JP6975086B2 - Quality evaluation method and quality evaluation equipment - Google Patents

Description

The present disclosure relates to a quality evaluation method and a quality evaluation device for infrastructure infrastructure.

In recent years, a system has been developed that can predict the quality of finished products from the entered manufacturing conditions by accumulating data on past manufacturing results at the manufacturing site and statistically analyzing the relationship between manufacturing conditions and the quality of finished products. ing.

For example, Patent Document 1 discloses a predictive formula creating device that predicts future manufacturing results with high accuracy when control when manufacturing conditions are out of the control range or quality design at the time of new product development is performed. Has been done.

Further, Patent Document 2 discloses "a device capable of quality evaluation (evaluation of bug convergence time) by comparing with a quality index of a development target system (program group) which is a development target of a project".

In addition to the above, at the application software development site, the quality of the software is quantitatively evaluated based on the number of source code lines of the developed application software.

Japanese Unexamined Patent Publication No. 2008-11288 Japanese Unexamined Patent Publication No. 2014-174895

By the way, the above-mentioned quality evaluations are all quality evaluations for finished products of software alone or hardware alone, but the services provided by companies to customers are not limited to single finished products. For example, a company that provides IT solutions connects multiple hardware such as servers based on customer requests, and also provides an infrastructure infrastructure construction service that prepares IT equipment so that software can run on the hardware. It is offered as.

In the above infrastructure construction, there has been no index that quantitatively indicates the scale of project deliverables, such as the number of source code lines at the time of application software development. Therefore, quantitatively evaluate whether the quality evaluation items such as the number of checklists to be checked when testing the prepared IT equipment or the number of bugs to be extracted during the test are within an appropriate range compared to the scale of the IT equipment. The method was not established. In other words, until now, it has not been possible to accurately evaluate the quality of the IT equipment construction process.

Similarly, the amount of description in the design document created in the design process of infrastructure construction is also an item whose value changes according to the scale of the infrastructure to be constructed, but the amount of description has not been quantitatively evaluated. The only evaluation method for the amount of description in the design document is the quality evaluation method that guarantees the quality of the design process based on the fact that all the reviews on the design document have been carried out and all the points of the review have been incorporated into the finished product. There wasn't. That is, the quality evaluation of conventional infrastructure projects was probably qualitative.

This disclosure has been made in view of the above points, and provides a technique for quantitatively and accurately evaluating the quality of deliverables in a project for constructing an infrastructure infrastructure.

In order to solve the above problems, it is a quality evaluation method for evaluating the quality of a project for constructing an infrastructure infrastructure by a computer, and the actual value of a quality evaluation item which is an index for evaluating the quality of the infrastructure infrastructure by the computer. , The step of acquiring the data set of the actual values of two or more construction items of the infrastructure infrastructure, and the computer performs regression analysis on the data set, and the quality evaluation item is used as the objective variable. The step of determining the regression coefficient of the regression equation using the construction item as an explanatory variable and defining the calculation formula of the construction scale indicating the scale of the infrastructure infrastructure using the determined regression coefficient, and the computer are the above two. The step of acquiring the project basic information including the planned construction number of the above construction items, and the computer subdivides each of the acquired construction planned numbers into product categories, and weights each of the subdivisions with a coefficient for each product category. A step of calculating the added sum, multiplying the calculated sum by the regression coefficient corresponding to the construction item, and adding the value over all the construction items as the construction scale. Provides a quality assessment method to perform.

In addition, a data set of the actual value of the quality evaluation item, which is an index for evaluating the quality of the infrastructure to be built, and the actual value of two or more construction items of the infrastructure, is acquired, and the data set is used. A construction scale definition that performs regression analysis, determines the regression coefficient of the regression equation with the quality evaluation item as the objective variable and the construction item as the explanatory variable, and defines the calculation formula of the construction scale indicating the scale of the infrastructure infrastructure. The sum of the department and the project basic information including the planned number of construction items of the two or more construction items is acquired, the planned construction number is subdivided by product category, and each subdivided is weighted by the coefficient for each product category. Is calculated, and the value obtained by multiplying the calculated sum by the regression coefficient corresponding to the construction item is added over all the construction items, and the value is calculated as the construction scale. Provide a quality evaluation device to be equipped.

According to the present disclosure, the quality of deliverables can be quantitatively and accurately evaluated in a project for constructing an infrastructure infrastructure. Issues, configurations and effects other than the above will be clarified by the following description of embodiments.

It is a block diagram which shows the schematic structure of the quality evaluation apparatus which concerns on this Example. This is an example of a matrix in which the results of factor analysis are described. It is a figure which shows an example of the data structure of the construction scale calculation logic information. It is a figure which shows an example of the data structure of product category information. It is a figure which shows an example of the data structure of product information. It is a figure which shows an example of the data structure of the project basic information (server construction). It is a figure which shows an example of the data structure of the project basic information (network construction). It is a figure which shows an example of the data structure of quality index information. It is a figure which shows the relationship between the server construction scale (Cs), and the number of pages of a basic design document. It is a figure which shows an example of the data structure of quality data information. It is a figure which shows an example of the infrastructure infrastructure quality control report output by a quality evaluation department. It is a flowchart which roughly showed the process from the factor analysis of the performance data to the output of the report of the evaluation result by the quality evaluation apparatus. It is a flowchart of the process concerning the definition of the construction scale and the definition of the quality index executed by the construction scale definition unit. It is a flowchart which shows the quality target value calculation process executed by a quality target setting part. It is a flowchart which shows the quality evaluation process which a quality evaluation part executes.

