than the corresponding threshold from the several quality factors; The evaluation rule is adjusted based on the selected quality factor and the corresponding threshold. 10. An optimization device for a quality monitoring model for monitoring R&D quality, the device comprising: The judgment unit is used for judging whether the software quality of the released software of each R&D team is abnormal based on the distribution curve corresponding to the monitoring index of the software quality in the control chart and the control limit; It is drawn from the multiple statistical values obtained from the statistics of the monitoring indicators; A selection unit, configured to select from several quality factors included in the quality monitoring model preconfigured by the first R&D team if the determination unit determines that the software quality of the released software of any first R&D team is abnormal the target factor affecting the monitoring index; the quality monitoring model is used to monitor the R&D quality of the first R&D team in the process of developing the software; the quality monitoring model is based on the weighted combination result of the several quality factors to determine; The adjustment unit is configured to adjust at least the weight value set by the first R&D team for the target factor selected by the selection unit, so as to realize the optimization of the quality monitoring model pre-configured by the first R&D team. 11. The apparatus of claim 10, the distribution curve comprising a plurality of data points, wherein each data point corresponds to a research and development team of the research and development teams and a statistic of the plurality of statistical values value; the control limit includes an upper control limit and a lower control limit; the upper control limit and the lower control limit constitute a control area; The judging unit is specifically used for: Judging whether there are target data points located outside the control area in the distribution curve corresponding to the monitoring index; If so, it is determined that there is an abnormality in the software quality of the released software of the R&D team corresponding to the target data point. 12. The device according to claim 11, wherein the adjustment unit is specifically used for: From the distribution curve corresponding to the monitoring index, select other data points except the target data point; A number of reference R&D teams are determined from the respective R&D teams corresponding to the other data points; wherein, the target factors are included in the quality factors that affect the monitoring indicators set by each reference R&D team; Based on the weight values set by each reference R&D team for the target factor, the weight value set by the first R&D team for the target factor is adjusted. 13. The device according to claim 12, wherein the adjustment unit is specifically used for: A target R&D team is selected from the reference R&D teams; wherein, the weight value set by the target R&D team for the target factor is not lower than the weight value set by the first R&D team for the target factor ; From the weight values set by the target R&D team for the target factor, select the maximum weight value and the minimum weight value; Based on the maximum weight value and the minimum weight value, the weight value set by the first research and development team for the target factor is adjusted. 14. The apparatus according to claim 12, further comprising: an acquisition unit and an optimization unit; The selection unit is further configured to, for each reference R&D team in the several reference R&D teams, select a quality factor other than the target factor from the quality factors set by the reference R&D team that affect the monitoring index. other factors; The obtaining unit is used to obtain the weight values set by the reference R&D team for the other factors selected by the selection unit; The optimization unit is configured to optimize the quality monitoring model preconfigured by the first R&D team based on the other factors selected by the selection unit and the weight values corresponding to the other factors obtained by the acquisition unit. 15. The apparatus according to claim 10, wherein the monitoring indicators comprise any one of the following: release rollback rate and number of online failures; the quality factor comprises unit test coverage, functional test coverage, code specification, and Several of the number of black and white box security scans. 16. A monitoring device for R&D quality, comprising: The obtaining unit is used to obtain the respective values of several quality factors included in the quality monitoring model optimized by the research and development team after the current research and development stage of the research and development team is completed; wherein, the quality monitoring model is used for the research and development team in the research and development team. Monitoring the quality of research and development in the process of developing software, which is optimized by the method of any one of claims 1-6; an input-output unit, configured to input the respective values of the several quality factors obtained by the obtaining unit into the quality monitoring model, and output corresponding score values; An evaluation unit, configured to evaluate whether there is an abnormality in the research and development quality of the current research and development stage based on at least the score value output by the input and output unit; The sending unit is configured to send a notification message that the research and development quality of the current research and development stage is abnormal according to a predetermined notification method if the assessment by the assessment unit is abnormal. 17. The apparatus according to claim 16, the evaluation unit is specifically used for: Based on a predefined evaluation rule, it is evaluated whether the R&D quality of the current R&D stage is abnormal; the evaluation rule at least indicates that the value of the important factor among the several quality factors needs to exceed the corresponding threshold. 18. The apparatus of claim 17, further comprising: a selection unit, configured to select a quality factor whose corresponding value is lower than the corresponding threshold from the several quality factors; An adjustment unit, configured to adjust the evaluation rule based on the quality factor selected by the selection unit and the corresponding threshold. 19. A computer-readable storage medium having stored thereon a computer program which, when executed in a computer, causes the computer to perform the method of any one of claims 1-6. 20. A computing device comprising a memory and a processor, wherein executable code is stored in the memory, and when the processor executes the executable code, the method of any one of claims 1-6 is implemented.

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