Product standardization rate determination method and apparatus, and computer program product

Abstract

The invention provides a product standardization rate determination method and device, electronic equipment, a storage medium and a computer program product, relates to the technical field of computers, in particular to the technical field of software development, and can be applied to a software development scene. According to the specific implementation scheme, the method comprises the steps that the weight of newly-added demand data is determined according to the number of the newly-added demand data for the software product; and determining the product standardization rate of the software product according to the weight of the newly added demand data and the number of the target software projects related to the software product. According to the method, the product standardization rate can be determined based on the number of the newly added demand data and the number of the target software projects related to the software product, and the accuracy and convenience of the calculation process of the product standardization rate are improved.

Description

Technical Field

[0001] The present disclosure relates to the field of computer technology, specifically to the field of software development technology, and in particular to a method, device, electronic device, storage medium and computer program product for determining a product standardization rate, which can be applied in software development scenarios. Background Art

[0002] Software projects generally consist of standardized software products and customized software products developed based on customer customization requirements. Standardized software products usually have higher profit margins due to their replicability. Customized software products, on the other hand, require customized development, and most customized software products cannot be reused, which usually results in higher costs. Therefore, major software development companies are pursuing a high product standardization rate for software products to reduce customized development. However, how to measure the product standardization rate is a problem. Summary of the invention

[0003] The present disclosure provides a method, an apparatus, an electronic device, a storage medium and a computer program product for determining a product standardization rate.

[0004] According to a first aspect, a method for determining a product standardization rate is provided, comprising: determining a weight of new demand data according to the amount of new demand data for a software product; and determining a product standardization rate of the software product according to the weight of the new demand data and the number of target software projects involving the software product.

[0005] According to a second aspect, a device for determining a product standardization rate is provided, comprising: a weight determination unit, configured to determine the weight of new demand data according to the amount of new demand data for a software product; a standardization rate determination unit, configured to determine the product standardization rate of a software product according to the weight of the new demand data and the amount of target software projects involved in the software product.

[0006] According to a third aspect, an electronic device is provided, comprising: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute a method described in any implementation manner of the first aspect.

[0007] According to a fourth aspect, a non-transitory computer-readable storage medium storing computer instructions is provided, where the computer instructions are used to cause a computer to execute the method described in any implementation of the first aspect.

[0008] According to a fifth aspect, a computer program product is provided, comprising: a computer program, which implements the method described in any implementation manner of the first aspect when executed by a processor.

[0009] According to the technology disclosed in the present invention, a method and device for determining a product standardization rate are provided. First, the weight of the new demand data is determined according to the amount of new demand data for the software product. Then, the product standardization rate of the software product is determined according to the weight of the new demand data and the number of target software projects involving the software product. From the perspective of user needs, the product standardization rate can be determined based on the amount of new demand data and the number of target software projects involving the software product, thereby improving the accuracy and convenience of the product standardization rate calculation process.

[0010] It should be understood that the content described in this section is not intended to identify the key or important features of the embodiments of the present disclosure, nor is it intended to limit the scope of the present disclosure. Other features of the present disclosure will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] The accompanying drawings are used to better understand the present solution and do not constitute a limitation of the present disclosure.

[0012] Figure 1 is an exemplary system architecture diagram in which an embodiment of the present disclosure may be applied;

[0013] Figure 2 is a flow chart of an embodiment of a method for determining a product standardization rate according to the present disclosure;

[0014] Figure 3 is a schematic diagram of an application scenario of the method for determining a product standardization rate according to this embodiment;

[0015] Figure 4 is a schematic diagram of the development process of a software product according to this embodiment;

[0016] Figure 5 is a flow chart of another embodiment of a method for determining a product standardization rate according to the present disclosure;

[0017] Figure 6 is a structural diagram of an embodiment of a device for determining a product standardization rate according to the present disclosure;

[0018] Figure 7 It is a schematic diagram of the structure of a computer system suitable for implementing the embodiments of the present disclosure. DETAILED DESCRIPTION

[0019] The following is a description of exemplary embodiments of the present disclosure in conjunction with the accompanying drawings, including various details of the embodiments of the present disclosure to facilitate understanding, which should be considered as merely exemplary. Therefore, it should be recognized by those of ordinary skill in the art that various changes and modifications may be made to the embodiments described herein without departing from the scope and spirit of the present disclosure. Similarly, for the sake of clarity and conciseness, descriptions of well-known functions and structures are omitted in the following description.

