Cloud platform quality evaluation method and device, and electronic device

Abstract

The application provides an evaluation method for cloud platform quality, comprising the following steps: determining the coverage and pass rate of each quality sub-domain; according to the coverage and pass rate, using a preset coloring rule to determine the coloring condition of each quality sub-domain in the quality map corresponding to the cloud product, wherein the coloring condition is used to represent the quality condition of the quality sub-domain; and using the quality condition to determine the quality score of the cloud platform. The application can comprehensively evaluate each quality domain of the distributed complex system of the cloud platform, supplement the existing quality model according to the particularity of the cloud platform, increase the API quality, the high availability and the monitoring alarm, and make the evaluation result of the quality model more accurate.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of platform quality evaluation, and in particular to a cloud platform quality evaluation method and device and electronic equipment. BACKGROUND

[0002] With the continuous development of the IT field, the continuous progress of digital production and life, and the gradual popularity of cloud-shaped software, the cloud has become a basic infrastructure for carrying data and applications, and its quality status has attracted more and more attention. Once the infrastructure fails, the consequences are disastrous. However, as one of the most complex software systems, it is very difficult to evaluate the quality status of the cloud. Before a version is updated to the production environment, it has to be evaluated.

[0003] In the traditional technology, the McCall model, the Boehm model, etc. are usually used to evaluate the quality of software according to the running state or use of the software. The ISO / IEC 2501n is the latest achievement at present. This standard model uses 8 characteristics and 31 sub- characteristics to evaluate the software quality. For single machine systems and software, it is a very comprehensive and accurate evaluation model. However, for a cloud platform, which is a distributed complex system, this model lacks the evaluation of the quality domains such as API (Application Program Interface) quality, high availability quality, and monitoring and alarm quality. The quality of these quality domains is crucial to the online operation of the cloud platform. SUMMARY

[0004] The technical problem to be solved by the present application is that the prior art lacks a method for comprehensively evaluating the quality of a cloud platform, which is a distributed complex system. The present application provides a cloud platform quality evaluation method.

[0005] The technical solution adopted by the present application is that the cloud platform includes at least one cloud product, each cloud product includes at least two quality sub-domains, and the cloud platform quality evaluation method includes: determining the coverage rate and pass rate of each quality sub-domain; according to the coverage rate and the pass rate, using a preset coloring rule to determine the coloring condition of each quality sub-domain in the quality map corresponding to the cloud product, wherein the coloring condition is used to represent the quality status of the quality sub-domain; and using the coloring condition to determine the quality score of the cloud platform.

[0006] In one embodiment, the determination of the coverage rate and the pass rate of each quality sub-domain includes: determining the coverage rate corresponding to the quality sub-domain according to a preset coverage rate measurement method corresponding to the quality sub-domain; and calculating the pass rate corresponding to the quality sub-domain according to the following formula:

[0007]

[0008] wherein, P is the pass rate, D i is a weight of a test case with priority i, M i is a number of test cases with a pass result and priority i in the quality sub-domain, N i is a total number of test cases with priority i in the quality sub-domain participating in the calculation of the coverage rate.

[0009] In one embodiment, the coloring condition of each of the quality sub-domains in the quality map corresponding to the cloud product is determined according to the coverage rate and the pass rate, and a preset coloring rule, wherein the coloring condition is used to represent the quality condition of the quality sub-domain, including: drawing a corresponding table including the coverage rate and the pass rate of all the cloud products and all the quality sub-domains corresponding thereto to form the quality map; when the pass rate is greater than a preset first pass rate threshold and the coverage rate is greater than a preset first coverage rate threshold, the corresponding quality sub-domain is configured as a first color at a corresponding position in the quality map; when the pass rate is less than a preset second pass rate threshold and the coverage rate is greater than a preset second coverage rate threshold, the corresponding quality sub-domain is configured as a second color at a corresponding position in the quality map; and other areas in the quality map not configured with a color are configured as a third color; wherein the first pass rate threshold is greater than the second pass rate threshold, and the first coverage rate threshold is greater than the second coverage rate threshold.