[Overview]
The quality evaluation device of the present disclosure accumulates data on the evaluation metrics of the infrastructure infrastructure construction project such as the number of pages of the basic design document and the number of reviews pointed out when constructing the infrastructure infrastructure, and statistically analyzes the accumulated data to analyze the project. Determine the calculation formula of "construction scale" which is a value indicating the scale.

The quality evaluation device calculates the construction scale by inputting the number of products, the number of servers, etc. of the infrastructure to be constructed using the above-mentioned construction scale calculation formula. Furthermore, the quality evaluation device calculates target values such as the number of pages of the basic design document and the number of points to be reviewed by using the construction scale.

By comparing the obtained target values with the actual values such as the actual number of pages of the basic design document and the number of reviews pointed out that became clear in the process of constructing the infrastructure infrastructure, the user can compare the scale of the infrastructure infrastructure, for example. It is possible to make a quantitative quality evaluation such as whether the number of reviews pointed out is excessive. The user can improve the accuracy of the quality evaluation of the product by using the quality evaluation device of the present disclosure.

Hereinafter, examples of the present disclosure will be described with reference to the drawings. The embodiment of the present disclosure is not limited to the embodiment described later, and various modifications can be made within the scope of the technical idea. Further, the corresponding parts of the drawings used in the description of each embodiment described later are designated by the same reference numerals, and duplicate description will be omitted.

Further, in the present specification, the infrastructure infrastructure construction means, for example, setting the hardware (server, storage device, network device etc.) and software (OS, middleware etc.) based on the design document, and setting the system. Refers to the work of assembling. The construction scale includes, for example, a server construction scale (Cs (Construction Scale)) for starting up server devices and installing an OS, and a network construction scale (Ns (Network Construction Scale)) for connecting servers and clients. be.

[Configuration of quality evaluation device]
FIG. 1 is a block diagram showing a schematic configuration of the quality evaluation device 1 according to the present embodiment. The quality evaluation device 1 includes a control unit 100, a recording unit 110, an input device (not shown) such as a keyboard, and an output device (not shown) such as a printer. The control unit 100 is, for example, a CPU (Central Processing Unit), and the recording unit 110 is, for example, a RAM (Random Access Memory) and an SSD (Solid State Drive).

By executing the program recorded in the recording unit 110, the control unit 100 functions as a construction scale definition unit 101, a quality target setting unit 102, and a quality evaluation unit 103, which will be described later.

In addition to the above-mentioned program, the recording unit 110 includes quality data information 111, construction scale calculation logic information 112, product category information 113, product information 114, project basic information (server construction) 115, and project basic information (network construction) 116. And the quality index information 117 is stored. Hereinafter, each process executed by the control unit 100 will be described.

The construction scale definition unit 101 performs factor analysis on a set of actual values of a plurality of quality evaluation items and actual values of a plurality of construction items stored in the quality data information 111. Here, the actual value of the quality evaluation item refers to, for example, the number of pages of the basic design document of the project, the number of checklists, and the like. The actual value of the construction item refers to, for example, the number of servers actually constructed and the number of types of installed OS (Linux (registered trademark), Windows (registered trademark), etc.). In addition, abnormal data such as actual values of projects that clearly failed are excluded from the set of actual values for performing factor analysis.

The above factor analysis is carried out to understand the correlation between the infrastructure construction items (number of servers, number of routers, number of products) and quality evaluation items. The construction scale definition unit 101 selects, for example, a quality evaluation item from a set of variables whose correlation coefficient is higher than a predetermined value. The quality evaluation items selected in this way are considered to be parameters that well represent the scale of the infrastructure to be constructed. The objective variable may be selected by the user.

FIG. 2 is an example of a matrix in which the results of factor analysis are recorded. In FIG. 2, the number of servers, the number of products, the number of pages of the basic design document, the number of integration test items, and the correlation coefficient between the number of integration defects are shown. The number of servers is, for example, the number of servers included in the infrastructure to be constructed. The number of products is, for example, the number of service products provided by an IT solution company such as OS settings, mailer software settings, and database construction. The basic design document is, for example, a rough design document of the infrastructure to be constructed. The number of integration test items is, for example, the number of test items when a server, a client, or the like is integrated. The number of defective couplings is, for example, the number of defective couplings that occurred when the above-mentioned integration test was performed. In FIG. 2, the number of valid data 13 indicates the number of input project data.

In FIG. 2, the cells having a high correlation coefficient are shaded. In the example shown in FIG. 2, there is a high positive correlation between the number of products, the number of pages of the basic design document, and the number of poor couplings. In the following, the case where the number of pages of the basic design document is selected as a quality evaluation item to replace the scale of the infrastructure scale will be described as an example. Although it is possible to use the number of poor couplings as a quality evaluation item that substitutes for the scale of the infrastructure scale, the objective variable is the number of pages of the basic design document that is determined in the upstream process rather than the number of defective couplings counted in the downstream process. It is easier to accurately reflect the scale of infrastructure construction because the values are less likely to fluctuate for each project.