[0020] In the technical solution of the present disclosure, the collection, storage, use, processing, transmission, provision and disclosure of user personal information involved are in compliance with the provisions of relevant laws and regulations and do not violate public order and good morals.

[0021] Figure 1 An exemplary architecture 100 is shown to which the method and apparatus for determining a product normalization rate of the present disclosure may be applied.

[0022] like Figure 1 As shown, the system architecture 100 may include terminal devices 101, 102, 103, a network 104 and a server 105. The communication connection between the terminal devices 101, 102, 103 constitutes a topological network, and the network 104 is used to provide a medium for the communication link between the terminal devices 101, 102, 103 and the server 105. The network 104 may include various connection types, such as wired, wireless communication links or optical fiber cables, etc.

[0023] Terminal devices 101, 102, 103 may be hardware devices or software that support network connection for data interaction and data processing. When terminal devices 101, 102, 103 are hardware, they may be various electronic devices that support network connection, information acquisition, interaction, display, processing and other functions, including but not limited to smart phones, tablet computers, e-book readers, laptop computers and desktop computers, etc. When terminal devices 101, 102, 103 are software, they may be installed in the electronic devices listed above. They may be implemented as multiple software or software modules for providing distributed services, or they may be implemented as a single software or software module. No specific limitation is made here.

[0024] The server 105 may be a server that provides various services, for example, a background processing server that obtains new demand data for software products sent by users through the terminal devices 101, 102, 103, and determines the product standardization rate of the software product according to the new demand data. As an example, the server 105 may be a cloud server.

[0025] It should be noted that the server can be hardware or software. When the server is hardware, it can be implemented as a distributed server cluster consisting of multiple servers, or it can be implemented as a single server. When the server is software, it can be implemented as multiple software or software modules (for example, software or software modules used to provide distributed services), or it can be implemented as a single software or software module. No specific limitation is made here.

[0026] It should also be noted that the method for determining the product standardization rate provided in the embodiments of the present disclosure is generally executed by a server, but the possibility of being executed by a terminal device, or being executed by the server and the terminal device in cooperation with each other, is not excluded. Accordingly, the various parts (such as various units) included in the device for determining the product standardization rate can be all set in the server, or all set in the terminal device, or can be set in the server and the terminal device respectively.

[0027] It should be understood that Figure 1 The number of terminal devices, networks, and servers in the system is only illustrative. According to the implementation requirements, there may be any number of terminal devices, networks, and servers. When the electronic device on which the method for determining the product standardization rate is running does not need to transmit data with other electronic devices, the system architecture may only include the electronic device (e.g., terminal device or server) on which the method for determining the product standardization rate is running.

[0028] Please refer to Figure 2 , Figure 2 A flowchart of a method for determining a product standardization rate provided in an embodiment of the present disclosure. In process 200, the following steps are included:

[0029] Step 201 : determining the weight of the newly added demand data according to the amount of the newly added demand data for the software product.

[0030] In this embodiment, the execution subject of the method for determining the product standardization rate (for example, Figure 1 The server in the example may obtain the new demand data for the software product remotely or locally through a wired network connection or a wireless network connection, and determine the weight of the new demand data according to the amount of the new demand data for the software product.

[0031] A software project refers to a task or a series of tasks aimed at developing, maintaining or improving a software system. It is generally composed of standardized software products and customized software products developed based on customer customization requirements. Standardized software products refer to a series of software products with universality, stability and reliability that are formed after extensive market research, demand analysis, design, development and testing. These products usually follow certain industry standards and specifications and can meet the common needs of most users in the market. For standardized software products, due to their universality, stability and ease of use, they usually have higher profit margins. For customized software products, customized development is required, and most customized software products cannot be reused, and usually have higher costs. Therefore, major software development manufacturers are pursuing a high product standardization rate for software products to reduce customized development.

[0032] The product standardization rate (standardization rate) is given by the market and is a measure of whether the product meets the needs of users in the market. If a software product meets the needs of all users in the market or as many users as possible, then its standardization rate is high; if a software product can only meet the needs of a few users in the market, then its standardization rate is low. At this time, users can propose new development requirements (new demand data) to the software product so that the software product can meet their own needs as much as possible.

[0033] In this embodiment, the number of new demand data is used as an inverse indicator to measure the product standardization rate. When the number of new demand data for a software product is large, the product standardization rate is low; when the number of new demand data for a software product is small, the product standardization rate is high.

[0034] As an example, a software developer (such as a software developer) counts the new demands of users of each software product developed by the software product to obtain new demand data; clusters or classifies the new demand data to determine the number of each type of new demand data; and for each type of new demand data, determines the weight of the new demand data according to the number of the new demand data.

