Method, device, medium and product for evaluating the production effect of software requirements

Abstract

The application provides a software requirement production effect evaluation method, device, equipment, computer readable storage medium and computer program product, which can be applied to the financial technology field. The method comprises the following steps: determining the requirement type of a to-be-evaluated requirement item and an evaluation index corresponding to the requirement item; wherein the evaluation index comprises a business index and a user behavior index; obtaining an index target value and an index actual value of each evaluation index within a first time length; determining an index baseline value of each evaluation index within the first time length according to the requirement type; determining a weight coefficient corresponding to each evaluation index based on the first time length and a time decay function; wherein the weight coefficient corresponding to the user behavior index decreases as the first time length increases, and the weight coefficient corresponding to the business index increases as the first time length increases; and determining an evaluation result of the requirement item according to the index target value, the index baseline value, the index actual value and the weight coefficient.

Description

Technical Field

[0001] This application relates to the field of financial technology, and in particular to a method, apparatus, device, computer-readable storage medium, and computer program product for evaluating the effectiveness of software requirements in production. Background Technology

[0002] Currently, evaluating the effectiveness of software requirements after deployment remains a significant challenge for enterprises. With the increasing adoption of agile development and continuous delivery models, the delivery frequency of software requirements is constantly rising. Objectively and accurately assessing the actual effectiveness of each requirement after deployment or launch has become a crucial step for enterprises to optimize R&D resource allocation and improve product decision-making efficiency.

[0003] In related technologies, qualitative assessments are usually conducted based on human experience. The assessment results of such methods are highly dependent on the personal experience and subjective judgment of the requirements analyst or product manager, and lack unified and quantitative assessment standards, which affects the accuracy of the assessment results. Summary of the Invention

[0004] This application provides a method, apparatus, device, computer-readable storage medium, and computer program product for evaluating the effectiveness of software requirements in production.

[0005] In a first aspect, embodiments of this application provide a method for evaluating the effectiveness of software requirement deployment, including: Determine the demand type of the demand item to be evaluated and the corresponding evaluation indicators; wherein, the evaluation indicators include business indicators and user behavior indicators, the business indicators are determined based on the business effectiveness data brought by the demand item, and the user behavior indicators are determined based on the user's interaction behavior data with the demand item. Obtain the target value and actual value of each evaluation indicator within a first time period; wherein, the first time period is the time between the production launch time of the demand item and the current evaluation time. Based on the demand type, determine the baseline value of each evaluation indicator within the first time period; wherein, the baseline value of the indicator serves as the comparison benchmark after the demand item is put into production; The weight coefficients corresponding to each evaluation indicator are determined based on the first duration and the time decay function; wherein, the weight coefficients corresponding to the user behavior indicators decrease as the first duration increases, and the weight coefficients corresponding to the business indicators increase as the first duration increases; The evaluation result of the requirement item is determined based on the target value of the indicator, the baseline value of the indicator, the actual value of the indicator, and the weighting coefficient.

[0006] Secondly, embodiments of this application provide an apparatus for evaluating the effectiveness of software requirement deployment, comprising: The processing module is used to determine the requirement type of the requirement item to be evaluated and the evaluation index corresponding to the requirement item; wherein, the evaluation index includes business indicators and user behavior indicators, the business indicators are determined based on the business effectiveness data brought by the requirement item, and the user behavior indicators are determined based on the user's interaction behavior data with the requirement item. The acquisition module is used to acquire the target value and actual value of each evaluation indicator within a first time period; wherein, the first time period is the time between the production launch time of the demand item and the current evaluation time. The processing module is further configured to determine the baseline value of each evaluation indicator within the first time period according to the demand type; wherein the baseline value of the indicator serves as a comparison benchmark after the demand item is put into production. The processing module is further configured to determine the weight coefficients corresponding to each evaluation indicator based on the first duration and the time decay function; wherein, the weight coefficients corresponding to the user behavior indicators decrease as the first duration increases, and the weight coefficients corresponding to the business indicators increase as the first duration increases; The processing module is further configured to determine the evaluation result of the requirement item based on the target value of the indicator, the baseline value of the indicator, the actual value of the indicator, and the weighting coefficient.

[0007] Thirdly, embodiments of this application provide an electronic device, including a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the steps of the evaluation method for the production effectiveness of software requirements provided in the first aspect of embodiments of this application.

[0008] Fourthly, embodiments of this application provide a computer-readable storage medium having a computer program stored thereon, wherein when the computer program is executed by a processor, it implements the steps of the method for evaluating the deployment effect of software requirements provided in the first aspect of embodiments of this application.

[0009] Fifthly, embodiments of this application provide a computer program product having a computer program stored thereon, wherein when the computer program is executed by a processor, it implements the steps of the evaluation method for the production effect of software requirements provided in the first aspect of embodiments of this application.