The construction scale definition unit 101 executes a multiple regression analysis for determining the following equation 1 with the number of pages of the basic design document as the objective variable and the construction items (the number of servers and the number of products) as the explanatory variables. Further, the construction scale definition unit 101 determines the linear equation of the server construction scale by using the obtained regression coefficient.
(Equation 1)
(Number of pages of basic design document = α x number of servers + β x number of products + γ)
Since the number of pages of the basic design document is 0 when no infrastructure is constructed, γ = 0 is set here. Further, the multiple regression analysis is executed for a data set classified by a construction category such as a backbone server construction or an information server construction. (Therefore, two types of server construction scale are defined, the core server construction scale and the information system server construction scale, but they are simply abbreviated as the server construction scale below.) The construction scale definition unit 101 is determined by multiple regression analysis. The regression coefficients α'and β'of the server construction scale are stored in the construction scale calculation logic information 112 of the recording unit 110.

FIG. 3 is a diagram showing an example of the data structure of the construction scale calculation logic information 112. The construction scale calculation logic information 112 has a construction category 1701, a parameter name 1702 associated with the construction category, and a coefficient 1703.

The construction category 1701 indicates a category of server construction or network construction, and for example, a plurality of values such as a backbone server construction, an information system server construction, and a network construction are stored.

As the parameter name 1702, values such as the number of products 1711, the number of servers 1712, the number of device types 1713, and the number of devices 1714 are stored. When defining the server construction scale (Cs) and network construction scale (Ns) by factor analysis and multiple regression analysis, it was judged that it is appropriate to add quality evaluation items other than the above to the right side of equations 1 and 2. In this case, quality evaluation items other than the above may be included in the possible values of the parameter name 1702.

The construction scale definition unit 101 calculates the regression coefficient for each construction category 1701 and stores it in the item of the coefficient 1703. The value of the coefficient 1703 stored in the construction scale calculation logic information 112 may be updated when the project of the infrastructure infrastructure is executed and the actual data is accumulated.

The inventors have found that if the server construction scale is defined by the following equation 2 using the regression coefficients α'and β'determined by the multiple regression analysis, the scale of the infrastructure to be constructed can be well expressed.
(Equation 2)
(Server construction scale (Cs) = α'x Σ _k (coefficient of product category k x number of servers in product category k) + β'x MAX (coefficient of product category k) x number of products)

That is, the construction scale definition unit 101 divides each construction item into product categories, calculates a sum weighted by a coefficient for each product category, and multiplies the calculated sum by a regression coefficient corresponding to the construction item. The value obtained by adding the above values over all the construction items is calculated as the construction scale indicating the scale of the infrastructure infrastructure. In the second term on the right side of Equation 2, the weighting coefficient is MAX (coefficient by product category), and all products have the same weight, so the result is whether or not the construction items (number of products) are subdivided. does not change.

In Equation 2 above, the product category refers to the type of server to be built, such as the OS to be installed, mail, AD (Active Directory), cluster, monitoring, and database, and each product category has a corresponding coefficient in advance for the user. Registered by.

In Equation 2, the multiplication factor differs for each product category because, for example, even in a project for constructing the same number of servers, the number of pages of the basic design document and the number of checklists differ for each product category. For example, AD servers and mail servers tend to have a large coefficient, and servers for remote access tend to have a small coefficient.

FIG. 4 is a diagram showing an example of the data structure of the product category information 113. The product category information 113 has a product category 1301 and a coefficient for each product category 1302. Product category 1301 is an item that defines a product category. Specific examples of product categories are as described above.

The product category coefficient 1302 defines a coefficient to be multiplied by the product category, which is read when calculating the server construction scale (Cs) or the network construction scale (Ns). The coefficient 1302 for each product category is updated, for example, when an infrastructure project is executed and actual data is accumulated.

FIG. 5 is a diagram showing an example of the data structure of the product information 114. The product information 114 has a product category 1401 and a product name 1402. As described above, the product category 1401 is an item that defines a product category, and stores data such as a monitoring server and a mail server. The product name 1402 is an item that defines the name of the product itself. For example, if there are multiple types of mail software in a product category called a mail server and each mail software has a different product name, the data of the product name of each mail software is stored.

Similarly, the construction scale definition unit 101 performs a multiple regression analysis for determining the regression coefficient of the following equation 3 with the number of pages of the basic design document as the objective variable and the construction items (number of devices and number of device types) as explanatory variables. Run. The construction scale definition unit 101 determines a linear equation of the network construction scale (Ns) using the obtained regression coefficient.
(Equation 3)
(Number of pages of basic design document = α x number of devices + β x number of device types + γ)
Since the number of pages of the basic design document is 0 when no infrastructure is constructed, setting γ = 0 is the same as above. In addition, the multiple regression analysis is performed on a data set whose construction category is classified as network construction. The construction scale definition unit 101 stores the regression coefficients α'and β'of the network construction scale (Ns) determined by the multiple regression analysis in the construction scale calculation logic information 112 of the recording unit 110.

Similarly, if the network construction scale is defined by the following equation 4 using the regression coefficients α'and β'determined by the multiple regression analysis, it can be effectively used as an index to replace the scale of the infrastructure to be constructed.
(Equation 4)
(Network construction scale (Ns) = α'x Σ _k (coefficient of product category k x number of devices of product category k) + β'x MAX (coefficient by product category) x number of device types)
Subsequently, the function of the quality target setting unit 102 will be described.