[0035] Among them, the weight of the new demand data can be positively correlated with the quantity, and the weight of the new demand data can also be negatively correlated with the quantity, which involves the relationship between the subsequent product standardization rate and the weight of the new demand data.

[0036] In some optional implementations of this embodiment, the execution subject may perform step 201 in the following manner:

[0037] First, within a preset time period, in response to obtaining new demand data for a software product, it is determined whether the demand data pool includes the new demand data.

[0038] In this implementation, the product standardization rate of the software product is determined with a preset time period as the statistical period, wherein the preset time period can be flexibly set according to actual needs, for example, the length of the preset time period is one quarter.

[0039] In a preset time period, the newly added demand data of the users of the software product for the software product can be continuously obtained. In response to receiving a newly added demand of the user for the software product, a piece of newly added demand data representing the newly added demand is determined, and it is determined whether the newly added demand data is already included in the demand data pool according to the newly added demand data. Among them, the newly added demand pool includes the demand data of all the demands of each user for the software product in the preset time period. It can be understood that the demand data in the newly added demand pool is not repeated, and for each demand, only one piece of demand data corresponding to the demand is included.

[0040] As an example, the above-mentioned execution entity may compare the newly added demand data with the existing demand data in the demand data pool to determine the similarity between the newly added demand data and the demand data in the demand data pool; in response to the existence of a target similarity exceeding a preset similarity threshold, it is determined that the demand data pool includes the newly added demand data, that is, the demand data corresponding to the target similarity is essentially consistent with the newly added demand data.

[0041] Then, in response to the determination, the weight of the newly added demand data is increased based on a preset manner on the basis of a current weight of the newly added demand data in the demand data pool to obtain an adjusted weight.

[0042] Each piece of demand data in the demand data pool is provided with a corresponding weight, and in response to receiving new demand data that is consistent with the existing demand data, the weight of the demand data that is consistent with the new demand data is adjusted.

[0043] The preset method is, for example, to increase a preset weight value or to increase a preset weight multiple.

[0044] As an example, if the newly added demand data is consistent with demand data A in the demand data pool, the current weight a corresponding to demand data A is multiplied by the weight multiplier 2 to obtain the adjusted weight.

[0045] In this implementation, a specific method for determining the weight of new demand data is provided. Based on the demand data pool, it can be determined whether the new demand data already exists, and the weight is adjusted according to the determination result, which improves the simplicity of the data processing process and the accuracy of the weight result.

[0046] In some optional implementations of this embodiment, before determining whether the demand data pool includes new demand data, the above-mentioned execution entity may also determine the validity of the new demand data to determine whether the demand data pool includes the new demand data if the new demand data is determined to be valid.

[0047] For example, the above-mentioned execution entity may determine whether the new demands represented by the new demand data are clear and whether the new demands represented by the new demand data are technically feasible.

[0048] By judging the validity of the new demand data and filtering out invalid new demand data, it helps to improve the effectiveness of the information processing process and the reliability of the information processing results.

[0049] In some optional implementations of this embodiment, the execution subject may determine whether the demand data pool includes the newly added demand data in the following manner:

[0050] First, based on the preset field template, determine the characteristic data of the newly added demand data.

[0051] Among them, the preset field template includes multiple key fields that can represent user needs.

[0052] In this implementation, the execution subject may extract keywords corresponding to the multiple key fields to obtain feature data of the newly added demand data.

[0053] Then, the feature data of the newly added demand data is compared with the feature data of the existing demand data in the demand data pool to determine whether the demand data pool includes the newly added demand data.

[0054] In this implementation, the execution subject or the electronic device connected to the execution subject for communication maintains a table of characteristic data of the existing demand data in the demand data pool.

[0055] The execution entity may compare the feature data of the newly added demand data with the feature data of the existing demand data in the demand data pool one by one to determine the similarity. When there is a maximum similarity that exceeds the similarity threshold, the demand data corresponding to the maximum similarity is determined as the demand data consistent with the newly added demand data, that is, it is determined that the demand data pool includes the newly added demand data. Otherwise, it is determined that the demand data pool does not include the newly added demand data.

[0056] In this implementation, a method is provided for determining whether the demand data pool includes new demand data based on comparing feature data, which reduces the amount of data in the comparison process based on the feature data and improves the efficiency and accuracy of determining the comparison result.

[0057] In some optional implementations of this embodiment, the above-mentioned execution subject may also perform the following operations: in response to determining that it is not included, adding the newly added demand data to the demand data pool, and setting an initial weight for the newly added demand data.