[0010] In one embodiment, the quality score of the cloud platform is determined according to the quality condition, including: determining the quality score of the cloud product corresponding to the quality condition by using the following formula:

[0011]

[0012] wherein, ω is the quality score of the cloud product, k(P, C) is a coloring formula, D is a high-risk legacy problem correction score, and L is the total number of quality sub-domains; and the quality score of the cloud platform commonly corresponding to at least one of the cloud products is determined by using the following formula:

[0013]

[0014] wherein, A is the quality score of the cloud platform, and R is the total number of cloud products in the cloud platform.

[0015] Another aspect of the present application provides a cloud platform quality evaluation device, the cloud platform comprising at least one cloud product, each of the cloud products comprising at least two quality sub-domains, the cloud platform quality evaluation device comprising: a calculation module configured to determine a coverage rate and a pass rate of each of the quality sub-domains; a dyeing module configured to determine a dyeing condition of each of the quality sub-domains in a quality map corresponding to the cloud product according to the coverage rate and the pass rate by using a preset dyeing rule, wherein the dyeing condition is used to represent a quality condition of the quality sub-domain; and a statistical module configured to determine a quality score of the cloud platform by using the quality condition.

[0016] In one embodiment, the calculation module is further configured to determine the coverage rate of each of the quality sub-domains according to a preset coverage rate measurement method corresponding to the quality sub-domain, and to calculate the pass rate of each of the quality sub-domains according to the following formula:

[0017]

[0018] wherein P is the pass rate, D i is a test case weight of a priority i, M i is a number of test cases of the quality sub-domain with a pass result and a priority i, N i is a total number of test cases of the quality sub-domain participating in coverage rate calculation and having a priority i.

[0019] In one embodiment, the dyeing module is further configured to draw a corresponding table comprising the coverage rate and the pass rate of all the cloud products and corresponding all the quality sub-domains to constitute the quality map, to configure a corresponding position of each of the quality sub-domains in the quality map as a first color when the pass rate is greater than a preset first pass rate threshold value and the coverage rate is greater than a preset first coverage rate threshold value, to configure a corresponding position of each of the quality sub-domains in the quality map as a second color when the pass rate is less than a preset second pass rate threshold value and the coverage rate is greater than a preset second coverage rate threshold value, and to configure other areas in the quality map without color configuration as a third color, wherein the first pass rate threshold value is greater than the second pass rate threshold value, and the first coverage rate threshold value is greater than the second coverage rate threshold value.

[0020] In one embodiment, the statistical module is further configured to determine the quality score of the cloud product corresponding to the quality condition by using the following formula:

[0021]

[0022] wherein, ω is a quality score of the cloud product, k(P,C) is a dyeing formula, D is a high-risk legacy problem correction score, L is a total number of the quality sub-domains; a quality score of the cloud platform commonly corresponding to at least one of the cloud products is determined by using the following formula:

[0023]

[0024] wherein, A is a quality score of the cloud platform, R is a total number of the cloud products in the cloud platform.

[0025] Another aspect of the present application provides an electronic device comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, wherein the computer program, when executed by the processor, implements the steps of the cloud platform quality evaluation method according to any one of the above.

[0026] Another aspect of the present application provides a computer storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the steps of the cloud platform quality evaluation method according to any one of the above.

[0027] By using the above technical solution, the present application has at least the following advantages:

[0028] The cloud platform quality evaluation method according to the present application can comprehensively evaluate each quality domain of the cloud platform, which is a distributed complex system, and supplement the existing quality model according to the particularity of the cloud platform. The quality model is increased with the quality domains of API quality, high availability, and monitoring and alarming, so that the evaluation result of the quality model is more accurate.

[0029] Furthermore, the present application uses the coverage rate and pass rate of test cases to comprehensively evaluate the quality of each quality domain, and does not rely on subjective judgment of experts, so that the result is more objective and more in line with the actual situation.

[0030] Further, the present application draws a quality map according to the quality status of each quality domain, so that the quality risk is visible and measurable. The cloud platform customer can obtain the strong and weak points from the map. The R&D test of the cloud platform can obtain which quality domain has a problem and where more investment is needed from the map. BRIEF DESCRIPTION OF DRAWINGS

[0031] Figure 1 A flow chart of the cloud platform quality evaluation method according to the embodiment of the present application;

[0032] Figure 2 A schematic diagram of the dyeing rule in the embodiment of the present application;

[0033] Figure 3 A schematic diagram of the quality map after dyeing processing in the embodiment of the present application;

[0034] Figure 4 A cloud platform quality evaluation device according to an embodiment of the present application is shown in the structure diagram.