The quality target setting unit 102 first acquires the project basic information 120 input by the project manager or the quality control person in charge. The project basic information 120 acquired by the quality target setting unit 102 includes the number of servers 121 and the number of products 122 of the infrastructure infrastructure to be constructed, the number of devices, the number of device types, and the product categories of each server, product, and device.

Further, the quality target setting unit 102 acquires the product category information 113, the product information 114, and the construction scale calculation logic information 112, and calculates the server construction scale (Cs) and the network construction scale (Ns). The quality target setting unit 102 stores the calculated server construction scale (Cs) and network construction scale (Ns) in the project basic information (server construction) 115 and the project basic information (network construction) 116 in the recording unit 110, respectively. do. The data structures of the project basic information (server construction) 115 and the project basic information (network construction) 116 will be described below.

[Data structure of project basic information (server construction)]
FIG. 6 is a diagram showing an example of the data structure of the project basic information (server construction) 115. The project basic information (server construction) 115 includes data of the project name 1101, the definition item 1102 associated with each project, and the definition content 1103.

The project name of the infrastructure to be constructed is stored as data in the project name 1101, and the data is input, for example, by a quality control person via a keyboard connected to the quality evaluation device 1.

The definition item 1102 includes the construction category 1111, the number of servers 1112, the number of products 1113, and the server construction scale (Cs) 1114, which are parameters that characterize the infrastructure to be constructed.

The construction category 1111 indicates a server construction category, and can take a plurality of values such as a backbone system or an information system. For example, when the construction category 1111 of the server to be constructed is different, the target value of the quality evaluation is also different, so that the quality index value described later is defined for each construction category 1111.

The number of servers 1112 defines the number of servers to be built in the project. Since there is no big difference in the number of processes for constructing the infrastructure infrastructure, the number of servers 1112 is defined, for example, by adding up the numbers without distinguishing whether the server type is a physical server or a virtual server.

The number of products 1113 defines the number of products used in the project. The number of products is, for example, a total value of the number of types of OS installed on the server, the number of types of mail software, and the like.

The server construction scale (Cs) 1114 defines the server construction scale (Cs) of the project. In this embodiment, the server construction scale (Cs) is calculated by the quality target setting unit 102 based on the construction scale calculation logic information 112, the number of servers 1112, and the number of products 1113.

As described above, the project basic information (server construction) 115 stores the information necessary for calculating the server construction scale (Cs) and the calculated value of the server construction scale (Cs) itself.

[Data structure of project basic information (network construction)]
FIG. 7 is a diagram showing an example of the data structure of the project basic information (network construction) 116. The project basic information (network construction) 116 includes data of the project name 1201, the definition item 1202 associated with each project, and the definition content 1203. The definition of each of these items is the same as the definition made in the explanation of the project basic information (server construction) 115.

Definition item 1202 includes the number of devices 1211, the number of device types 1212, and the network construction scale (Ns) 1213, which are parameters that characterize the infrastructure to be constructed.

The number of devices 1211 defines the number of network devices to be built in the project. The number of devices 1211 is, for example, the number of routers.

The device type number 1212 defines the number of network device types used in the project.

The network construction scale (Ns) 1213 defines the network construction scale (Ns) of the project. As described above, the network construction scale (Ns) is calculated by the quality target setting unit 102 based on the construction scale calculation logic information 112, the number of devices 1211 and the number of device types 1212. Subsequently, the quality index information calculated by the quality target setting unit 102 will be described.

[Data structure of quality index information]
FIG. 8 is a diagram showing an example of the data structure of the quality index information 117. The quality index information 117 has a construction category 1601, an index name 1602 associated with the construction category, an index value (From) 1603, and an index value (to) 1604.

As described above, the construction category 1601 indicates a server construction category, and can take a plurality of values such as a backbone system and an information system. As shown in FIG. 8, the quality index value is defined for each construction category 1601.

The index name 1602 includes the basic design document writing density 1611, the basic design document indication density 1612, the unit test checklist density 1613, the unit test defect rate 1614, the integration test checklist density 1615, and the integration test defect rate 1616.

The basic design document writing density 1611 is an index obtained by dividing the number of pages of the basic design document by the calculated construction scale. The basic design document indication density 1612 is an index obtained by examining the basic design document before starting the construction of the server and dividing the number of reviews generated at that time by the construction scale. The unit test checklist density 1613 is an index obtained by dividing the number of check items described in the unit test checklist performed when constructing a single server by the construction scale. The unit test failure rate 1614 is an index obtained by dividing the number of tests to be performed when constructing the unit server by the construction scale. The integration test checklist density 1615 is an index obtained by dividing the number of check items described in the test checklist performed when combining a plurality of servers by the construction scale. The integration test defect rate 1616 is an index obtained by dividing the number of defects generated when the check items described in the above integration checklist are performed by the construction scale.

In the above description, when "dividing each value by the construction scale", the value of the construction scale determined for each project is used as the divisor. Therefore, in the case of a server construction project, the server construction scale (Cs) is a divisor, and in the case of a network construction project, the network construction scale (Ns) is a divisor. Subsequently, a method for determining the index value (From) and the index value (to) will be described.