[0058] The initial weight may be set according to actual conditions. For example, the initial weight is 1.

[0059] In this implementation, for each piece of newly added demand data added to the demand data pool, its corresponding feature data can be added to the feature data table to be applied to the subsequent feature data comparison process.

[0060] In this implementation, when the demand data pool does not include newly added demand data, the newly added demand data is added to the demand data pool, thereby improving the comprehensiveness and accuracy of the data in the demand data pool.

[0061] Step 202: determine the product standardization rate of the software product according to the weight of the newly added demand data and the number of target software projects related to the software product.

[0062] In this embodiment, the execution entity may determine the product standardization rate of the software product according to the weight of the newly added demand data and the number of target software projects involved in the software product.

[0063] As an example, for a software product, the above-mentioned execution entity may sum the weights of all types of new demand data for the software product to obtain the total weights; determine the number of target software projects that include the software product; divide the total weights by the number of target software projects to obtain a product standardization rate index, and determine the product standardization rate of the software product based on the product standardization rate index.

[0064] It can be understood that when the weight of the newly added demand data is positively correlated with the quantity, the greater the quantity, the greater the weight, and the greater the determined product standardization rate index, at this time, the lower the product standardization rate of the software product. That is, when the weight of the newly added demand data is positively correlated with the quantity, the product standardization rate index is negatively correlated with the product standardization rate.

[0065] When the weight of the newly added demand data is negatively correlated with the quantity, the larger the quantity, the smaller the weight, and the smaller the determined product standardization rate index, at this time, the product standardization rate of the software product is lower. That is, when the weight of the newly added demand data is negatively correlated with the quantity, the product standardization rate index is positively correlated with the product standardization rate.

[0066] In this way, the present disclosure defines the standardization rate of a product from the perspective of user usage of the software product and based on the user's new demand for the software product, thereby providing a unique and novel way to determine the standardization rate, making the determined product standardization rate more practical.

[0067] In some optional implementations of this embodiment, the execution subject may perform step 202 in the following manner:

[0068] First, for a plurality of target software projects, a weight sub-sum corresponding to the target software projects is obtained according to the weight of each of at least one newly added requirement data corresponding to the software products in the target software projects.

[0069] When there are multiple target software projects involving software products, for each target software project, the above execution obtains a weight sub-sum corresponding to the target software project according to the respective weights of at least one newly added requirement data corresponding to the software products in the target software project.

[0070] As an example, the target software projects involving software product A include X and Y. In the preset time period, for software product A in target software project X, the user proposed 3 new requirements, and corresponding new requirement data a, b and c are obtained. For software product A in target software project Y, the user proposed 4 new requirements, and corresponding new requirement data a, c, d and e are obtained.

[0071] At this time, the demand data pool includes demand data a, b, c, d and e. The initial weight of each demand data is 1, and the preset method of increasing the weight is multiplying by a multiple of 2, so the current weights of demand data a, b, c, d and e are 2, 1, 2, 1, 1 respectively.

[0072] For the target software project X, the weights of the requirement data a, b, and c corresponding to the software product A are 2, 1, and 2 respectively, and the sub-sum of the weights is 5 (2+1+2); for the target software project Y, the weights of the requirement data a, c, d, and e corresponding to the software product A are 2, 2, 1, and 1 respectively, and the sub-sum of the weights is 6 (2+2+1+1).

[0073] Then, the total weight is obtained according to the multiple weight sub-sums corresponding to the multiple target software projects.

[0074] In this implementation, multiple weight sub-sums corresponding to multiple target software projects are added together to obtain a weight sum. Continuing with the above example, the weight sub-sum corresponding to target software project X is 5, and the weight sub-sum corresponding to target software project Y is 6, then the weight sum is 11.

[0075] Finally, the product standardization rate of the software product is determined based on the sum of the weights and the number of target software projects.

[0076] In this implementation, the execution entity may divide the sum of the weights by the number of target software projects to obtain a product standardization rate of the software product.

[0077] Continuing to refer to the above example, the total weight 11 is divided by the number of target software projects 2, and the product standardization rate index of the software product is obtained as 5.5. In this implementation, the product standardization rate index is negatively correlated with the product standardization rate.

[0078] In this implementation, a specific method for determining the product standardization rate is provided, which improves the accuracy of the product standardization rate by combining the sum of weights of the weight sub-sums corresponding to each target software project and the number of target software projects.