[0035] Figure 5 An electronic device according to an embodiment of the present application is shown in the structure diagram. DETAILED DESCRIPTION

[0036] In order to further clarify the technical means and effects of the present application, the following will be described in detail in conjunction with the preferred embodiments and the accompanying drawings.

[0037] The description of the method flow in the specification of the present application and the steps of the flow chart in the drawings of the present application do not necessarily strictly follow the step numbers, and the method steps can change the execution order. Moreover, some steps can be omitted, a plurality of steps can be combined into one step, and / or one step can be divided into a plurality of steps.

[0038] A cloud platform quality evaluation method according to a first embodiment of the present application, as shown in the flow chart, includes the following specific steps: Figure 1

[0039] Step S1, determining the coverage rate and the pass rate of each quality sub-domain.

[0040] Step S2, according to the coverage rate and the pass rate, using a preset coloring rule, determining the coloring condition of each quality sub-domain in the quality map corresponding to the cloud product, wherein the coloring condition is used to represent the quality condition of the quality sub-domain.

[0041] Step S3, using the quality condition, determining the quality score of the cloud platform.

[0042] The cloud platform quality evaluation method provided in the present example will be described in detail in the following steps.

[0043] Step S1, determining the coverage rate and the pass rate of each quality sub-domain.

[0044] In the present embodiment, the cloud platform can include at least one cloud product (usually there are many cloud products), wherein each cloud product can include a plurality of quality domains according to the needs, and each quality domain can further include one or more quality sub-domains.

[0045] In the present embodiment, the quality model of ISO / IEC 2501n can be supplemented, specifically, the supplement of the quality sub-domain can be included.

[0046] ​Exemplarily, each cloud product can include 5 quality domains and 11 quality sub-domains, and specifically, the 5 quality domains include deliverability, availability, reliability, operability, and secure operation. Further, the deliverability quality domain includes an E2E deployment quality sub-domain, the availability quality domain includes 3 quality sub-domains of API quality, E2E function (UI), and performance capacity, the reliability quality domain includes 2 quality sub-domains of high availability and long-time stability, the operability includes 3 quality sub-domains of monitoring alarm, data backup, and server operation, and the secure operation includes 2 quality sub-domains of security scanning and penetration testing, totaling 5 quality domains and 11 quality sub-domains.

[0047] In this embodiment, each quality sub-domain includes a large number of test cases, and each test case is set with a different processing priority, which can be 4 levels. In subsequent steps, the test cases of each quality sub-domain can be processed in order according to the priority order of the test cases.

[0048] In this embodiment, the coverage rate corresponding to the quality sub-domain is determined according to the preset coverage rate measurement method corresponding to the quality sub-domain, and the specific corresponding calculation method can be as shown in the following table:

[0049]

[0050] According to the corresponding relationship in the table, the coverage rate C of each quality sub-domain in each cloud product is calculated.

[0051] It should be noted that the number of quality domains and the division of the corresponding relationship can be appropriately changed according to actual needs, and similarly, the calculation method shown in the table does not mean that there is only one calculation method for the corresponding quality sub-domain. Any reasonable modification made on the basis of the present application should be included in the protection scope of the present application.

[0052] Further, the pass rate of each quality sub-domain can be calculated. It can be understood that the calculation of the pass rate does not need to be performed after the calculation of the coverage rate, and the order between the two does not affect the present application. That is, the order of calculating the pass rate of each quality sub-domain and the pass rate can be adjusted.

[0053] Specifically, the pass rate corresponding to the quality sub-domain can be calculated according to the following formula (1):

[0054]

[0055] Wherein, P is the pass rate, D i is the weight of a test case with priority i, M i is the number of test cases with a pass result and priority i in the quality sub-domain, and N iTotal number of test cases in the quality sub-domain with priority i participating in the coverage calculation.

[0056] In step S2, according to the coverage and the pass rate, a preset coloring rule is used to determine the coloring condition of each quality sub-domain in the quality map corresponding to the cloud product, wherein the coloring condition is used to represent the quality condition of the quality sub-domain.

[0057] In this embodiment, a corresponding table including the coverage and the pass rate of all the cloud products and all the quality sub-domains can be drawn first to form a quality map.