The quality target setting unit 102 averages each index obtained for each project over a plurality of projects. That is, the average value between projects is calculated for each index. The quality target setting unit 102 sets the value deviating downward by a predetermined ratio from the calculated average value as the lower limit value (index value (From)) of the index, and sets the value deviating upward by a predetermined ratio from the average value as the index. It is stored in the table of quality index information 117 as an upper limit value (index value (to)).

As a specific example, when the average value of the basic design document writing density is "55", "44", which is 20% lower than the average value, is set as the lower limit of the basic design document writing density, and is 20% from the average value. A high "66" is set as the upper limit of the basic design document writing density.

The quality target setting unit 102 sets the lower limit of the target value (target value (From)) of the project by multiplying the index value (From) determined as described above by the construction scale calculated based on the project basic information. decide. Similarly, the quality target setting unit 102 determines the upper limit (target value (to)) of the target value of the project by multiplying the index value (to) by the construction scale calculated based on the project basic information. As in the case of factor analysis, the above calculation excludes abnormal values from the set of molecular values. In addition, the index value is updated regularly as the actual data is accumulated. The quality target setting unit 102 stores the determined target value (From) and target value (to) in the quality data information 111.

In the above description, the quality target setting unit 102 defines values deviating from the calculated average value by a predetermined ratio as the lower limit value and the upper limit value of the index, and the range of the quality index is the range of the target value of the quality evaluation item. Proportional. Hereinafter, how to determine the range of the quality index will be visually described with reference to FIG. 9.

FIG. 9 is a diagram showing the relationship between the server construction scale (Cs) and the number of pages of the basic design document. In FIG. 9, the horizontal axis shows the server construction scale (Cs), and the vertical axis shows the number of pages of the basic design document. In FIG. 9, the solid line indicates the lower limit of the target value of the number of pages of the basic design document, and the broken line indicates the upper limit of the target value of the number of pages of the basic design document. The lower limit value and the upper limit value of the quality index mean the slopes of the solid line and the broken line in FIG. 9, respectively. Therefore, the lower limit value and the upper limit value of the quality index may be set so that a large amount of data from which abnormal data is removed is included between the solid line and the broken line among the actual values of the number of pages of the basic design document in FIG. Recognize.

Subsequently, the quality evaluation unit 103 will be described. The quality evaluation unit 103 acquires quality performance information 123 such as design document page number 124, checklist number 125, and defect number 126, which is input by the project manager or the quality control person, and stores the data in the quality data information 111. ..

The quality evaluation unit 103 compares the target value and the actual value in the quality data information 111, and stores the comparison result in the quality data information 111. The quality evaluation unit 103 determines the degree of deviation between the actual value of the quality evaluation item and the numerical value in the range from the lower limit of the target value (target value (From)) to the upper limit of the target value (target value (to)). Evaluate the quality of the project that builds the infrastructure infrastructure based on it.

For example, when the actual value of the quality evaluation item is within the range from the target value (From) to the target value (to), the quality evaluation unit 103 evaluates that the quality evaluation item is ◯. On the other hand, the quality evaluation unit 103 determines that the quality evaluation item is Δ when the actual value of the quality evaluation item is lower than the target value (From) by a predetermined ratio or when the actual value is higher than the target value (to) by a predetermined ratio. evaluate. The reason is that, due to the nature of the quality evaluation items, it cannot be said that the quality is high regardless of whether the actual value is too small or too large. For example, in the case of the unit test defect rate 1614, if the actual value is less than the target value, there is a possibility that the product is delivered to the customer without sufficiently confirming the error. If the actual value is larger than the target value, it can be said that there is a problem in the method of proceeding with the project.

There are various evaluation methods of the quality evaluation unit 103, and the evaluation may be expressed numerically. The quality evaluation unit 103 also stores the evaluation result in the quality data information 111. The quality evaluation unit 103 outputs an infrastructure infrastructure quality control report 130 in which the evaluation is described. An example of the data structure of the quality data information 111 is shown below.

[Quality data information]
FIG. 10 is a diagram showing an example of the data structure of the quality data information 111. The quality data information 111 includes a project name 1501, a definition item 1502 associated with each project, a target value (From) 1503, a target value (to) 1504, an actual value 1505, and an evaluation 1506.

The definition item 1502 includes the number of pages of the basic design document 1511, the number of reviews pointed out 1512, the number of unit test checklists 1513, the number of unit test defects 1514, the number of integration test checklists 1515, the number of integration test defects 1516, and the like. Quality evaluation items may be added. The definitions of the respective terms described in the definition item 1502 are as described above.

For each definition item, the target value (From) 1503 stores the lower limit of the target value obtained by multiplying the server construction scale (Cs) or network construction scale (Ns) of the project by the lower limit of the quality index. do.

Similarly, the target value (To) 1504 stores the upper limit value of the target value obtained by multiplying the server construction scale (Cs) or the network construction scale (Ns) of the project by the upper limit value of the quality index.

Further, the actual value 1505 stores the quality actual information 123 input by the project manager or the quality control person in charge.

The evaluation 1506 stores the evaluation results of the quality evaluation items by the quality evaluation unit 103. It is desirable that the evaluation result data be visualized with symbols such as ○ and Δ, but the criteria may be changed as necessary. The infrastructure infrastructure quality control report will be explained below with reference to the figure.