[0079] Continue to see Figure 3 , Figure 3 300 is a schematic diagram of an application scenario of the method for determining the product standardization rate according to the present embodiment. A software developer 301 provides software services to many users through a server 302. In the process of providing software services, the software developer 301 collects new demands for the software product from a user 303 of the software product through the server 302 to obtain new demand data. After the new demand data is obtained by statistics, first, the weight of the new demand data is determined according to the number of new demand data for the software product, and then the product standardization rate of the software product is determined according to the weight of the new demand data and the number of target software projects involved in the software product.

[0080] In this embodiment, a method for determining a product standardization rate is provided. First, the weight of the new demand data is determined according to the amount of new demand data for the software product. Then, the product standardization rate of the software product is determined according to the weight of the new demand data and the number of target software projects involving the software product. Thus, the product standardization rate can be determined based on the amount of new demand data and the number of target software projects involving the software product, thereby improving the accuracy and convenience of the product standardization rate calculation process.

[0081] In some optional implementations of this embodiment, the above-mentioned execution subject may also perform the following operations: sort the demand data in the demand data pool according to the weight, and determine the sorted demand data to assist the target personnel in determining the requirements for the software product to be developed.

[0082] In this implementation, the above-mentioned execution entity can sort the demand data in the demand data pool in order of weight from large to small, determine the sorted demand data, and display the development priority of the demand data in the demand data pool to the target personnel (for example, software developers), thereby assisting the target personnel in determining the most urgent development needs.

[0083] Continue to refer Figure 4 , which shows a schematic diagram of the development process of a software product.

[0084] In response to receiving new demand data for a software product from a user, the similarity (duplication) between the new demand data and the demand data in a demand data pool is determined; the delivery interface person (e.g., product manager) evaluates the new demand data based on the similarity; in response to determining that the evaluation has passed, the new demand data is transferred to product R&D personnel for evaluation; in response to the evaluation passing, the new demand data is added to the demand data pool, wherein when the demand data pool does not include the new demand data, an initial weight is set for it, and when the demand data pool includes the new demand data, its original weight is adjusted in a preset manner; the demand data in the demand data pool is sorted in descending order of weight, and the product R&D personnel can determine the new demand functions to be developed based on the weights, and release them with the new version of the software product.

[0085] Among them, the delivery interface person and product development personnel may reject the new demand data. When the product development personnel reject the new demand data, the delivery interface person needs to further confirm it. If the delivery interface person disagrees with the rejection, it needs to be submitted to the product development personnel for re-evaluation.

[0086] In this implementation, based on the weight of the demand data in the demand data pool, the target personnel can be assisted in determining the urgency of development of each demand for the software product, so as to instruct the target personnel to give priority to the development of more urgent demand functions and improve the product standardization rate of the software product.

[0087] In some optional implementations of this embodiment, the above-mentioned execution subject may also perform the following operation: determine standardization rate change trend data of the software product according to the product standardization rates corresponding to each software product in multiple preset time periods.

[0088] There is a time sequence relationship between the multiple preset time periods, for example, the multiple preset time periods are four quarters of a year.

[0089] In this implementation, the execution subject can display the product standardization rate corresponding to each of the multiple preset time periods in the form of a line chart, a bar chart, etc. according to the time series relationship between the multiple preset time periods. Standardization rate change trend data includes, for example: the product standardization rate is low and does not show an upward trend; the product standardization rate is low and shows an upward trend; the product standardization rate is high and shows a stable or upward trend; the product standardization rate is high, but shows a downward trend.

[0090] In this implementation, based on the corresponding product standardization rates in multiple preset time periods, standardization rate change trend data can be obtained to assist users in understanding the changing trend of the standardization rate of software products, thereby improving users' information acquisition efficiency and helping users to carry out subsequent development work in an orderly manner.

[0091] In some optional implementations of this embodiment, the above-mentioned execution subject may also perform the following operations: determining a development strategy for the software product according to the standardization rate change trend data.

[0092] As an example, for different types of change trends shown by the standardization rate change trend data, corresponding development strategies can be pre-set to determine the development strategy corresponding to the change trend type after determining the change trend type shown by the standardization rate change trend data.

[0093] As another example, the execution entity may input the standardization rate change trend data into a large model to obtain a development strategy for the software product.

[0094] For example, the product standardization rate has been at a low level for a long time, and the development strategy is to adjust the production line.

[0095] In this implementation, the development strategy of the software product is further determined based on the standardization rate change trend data, which further improves the user's information acquisition efficiency and can help the user to carry out subsequent development work in a more orderly manner.