[0058] Next, the quality map is colored. In this embodiment, the specific color of the corresponding position in the quality map is determined according to the coverage and the pass rate of the corresponding quality sub-domain, as shown in FIG. 2. Figure 2

[0059] The specific coloring rule can be configured as follows:

[0060] When the pass rate is greater than a preset first pass rate threshold and the coverage is greater than a preset first coverage threshold, the corresponding quality sub-domain is configured as a first color at the corresponding position in the quality map;

[0061] When the pass rate is less than a preset second pass rate threshold and the coverage is greater than a preset second coverage threshold, the corresponding quality sub-domain is configured as a second color at the corresponding position in the quality map;

[0062] The area in the quality map that is not configured with a color is configured as a third color;

[0063] The first pass rate threshold is greater than the second pass rate threshold, and the first coverage threshold is greater than the second coverage threshold.

[0064] For example, the first color can be green, the second color can be red, the third color can be yellow, the first pass rate threshold can be 90%, the first coverage threshold can be 80%, the second pass rate threshold can be 80%, and the second coverage threshold can be 60%.

[0065] It should be noted that the color selection can be adjusted according to actual needs, and the selection of each threshold can also be adjusted within a certain range according to actual application needs.

[0066] It can be understood that, as shown in FIG. 2, the color corresponding to a quality sub-domain in the quality map after coloring can be used to represent the quality condition of the quality sub-domain. Figure 3

[0067] ​​Step S3, determining the quality score of the cloud platform by using the quality status.

[0068] In this embodiment, the quality score of the corresponding cloud product is obtained by comprehensively using the quality status of each quality sub-domain, and further, the quality score of the corresponding cloud platform is obtained by comprehensively using the quality scores of each cloud product.

[0069] First, the quality score of the cloud product corresponding to the quality status is determined by using the following formula (2):

[0070]

[0071] wherein ω is the quality score of the cloud product, k(P, C) is a coloring formula (P is the pass rate of the corresponding quality sub-domain, and C is the coverage rate of the corresponding quality sub-domain), D is a high-risk legacy problem correction score, and L is the total number of quality sub-domains.

[0072] The quality score of the cloud platform commonly corresponding to at least one cloud product is determined by using the following formula (3):

[0073]

[0074] wherein A is the quality score of the cloud platform, and R is the total number of the cloud products in the cloud platform.

[0075] In this embodiment, the quality score A of the cloud platform is obtained to quantify the quality status of the cloud platform.

[0076] Compared with the prior art, the present application has at least the following advantages:

[0077] 1) The present application can comprehensively evaluate each quality domain of the cloud platform, which is a distributed complex system, and supplement the quality model of ISO / IEC 2501n according to the particularity of the cloud platform. The quality model can obtain more accurate evaluation results by adding the quality domains of API quality, high availability and monitoring alarm.

[0078] 2) The present application uses the coverage rate and pass rate of test cases to comprehensively evaluate the quality of each quality domain, and does not rely on subjective judgment of experts, so that the results are more objective and more in line with the actual situation.

[0079] 3) The present application draws a quality map according to the quality status of each quality domain, so that the quality risk is visible and measurable. The cloud platform customers can obtain the strong and weak points from the map. The research and development test of the cloud platform can obtain which quality domain has problems and where more investment is needed from the map.

[0080] 4) The present application gives the evaluation score of the cloud platform, which can be used for simple comparison of the quality of the longitudinal version of the cloud platform, or for horizontal comparison of the quality of different cloud platforms.

[0081] The second embodiment of the present application corresponds to the first embodiment, and the embodiment introduces an evaluation device for cloud platform quality, as shown in the following figure, which comprises the following components: Figure 4

[0082] The computing module is configured to determine the coverage rate and the pass rate of each quality sub-domain. The coloring module is configured to determine the coloring condition of each quality sub-domain in the quality map corresponding to the cloud product according to the coverage rate and the pass rate by using a preset coloring rule, wherein the coloring condition is used to represent the quality condition of the quality sub-domain. The statistical module is configured to determine the quality score of the cloud platform by using the quality condition.

[0083] In the embodiment, the computing module is further configured to:

[0084] determine the coverage rate corresponding to the quality sub-domain according to a preset coverage rate measurement method corresponding to the quality sub-domain;

[0085] calculate the pass rate corresponding to the quality sub-domain according to the following formula (4):

[0086]

[0087] wherein P is the pass rate, D i is the weight of a test case with priority i, M i is the number of test cases with the test case result of pass and the priority of i in the quality sub-domain, and N i is the total number of test cases with the priority of i and participating in the coverage rate calculation in the quality sub-domain.