[Infrastructure Infrastructure Quality Control Report]
FIG. 11 is a diagram showing an example of the infrastructure infrastructure quality control report 130 output by the quality evaluation unit 103. The infrastructure infrastructure quality control report 130 is composed of a project basic information input field 3081, a quality result input field 3082, and a quality evaluation field 3083.

In the project basic information input field 3081, the project name 3001 and various information associated with the project are defined. In the example shown in FIG. 11, the project name “test project” is displayed.

As various information associated with the project, the number of servers by product category is displayed. The columns for the number of servers by product category include, for example, host OS 3002, physical server (Windows) 3003, physical server (Linux) 3004, virtual server (Windows) 3005, virtual server (Linux) 3006, mail 3007, AD3008, cluster 3009, and so on. It has the item names of monitoring 3010 and other 3011, and the number of built servers in the production environment and the verification environment is displayed for each product category.

Further, at the right end of the project basic information input field 3081, there is a display field of the construction scale 3021, the number of products 3022, the total number of production servers 3023, and the total number of verification servers 3024.

When determining the server construction scale (Cs) using the above (Equation 2), multiply the number of production servers by product category by the coefficient for each product category recorded in the product category information 113, and add the total value. Multiply the regression coefficient recorded in the construction scale calculation logic information 112, and similarly, multiply the value obtained by multiplying the number of products 3022 by the maximum value of the coefficient for each product category by the regression coefficient, and display the total value in the column of the construction scale 3021. do.

The quality record input field 3082 has input items such as product category 3033 and target device / product name 3034, and quality record data for each process in the construction of the infrastructure infrastructure can be freely input.

Similarly, various quality evaluation items such as the basic design document (page) 3035, the number of reviews pointed out 3036, the defect rate 3037, the checklist (CL) number 3038, the defect number 3039, and the defect occurrence rate 3040 are also input items. It is preferable to input an automatic calculation formula or a function in advance for the evaluation metric entered by the calculation based on other input items such as the defect rate 3037 and the defect occurrence rate 3040. For example, these items are input by the quality control person when each process is completed, and the quality actual data recorded in the recording unit 110 is displayed.

In the quality evaluation column 3083, evaluation items such as description density, checklist density, and defect rate for the entire project can be output, and the information aggregated and / or evaluated by the quality evaluation unit 103 is output.

For the actual result 3051, the information obtained by dividing the total value of the input information of the quality actual result input unit by the server construction scale (Cs) or the network construction scale (Ns) is output. In the example shown in FIG. 11, the description density (pages / Cs) obtained by dividing the number of pages of the basic design document by the server construction scale (Cs) and the defect rate (cases / case /) obtained by dividing the number of review indications by the server construction scale (Cs). Cs) and are displayed.

For the index 3052, the content of the index value (range between the target value (From) and the target value (to)) recorded in the quality index information 117 is displayed. The same item as the item displayed in the actual result 3051 is displayed on the index 3052 so that the user can compare the actual value with the target value.

For the evaluation 3053, the evaluation content performed by the quality evaluation unit 103 in the quality evaluation process is output. The evaluation contents are displayed for each phase in the infrastructure construction process such as basic design, detailed design or construction, unit test, and integration test. In the example shown in FIG. 11, since the description density (page / Cs) of the basic design is within the range of the target value, the symbol ○ is displayed, and the defect rate (case / Cs) of the basic design is the lower limit of the target value “11”. Since it is lower than ", the symbol of △ is displayed.

As described above, the quality evaluation device 1 of this embodiment has the project basic information 120, the quality performance information 123, the accumulated quality index information 117, and the construction scale calculation logic information input by the project manager or the quality control person in charge. Aggregate and compare based on 112, and output the infrastructure infrastructure quality control report 130 for each process.

In the example shown in FIG. 11, the comparison result between the actual value and the target value by the quality evaluation unit 103 is displayed in the report, but the quality evaluation unit 103 is at the stage where the quality control person inputs the project basic information 120. Then, a report displaying the target value of the quality evaluation item may be output. In this case, the quality control person can proceed with the infrastructure project while referring to the target values described in the report. Further, the user of the quality evaluation device 1 can quantitatively grasp the scale of the project to be executed by referring to the construction scale. The quality target setting unit 102 may output a report at the stage of calculating the construction scale. In that case, the user can quantitatively grasp the scale of the project.
Subsequently, a flowchart of the process executed by the quality evaluation device 1 will be described.

[Flowchart of processing of quality evaluation device]
FIG. 12 is a flowchart schematically showing the process from the factor analysis of the actual data to the output of the evaluation result report by the quality evaluation device 1. Hereinafter, each process of the flowchart of FIG. 12 will be described.
(Step 1101)
First, the construction scale definition unit 101 performs statistical analysis (factor analysis and correlation analysis) on a set of quality actual data registered in the quality data information. The construction scale definition unit 101 defines quality evaluation items called server construction scale (Cs) and network construction scale (Ns) based on the results of statistical analysis, and further defines quality indicators using the values of these quality evaluation items. do. The construction scale definition unit 101 stores the server construction scale (Cs) and the network construction scale (Ns) in the construction scale calculation logic information 112, and stores the quality index in the quality index information 117.
(Step 1102)
Next, the quality target setting unit 102 defines the server construction scale (Cs) and the network construction scale (Ns) in step 201 based on the project basic information 120 input by the project manager or the quality control person at the time of project planning. ) Is calculated. The quality target setting unit 102 stores the server construction scale (Cs) in the project basic information (server construction) 115, and stores the network construction scale (Ns) in the project basic information (network construction) 116. Further, the quality target setting unit 102 calculates the quality target value based on the calculated information of the server construction scale (Cs), the network construction scale (Ns), and the quality index information 117, and stores the data in the quality data information 111. Store.
(Step 1103)
The quality evaluation unit 103 evaluates the quality for each process of the project by comparing the quality performance data input by the project manager or the quality control person with the quality target value calculated in step 1102.