[0096] Continue to refer Figure 5 , shows a schematic process 500 of another embodiment of a method for determining a product standardization rate according to the present disclosure. In process 500, the following steps are included:

[0097] Step 501 : In response to obtaining new demand data for a software product within a preset time period, determining whether a demand data pool includes the new demand data.

[0098] Step 502, in response to the determination, includes increasing the weight of the newly added demand data in the demand data pool based on a preset method based on the current weight of the newly added demand data to obtain an adjusted weight.

[0099] Step 503 , in response to determining that it is not included, adding the newly added demand data to the demand data pool, and setting an initial weight for the newly added demand data.

[0100] Step 504 : for multiple target software projects, a weight sub-sum corresponding to the target software projects is obtained according to the weight of each of the at least one newly added requirement data corresponding to the software products in the target software projects.

[0101] Step 505 , obtaining a weight sum according to a plurality of weight sub-sums corresponding to a plurality of target software projects one by one.

[0102] Step 506: Determine the product standardization rate of the software product according to the total weight and the number of target software projects.

[0103] Step 507: determining standardization rate change trend data of the software product according to the product standardization rates corresponding to the software products in a plurality of preset time periods.

[0104] Among them, there is a time sequence relationship between the multiple preset time periods.

[0105] It can be seen from this embodiment that Figure 2 Compared with the corresponding embodiments, process 500 of the method for determining the product standardization rate in this embodiment specifically illustrates the process of determining the weight of demand data, the process of determining the product standardization rate, and the process of determining the standardization rate change trend data, thereby improving the accuracy and convenience of the product standardization rate calculation process and the user's information acquisition efficiency.

[0106] Continue to refer Figure 6 As an implementation of the methods shown in the above figures, the present disclosure provides an embodiment of a device for determining a product standardization rate. The system embodiment is similar to Figure 2 Corresponding to the method embodiment shown, the system can be specifically applied to various electronic devices.

[0107] like Figure 6 As shown, the device 600 for determining the product standardization rate includes: a weight determination unit 601, configured to determine the weight of the new demand data according to the amount of the new demand data for the software product; a standardization rate determination unit 602, configured to determine the product standardization rate of the software product according to the weight of the new demand data and the amount of target software projects involved in the software product.

[0108] In some optional implementations of this embodiment, the weight determination unit 601 is further configured to: within a preset time period, in response to obtaining new demand data for a software product, determine whether the demand data pool includes the new demand data; in response to determining that it is included, based on the current weight of the new demand data in the demand data pool, increase the weight of the new demand data based on a preset method to obtain an adjusted weight.

[0109] In some optional implementations of this embodiment, the weight determination unit 601 is further configured to: determine the characteristic data of the newly added demand data based on a preset field template; compare the characteristic data of the newly added demand data with the characteristic data of the existing demand data in the demand data pool, and determine whether the demand data pool includes the newly added demand data.

[0110] In some optional implementations of this embodiment, the weight determination unit 601 is further configured to: in response to determining that it is not included, add the newly added demand data to the demand data pool, and set an initial weight for the newly added demand data.

[0111] In some optional implementations of this embodiment, the above-mentioned device also includes: a sorting unit (not shown in the figure), which is configured to sort the demand data in the demand data pool according to the weight, and determine the sorted demand data to assist the target personnel in determining the requirements for the software product to be developed.

[0112] In some optional implementations of this embodiment, the standardization rate determination unit 602 is further configured to: for multiple target software projects, obtain a weight sub-sum corresponding to the target software project according to the weight of each of at least one new requirement data corresponding to the software product in the target software project; obtain a weight sum according to multiple weight sub-sums corresponding to the multiple target software projects one by one; and determine the product standardization rate of the software product according to the weight sum and the number of target software projects.

[0113] In some optional implementations of this embodiment, the above-mentioned device also includes: a trend determination unit (not shown in the figure), which is configured to determine the standardization rate change trend data of the software product according to the product standardization rates corresponding to each software product in multiple preset time periods, wherein there is a time series relationship between the multiple preset time periods.

[0114] In some optional implementations of this embodiment, the above-mentioned device further includes: a strategy determination unit (not shown in the figure), which is configured to determine the development strategy of the software product according to the standardization rate change trend data.

[0115] In the present embodiment, a device for determining a product standardization rate is provided. First, the weight of the new demand data is determined according to the amount of new demand data for the software product. Then, the product standardization rate of the software product is determined according to the weight of the new demand data and the number of target software projects involving the software product. Thus, the product standardization rate can be determined based on the amount of new demand data and the number of target software projects involving the software product, thereby improving the accuracy and convenience of the product standardization rate calculation process.