[0088] In the embodiment, the coloring module is further configured to:

[0089] draw a corresponding table including the coverage rate and the pass rate of all cloud products and all corresponding quality sub-domains to constitute the quality map.

[0090] when the pass rate is greater than a preset first pass rate threshold value and the coverage rate is greater than a preset first coverage rate threshold value, the corresponding quality sub-domain is configured as a first color at the corresponding position of the quality map.

[0091] when the pass rate is less than a preset second pass rate threshold value and the coverage rate is greater than a preset second coverage rate threshold value, the corresponding quality sub-domain is configured as a second color at the corresponding position of the quality map.

[0092] the other areas in the quality map which are not configured with colors are configured as a third color.

[0093] wherein the first pass rate threshold value is greater than the second pass rate threshold value, and the first coverage rate threshold value is greater than the second coverage rate threshold value. ​

[0094] In this embodiment, the statistical module is further configured to:

[0095] The quality score of the cloud product corresponding to the quality condition is determined by using the following formula (5):

[0096]

[0097] Wherein, ω is the quality score of the cloud product, k(P, C) is the dyeing formula, D is the high-risk residual problem correction score, and L is the total number of quality sub-domains.

[0098] The quality score of the cloud platform commonly corresponding to at least one cloud product is determined by using the following formula (6):

[0099]

[0100] Wherein, A is the quality score of the cloud platform, and R is the total number of cloud products in the cloud platform.

[0101] In the third embodiment of the present application, an electronic device is provided, which can be understood as a physical device, comprising a processor and a memory storing processor-executable instructions, when the instructions are executed by the processor, the steps of the cloud platform quality evaluation method in the first embodiment are performed. Figure 5 The electronic device can be understood as a physical device, comprising a processor and a memory storing processor-executable instructions, when the instructions are executed by the processor, the steps of the cloud platform quality evaluation method in the first embodiment are performed.

[0102] In the fourth embodiment of the present application, the flow of the cloud platform quality evaluation method is the same as that of the first embodiment, and the difference lies in that in engineering implementation, the present embodiment can be realized by means of software and necessary general hardware platform, of course, it can also be realized by hardware, but in many cases, the former is a better implementation. Based on such understanding, the method of the present application can be embodied in the form of a computer software product, which is stored in a storage medium (such as ROM / RAM, magnetic disc, optical disc), and includes a plurality of instructions for causing a device (which can be a base station or other network device) to execute the method described in the embodiments of the present application.

[0103] In summary, compared with the prior art, the present application has at least the following advantages:

[0104] 1) The present application can comprehensively evaluate each quality domain of the cloud platform, a distributed complex system, and supplement the quality model of ISO / IEC 2501n according to the particularity of the cloud platform. The quality model is more accurate in evaluation.

[0105] 2) The present application uses the coverage rate and pass rate of test cases to comprehensively evaluate the quality of each quality domain, and does not rely on subjective judgment of experts, so the result is more objective and more in line with reality.

[0106] 3) The present application draws a quality map according to the quality status of each quality domain, so that the quality risk is visible and measurable. The cloud platform customer can draw strong and weak points from this map. The R&D test of the cloud platform can draw which quality domain has problems and where more investment is needed from this map.

[0107] 4) The present application gives the evaluation score of the cloud platform, which can be used for simple comparison of the longitudinal version quality of the cloud platform, or for horizontal comparison of the quality of different cloud platforms.

[0108] Through the description of the specific embodiments, the technical means and effects taken by the present application to achieve the predetermined purposes can be more deeply and specifically understood. However, the accompanying drawings are only provided for reference and illustration, and are not used to limit the present application.