[Flowchart that defines the construction scale]
FIG. 13 is a flowchart of a process in which the construction scale definition unit 101 defines the construction scale and the quality index. Hereinafter, each process of the flowchart of FIG. 13 will be described.
(Step 1201)
First, a data set of all definition items (number of basic design document pages, number of reviews pointed out, number of unit test checklists, number of unit test defects, number of integration test checks, number of integration test defects) registered in the quality data information 111. Perform a factor analysis on the data. The abnormal value is removed from the above data set.
(Step 1202)
Subsequently, as a result of factor analysis, the construction scale definition unit 101 determines a set of parameters having a higher correlation coefficient than a predetermined value among the construction items and quality evaluation items of the infrastructure infrastructure. In the following, the case where the correlation coefficient of the four items of the number of products, the number of servers, the number of pages of the basic design document, and the number of test defects is high will be described as an example.
(Step 1203)
Next, among the number of products and servers for which correlation was confirmed, the number of pages of the basic design document, and the number of test defects, the number of pages of the basic design document, which is a quality evaluation item in the upstream process, was selected as the objective variable, and the number of products and servers. Perform multiple regression analysis by selecting a number as the explanatory variable. The data set to be the target of multiple regression analysis is the data of the server infrastructure construction project. The construction scale definition unit 101 determines the regression coefficients α'and β'of the regression equation of the equation 1 described above, and stores them in the construction scale calculation logic information 112. Further, the construction scale definition unit 101 defines the server construction scale (Cs) by the following equation 2, and stores the definition equation in the construction scale calculation logic information 112.
(Equation 2)
(Server construction scale (Cs) = α'x Σ _k (coefficient of product category k x number of servers in product category k) + β'x MAX (coefficient by product category) x number of products)
(Step 1204)
Similarly, perform multiple regression analysis on the data of network infrastructure construction projects. The data set to be the target of multiple regression analysis is the data of the network infrastructure construction project. The construction scale definition unit 101 determines the regression coefficients α'and β'of the regression equation of the equation 3 described above, and stores them in the construction scale calculation logic information 112. Further, the construction scale definition unit 101 defines the network construction scale (Ns) by the following equation 4, and stores the definition equation in the construction scale calculation logic information 112.
(Equation 4)
(Network construction scale (Cs) = α'x Σ _k (coefficient of product category k x number of devices of product category k) + β'x MAX (coefficient by product category) x number of device types)

[Flowchart of quality target value calculation process]
FIG. 14 is a flowchart showing a quality target value calculation process executed by the quality target setting unit 102. Hereinafter, each process of the flowchart of FIG. 14 will be described.
(Step 1301)
First, the project basic information input by the project manager or the quality control person is stored in the project basic information (server construction) and the project basic information (network construction) for each construction category.
(Step 1302)
Next, based on the construction scale calculation logic information 112, the server construction scale (Cs) is calculated and stored in the project basic information (server construction), and the network construction scale (Ns) is calculated and the project basic information (network construction). ).
(Step 1303)
The quality target setting unit 102 calculates the quality target value of each process based on the server construction scale (Cs), the network construction scale (Ns), and the quality index information obtained in step 1302. The quality target value is stored in the quality data information 111 by calculating two values, a lower limit value (FROM) and an upper limit value (TO), for each quality evaluation item.
(Step 1304)
The quality target setting unit 102 summarizes the server construction scale (Cs) and the network construction scale (Ns) and the quality targets of each process stored in the quality data information 111 into an infrastructure infrastructure quality control report, and outputs a report. Project managers and quality control personnel review this report and recognize quality goals at the start of the project.

[Flowchart of quality evaluation process]
FIG. 15 is a flowchart showing a quality evaluation process executed by the quality evaluation unit 103. Hereinafter, each process of the flowchart of FIG. 15 will be described. In the flowchart of FIG. 15, S1401 is the start point of the loop, and S1406 is the return point of the loop. This quality evaluation process is carried out for each step, and the following steps 1402 to 1405 are repeatedly carried out.
(Step 1402)
When one step of infrastructure infrastructure construction is completed, the project manager or the quality control person inputs the quality performance data into the quality evaluation device and stores it in the quality data information 111.
(Step 1403)
Next, the quality evaluation unit 103 compares the upper limit value and the lower limit value of the quality target value calculated at the time of project planning with the quality actual data, and quantitatively evaluates the quality of the process. The quality evaluation unit 103 evaluates quality evaluation items with symbols such as ○ or △ depending on whether the actual value is within the range of the target value and how much the actual value deviates from the target value, and quality data. Store in information 111.
(Step 1404)
Similar to the infrastructure infrastructure quality control report output processing in step 1304 performed by the quality target setting unit 102, the server construction scale (Cs), the network construction scale (Ns), the quality target values of each process, and the quality actual data and Output a report with the evaluation results added.
(Step 1405)
The project manager or quality control person confirms the output report, evaluates the validity of the implementation contents of each process, and adds the opinion to the report. At this time, the report may be printed out on paper from a printer connected to the quality evaluation device 1, or may be displayed on a monitor connected to the quality evaluation device 1. The project manager or quality control personnel can enter the validity and views of the project execution results in the report, for example, via the keyboard.
The process of steps 1402 to 1405 is repeated until the final step is reached.