[0116] According to an embodiment of the present disclosure, the present disclosure also provides an electronic device, which includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the method for determining the product standardization rate described in any of the above embodiments can be implemented when the at least one processor executes.

[0117] According to an embodiment of the present disclosure, the present disclosure further provides a readable storage medium, which stores computer instructions, and the computer instructions are used to enable a computer to implement the method for determining the product standardization rate described in any of the above embodiments when executed.

[0118] An embodiment of the present disclosure provides a computer program product, which, when executed by a processor, can implement the method for determining a product standardization rate described in any of the above embodiments.

[0119] Figure 7 A schematic block diagram of an example electronic device 700 that can be used to implement an embodiment of the present disclosure is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present disclosure described and / or required herein.

[0120] like Figure 7 As shown, the device 700 includes a computing unit 701, which can perform various appropriate actions and processes according to a computer program stored in a read-only memory (ROM) 702 or a computer program loaded from a storage unit 708 into a random access memory (RAM) 703. In the RAM 703, various programs and data required for the operation of the device 700 can also be stored. The computing unit 701, the ROM 702, and the RAM 703 are connected to each other via a bus 704. An input / output (I / O) interface 705 is also connected to the bus 704.

[0121] A number of components in the device 700 are connected to the I / O interface 705, including: an input unit 706, such as a keyboard, a mouse, etc.; an output unit 707, such as various types of displays, speakers, etc.; a storage unit 708, such as a disk, an optical disk, etc.; and a communication unit 709, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 709 allows the device 700 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0122] The computing unit 701 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the computing unit 701 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, digital signal processors (DSPs), and any appropriate processors, controllers, microcontrollers, etc. The computing unit 701 performs the various methods and processes described above, such as a method for determining a product standardization rate. For example, in some embodiments, the method for determining a product standardization rate may be implemented as a computer software program, which is tangibly contained in a machine-readable medium, such as a storage unit 708. In some embodiments, part or all of the computer program may be loaded and / or installed on the device 700 via the ROM 702 and / or the communication unit 709. When the computer program is loaded into the RAM 703 and executed by the computing unit 701, one or more steps of the method for determining a product standardization rate described above may be performed. Alternatively, in other embodiments, the computing unit 701 may be configured to perform a method for determining a product standardization rate in any other appropriate manner (e.g., by means of firmware).

[0123] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0124] The program code for implementing the method of the present disclosure can be written in any combination of one or more programming languages. These program codes can be provided to a processor or controller of a general-purpose computer, a special-purpose computer, or other programmable product standardization rate determination device, so that the program code, when executed by the processor or controller, enables the functions / operations specified in the flow chart and / or block diagram to be implemented. The program code can be executed entirely on the machine, partially on the machine, partially on the machine as a stand-alone software package and partially on a remote machine, or entirely on a remote machine or server.

[0125] In the context of the present disclosure, a machine-readable medium may be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, device, or equipment. A machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or equipment, or any suitable combination of the foregoing. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0126] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user can provide input to the computer. Other types of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, voice input, or tactile input).

[0127] The systems and techniques described herein may be implemented in a computing system that includes back-end components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes front-end components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such back-end components, middleware components, or front-end components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), and the Internet.

[0128] A computer system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The relationship between the client and the server is generated by computer programs running on the corresponding computers and having a client-server relationship with each other. The server may be a cloud server, also known as a cloud computing server or a cloud host, which is a host product in the cloud computing service system to solve the defects of difficult management and weak business scalability in traditional physical hosts and virtual private servers (VPS) services; it may also be a server for a distributed system, or a server combined with a blockchain.

[0129] According to the technical solution of the embodiment of the present disclosure, a method for determining a product standardization rate is provided. First, the weight of the new demand data is determined according to the amount of new demand data for the software product. Then, the product standardization rate of the software product is determined according to the weight of the new demand data and the number of target software projects involving the software product. Thus, the product standardization rate can be determined based on the amount of new demand data and the number of target software projects involving the software product, thereby improving the accuracy and convenience of the product standardization rate calculation process.

[0130] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps recorded in this disclosure can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solution provided by this disclosure can be achieved, and this document does not limit this.

[0131] The above specific implementations do not constitute a limitation on the protection scope of the present disclosure. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present disclosure shall be included in the protection scope of the present disclosure.

Claims

1. A method for determining a product standardization rate, comprising: Determining the weight of the newly added demand data according to the amount of the newly added demand data for the software product; A product standardization rate of the software product is determined according to the weight of the newly added demand data and the number of target software projects related to the software product.