Claims

1. A method for evaluating the quality of a cloud platform, characterized in that, The cloud platform includes at least one cloud product, each cloud product includes at least two quality subdomains, and the evaluation method for the quality of the cloud platform includes: Determine the coverage and throughput of each of the quality subdomains; Based on the coverage rate and the pass rate, and using preset coloring rules, the coloring status of each quality subdomain in the quality map corresponding to the cloud product is determined, wherein the coloring status is used to characterize the quality status of the quality subdomain. Using the aforementioned quality status, the quality score of the cloud platform is determined; determining the coverage and pass rate of each quality sub-domain includes: The coverage of the quality subdomain is determined according to the preset coverage measurement method corresponding to the quality subdomain; The throughput corresponding to the quality subdomain is calculated according to the following formula: ； in, The pass rate, Let i be the weight of a test case with priority i. This refers to the number of test cases in the quality subdomain that have passed the test and have a priority of i. The total number of test cases with priority i that participate in the coverage calculation within the quality subdomain; The step involves determining the coloring status of each quality sub-domain in the quality map corresponding to the cloud product based on the coverage rate and the pass rate, using preset coloring rules. The coloring status characterizes the quality status of the sub-domain and includes: A mapping table is drawn that includes the coverage and pass rate of all the cloud products and their corresponding quality subdomains to form the quality map; When the pass rate is greater than a preset first pass rate threshold and the coverage rate is greater than a preset first coverage threshold, the corresponding quality subdomain is configured with the first color at the corresponding position on the quality map. When the pass rate is less than a preset second pass rate threshold and the coverage rate is greater than a preset second coverage threshold, the corresponding quality subdomain is configured with the second color at the corresponding position on the quality map; Configure the other uncolored areas in the quality map to the third color; Wherein, the first pass rate threshold is greater than the second pass rate threshold, and the first coverage threshold is greater than the second coverage threshold; Determining the quality score of the cloud platform using the quality status includes: The quality score of the cloud product corresponding to the quality status is determined using the following formula: ； in, Let k(P,C) be the quality score of the cloud product, k(P,C) be the coloring formula, D be the high-risk legacy issue correction score, and L be the total number of the quality subdomains. The quality score of the cloud platform corresponding to at least one of the cloud products is determined using the following formula: ； Where A is the quality score of the cloud platform, and R is the total number of cloud products in the cloud platform.

2. A device for evaluating the quality of a cloud platform, characterized in that, The cloud platform includes at least one cloud product, each cloud product includes at least two quality subdomains, and the cloud platform quality evaluation device includes: The calculation module is configured to determine the coverage and throughput of each of the quality subdomains; Coloring module: configured to determine the coloring status of each quality subdomain in the quality map corresponding to the cloud product based on the coverage rate and the pass rate, using preset coloring rules, wherein the coloring status is used to characterize the quality status of the quality subdomain. The statistics module is configured to determine the quality score of the cloud platform using the quality status. The computing module is further configured as follows: The coverage of the quality subdomain is determined according to the preset coverage measurement method corresponding to the quality subdomain; The throughput corresponding to the quality subdomain is calculated according to the following formula: ； in, The pass rate, Let i be the weight of a test case with priority i. This refers to the number of test cases in the quality subdomain that have passed the test and have a priority of i. The total number of test cases with priority i that participate in the coverage calculation within the quality subdomain. The staining module is further configured as follows: A mapping table is drawn that includes the coverage and pass rate of all the cloud products and their corresponding quality subdomains to form the quality map; When the pass rate is greater than a preset first pass rate threshold and the coverage rate is greater than a preset first coverage threshold, the corresponding quality subdomain is configured with the first color at the corresponding position on the quality map. When the pass rate is less than a preset second pass rate threshold and the coverage rate is greater than a preset second coverage threshold, the corresponding quality subdomain is configured with the second color at the corresponding position on the quality map; Configure the other uncolored areas in the quality map to the third color; Wherein, the first pass rate threshold is greater than the second pass rate threshold, and the first coverage threshold is greater than the second coverage threshold; The statistics module is further configured as follows: The quality score of the cloud product corresponding to the quality status is determined using the following formula: ； in, Let k(P,C) be the quality score of the cloud product, k(P,C) be the coloring formula, D be the high-risk legacy issue correction score, and L be the total number of the quality subdomains. The quality score of the cloud platform corresponding to at least one of the cloud products is determined using the following formula: ； Where A is the quality score of the cloud platform, and R is the total number of cloud products in the cloud platform.

3. An electronic device, characterized in that, include: The memory, the processor, and the computer program stored in the memory and executable on the processor, wherein the computer program, when executed by the processor, implements the steps of the cloud platform quality evaluation method as described in claim 1.

4. A computer storage medium storing a computer program, wherein the computer program, when executed by a processor, implements the steps of the cloud platform quality evaluation method as described in claim 1.

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