It should be noted that the present disclosure is not limited to the above-described embodiment, and includes various modifications. For example, the above-described embodiment has been described in detail in order to explain the present disclosure in an easy-to-understand manner, and is not necessarily limited to the one including all the configurations described. Further, it is possible to replace a part of the configuration of one embodiment with the configuration of another embodiment, and it is also possible to add the configuration of another embodiment to the configuration of one embodiment. Further, it is possible to add / delete / replace a part of the configuration of each embodiment with another configuration. Further, each of the above configurations, functions, processing units, processing means and the like may be realized by hardware by designing a part or all of them by, for example, an integrated circuit. Further, each of the above configurations, functions, and the like may be realized by software by the processor interpreting and executing a program that realizes each function. Information such as programs, tables, and files that realize each function can be placed in a memory, a recording device such as a hard disk or SSD, or a recording medium such as an IC card, SD card, or DVD.

1 ... Quality evaluation device 100 ... Control unit 110 ... Recording unit 111 ... Quality data information 112 ... Construction scale calculation logical information 113 ... Product category information 114 ... Product information 115 ... Project basic information (server construction)
116 ... Project basic information (network construction)
117 ... Quality index information 120 ... Project basic information 121 ... Number of servers 122 ... Number of products 123 ... Quality performance information 124 ... Number of design document pages 125 ... Number of checklists 126 ... Number of defects 130 ... Infrastructure infrastructure quality control report

Claims (6)

It is a quality evaluation method that evaluates the quality of a project that builds an infrastructure infrastructure using a computer.
A step in which the computer acquires a data set of an actual value of a quality evaluation item which is an index for evaluating the quality of the infrastructure infrastructure and an actual value of two or more construction items of the infrastructure infrastructure.
The computer performs regression analysis on the data set, determines the regression coefficient of the regression equation with the quality evaluation item as the objective variable and the construction item as the explanatory variable, and uses the determined regression coefficient. The step of defining the calculation formula of the construction scale indicating the scale of the infrastructure infrastructure, and
A step in which the computer acquires project basic information including the planned number of construction items of the two or more construction items.
The computer subdivides each acquired number of planned constructions by product category, calculates a sum obtained by weighting each of the subdivisions with a coefficient for each product category, and corresponds to the construction item with respect to the calculated sum. The step of calculating the value obtained by multiplying the regression coefficient by the value obtained by adding the values over all the construction items as the construction scale, and
Quality evaluation method to perform. In the quality evaluation method according to claim 1,
The computer calculates a value obtained by averaging the actual value of the quality evaluation item divided by the construction scale on the data set, and specifies a lower limit value and an upper limit value in a predetermined range including the averaged value. Steps and
A step in which the computer determines the lower limit value and the upper limit value of the target value of the quality evaluation item by multiplying the lower limit value and the upper limit value by the construction scale calculated based on the project basic information.
Including further quality evaluation methods. In the quality evaluation method according to claim 2,
The step that the computer acquires the actual data of the quality evaluation items obtained as a result of constructing the infrastructure, and
A step in which the computer evaluates the quality of the infrastructure infrastructure project based on the degree of deviation between the actual data of the quality evaluation item and the numerical value in the range from the lower limit value of the target value to the upper limit value of the target value. ,
Including further quality evaluation methods. In the quality evaluation method according to claim 1,
The computer performs factor analysis on a set of actual values of a plurality of preliminary quality evaluation items and actual values of a plurality of preliminary construction items, and performs factor analysis on the quality evaluation items according to claim 1 and claim 1. A step of selecting two or more construction items described in the above from a set of variables whose correlation coefficient is higher than a predetermined value.
Including further quality evaluation methods. Acquire a data set of the actual value of the quality evaluation item, which is an index for evaluating the quality of the infrastructure to be built, and the actual value of two or more construction items of the infrastructure, and perform regression analysis on the data set. With the construction scale definition unit that defines the calculation formula of the construction scale that indicates the scale of the infrastructure infrastructure by determining the regression coefficient of the regression equation with the quality evaluation item as the objective variable and the construction item as the explanatory variable. ,
Acquire the project basic information including the planned number of constructions of the two or more construction items, subdivide the planned number of constructions by product category, and calculate the sum of each subdivided weight weighted by the coefficient for each product category. , The quality target setting unit that calculates the value obtained by multiplying the calculated sum by the regression coefficient corresponding to the construction item and adding the value over all the construction items as the construction scale.
A quality evaluation device equipped with. In the quality evaluation apparatus according to claim 5,
The quality target setting unit further
A value obtained by averaging the actual value of the quality evaluation item divided by the construction scale on the data set is calculated, a lower limit value and an upper limit value in a predetermined range including the averaged value are specified, and the lower limit value is specified. And by multiplying the upper limit value by the construction scale calculated based on the project basic information, the lower limit value and the upper limit value of the target value of the quality evaluation item are determined.
Quality evaluation device.

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