2. The method according to claim 1, wherein: Determining the weight of the newly added demand data according to the amount of the newly added demand data for the software product includes: In response to acquiring new demand data for the software product within a preset time period, determining whether the demand data pool includes the new demand data; The response to the determination includes, based on the current weight of the new demand data in the demand data pool, increasing the weight of the new demand data in a preset manner to obtain an adjusted weight.

3. The method according to claim 2, wherein: The determining whether the demand data pool includes the newly added demand data includes: Determining characteristic data of the newly added demand data based on a preset field template; The feature data of the newly added demand data is compared with the feature data of the existing demand data in the demand data pool to determine whether the demand data pool includes the newly added demand data.

4. The method according to claim 2, wherein: The determining the weight of the newly added demand data according to the amount of the newly added demand data for the software product also includes: In response to determining that it is not included, the newly added demand data is added to the demand data pool, and an initial weight is set for the newly added demand data.

5. The method according to claim 2, wherein: Also includes: The demand data in the demand data pool are sorted according to the weights, and the sorted demand data are determined to assist target personnel in determining the requirements to be developed for the software product.

6. The method according to claim 1, wherein: Determining the product standardization rate of the software product according to the weight of the newly added demand data and the number of target software projects related to the software product includes: For a plurality of the target software projects, obtaining a weight sub-sum corresponding to the target software projects according to respective weights of at least one newly added requirement data corresponding to the software products in the target software projects; Obtaining a weight sum according to a plurality of weight sub-sums corresponding to a plurality of target software projects one by one; A product standardization rate of the software product is determined according to the weight sum and the number of the target software items.

7. The method according to any one of claims 1 to 6, wherein: Also includes: According to the product standardization rates corresponding to the software product in a plurality of preset time periods, standardization rate change trend data of the software product is determined, wherein the plurality of preset time periods have a time series relationship.

8. The method according to claim 7, wherein: Also includes: The development strategy of the software product is determined according to the standardization rate change trend data.

9. A device for determining a product standardization rate, comprising: A weight determination unit, configured to determine the weight of the newly added demand data according to the amount of the newly added demand data for the software product; The standardization rate determination unit is configured to determine the product standardization rate of the software product according to the weight of the newly added demand data and the number of target software projects related to the software product.

10. The device according to claim 9, wherein: The weight determination unit is further configured to: Within a preset time period, in response to obtaining new demand data for the software product, determine whether the new demand data is included in the demand data pool; in response to determining that it is included, based on the current weight of the new demand data in the demand data pool, increase the weight of the new demand data based on a preset method to obtain an adjusted weight.

11. The device according to claim 10, wherein: The weight determination unit is further configured to: Based on a preset field template, characteristic data of the newly added demand data is determined; and the characteristic data of the newly added demand data is compared with characteristic data of existing demand data in the demand data pool to determine whether the demand data pool includes the newly added demand data.

12. The device according to claim 10, wherein: The weight determination unit is further configured to: In response to determining that it is not included, the newly added demand data is added to the demand data pool, and an initial weight is set for the newly added demand data.

13. The device according to claim 10, wherein: Also includes: The sorting unit is configured to sort the demand data in the demand data pool according to the weights, and determine sorted demand data to assist target personnel in determining the requirements to be developed for the software product.

14. The device according to claim 9, wherein: The normalization rate determination unit is further configured to: For multiple target software projects, a weight sub-sum corresponding to the target software project is obtained according to each weight of at least one newly added requirement data corresponding to the software product in the target software project; a weight sum is obtained according to multiple weight sub-sums corresponding to the multiple target software projects one by one; and a product standardization rate of the software product is determined according to the weight sum and the number of the target software projects.

15. The device according to any one of claims 9 to 14, wherein: Also includes: The trend determination unit is configured to determine the standardization rate change trend data of the software product according to the product standardization rates corresponding to each of the software products in a plurality of preset time periods, wherein the plurality of preset time periods have a time series relationship.

16. The device according to claim 15, wherein: Also includes: The strategy determination unit is configured to determine the development strategy of the software product according to the normalization rate change trend data.

17. An electronic device, characterized in that: include: at least one processor; as well as a memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the method according to any one of claims 1 to 8.

18. A non-transitory computer-readable storage medium storing computer instructions, characterized in that: The computer instructions are used to cause the computer to execute the method according to any one of claims 1 to 8.

19. A computer program product comprising: A computer program which, when executed by a processor, implements the method according to any one of claims 1 to 8.

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