[0010] The technical solution provided in this application, by acquiring the target value, baseline value, and actual value of the indicators and comprehensively determining the evaluation result based on the weighting coefficients, achieves an objective and quantitative evaluation of the production effect of demand items in a data-driven manner, thereby improving the accuracy of the evaluation results. For different demand types, the baseline value of each evaluation indicator is determined, and the baseline value is used as a comparison benchmark to isolate the influence of external environmental factors on the evaluation results. This allows for precise quantification of the incremental effect brought by the demand item itself, further improving the accuracy of the evaluation results. In addition, by introducing a time decay function, the weighting coefficients of each evaluation indicator are dynamically adjusted based on the length of time after the demand item is put into production. This enables the evaluation results of the demand item to adaptively match the evaluation focus of the demand item at different life cycle stages, so as to carry out targeted optimization of the demand item in the future. Attached Figure Description

[0011] Figure 1 A flowchart illustrating a method for evaluating the deployment effectiveness of software requirements provided in an embodiment of this application; Figure 2 Another flowchart illustrating the method for evaluating the deployment effectiveness of software requirements provided in this application embodiment; Figure 3 A schematic diagram of a device for evaluating the deployment effect of software requirements provided in an embodiment of this application; Figure 4 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Detailed Implementation

[0012] To make the objectives, technical solutions, and advantages of this application clearer, the technical solutions in the embodiments of this application will be further described in detail below with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are only for explaining this application and are not intended to limit this application. Those skilled in the art can make adjustments as needed to suit specific application scenarios. Furthermore, it should be noted that, for ease of description, only the parts related to this application are shown in the accompanying drawings, not the entire structure.

[0013] It should be noted that the method provided in this application embodiment can be executed by a software requirement production effect evaluation device. This device can be implemented by software and / or hardware and can be integrated into electronic devices, such as personal computer devices, portable devices or servers. This application embodiment does not limit the specific type of electronic device.

[0014] In addition, it should be noted that the information collected in the embodiments of this application is all information and data authorized by the user or fully authorized by all parties. The collection, storage, use, processing, transmission, provision, disclosure and application of the relevant data all comply with the relevant laws, regulations and standards of the relevant countries and regions, necessary confidentiality measures have been taken, and they do not violate public order and good morals. Corresponding operation entry points are provided for users to choose to authorize or refuse.

[0015] The key terms used in the following embodiments are explained below: Requirement item: refers to the functional module, business scenario, or technical improvement item that needs to be implemented during the software development process. In the embodiments of this application, the requirement item is the smallest independent unit for effect evaluation, and can be divided into new requirement items and optimization requirement items according to their nature.

[0016] Business metrics: Quantitative parameters used to characterize the business output of a demand item. They are determined based on the business performance data brought about by the demand item. Business metrics include, but are not limited to, business transaction volume, transaction success rate, business conversion rate, etc.

[0017] User behavior metrics are quantitative data that reflect the characteristics of user interaction. They are determined based on the interactive behavior data generated by users in response to their needs. User behavior metrics include, but are not limited to, page views, number of unique visitors, click-through rate, page dwell time, and frequency of function use.

[0018] Baseline value of indicators: The indicator value used as the benchmark for evaluating the effect of demand items after they are put into production. It is determined separately for new demand items and optimization demand items.

[0019] Target value of the indicator: The threshold of the effect expected to be achieved after the demand item is put into production.

[0020] Figure 1 This is a flowchart illustrating a method for evaluating the deployment effectiveness of software requirements as provided in an embodiment of this application. Figure 1 As shown, the method may include: S101. Determine the demand type and corresponding evaluation indicators for the demand items to be evaluated.

[0021] Specifically, a software program may include one or more requirement items. In one embodiment, all requirement items included in the software can be used as requirement items to be evaluated, or one or some requirement items can be used as requirement items to be evaluated based on the actual evaluation requirements. Further, based on the tag information or preset configuration information of the requirement items to be evaluated, the requirement type of the requirement items to be evaluated is automatically identified, such as determining whether the requirement items to be evaluated are new requirements or optimization requirements. New requirements can be understood as functions added from scratch, while optimization requirements can be understood as functions formed by further optimization or improvement of existing functions.

[0022] Whether it's a new requirement or an optimization requirement, it's proposed to achieve a certain purpose or solve a specific problem. Therefore, during the requirement issuance phase, the goal of the requirement can be quantitatively estimated, and the goal and intent can be quantified. That is, for each requirement, at least one business indicator and user behavior indicator should be configured, specifically configuring the attribute definitions, data source mapping relationships, and calculation methods of the indicators. Business indicators are determined based on the business performance data brought by the requirement, including but not limited to business transaction volume, transaction success rate, and business conversion rate. User behavior indicators are determined based on user interaction data related to the requirement, including but not limited to page views, unique visitors, click-through rate, page dwell time, and function usage frequency. When evaluating a requirement, the pre-configured business indicators and user behavior indicators for that requirement are obtained.

[0023] For example, for a promotional activity feature in the software, the desired return on investment is to both increase users and bring actual business growth. Therefore, at least two metrics can be configured for this feature, such as average daily user visits (a user behavior metric) and average daily spending (a business metric).

[0024] S102. Obtain the target value and actual value of each evaluation indicator within the first time period.

[0025] Specifically, before a requirement item is put into production or launched, requirement analysts will set target values ​​for each evaluation indicator based on business expectations and store these target values ​​as part of the requirement item's configuration information. The first duration is the time between the requirement item's production launch time and the current evaluation time; that is, the length of time the requirement item has been running since its launch. When evaluating a requirement item, the preset target values ​​for each evaluation indicator are read from the requirement item's configuration information, and the actual values ​​of each evaluation indicator are calculated based on the first duration, including actual values ​​of business indicators and actual values ​​of user behavior indicators.

[0026] In one embodiment, obtaining the actual value of each evaluation indicator within a first time period may include: for each evaluation indicator, determining the data source corresponding to the evaluation indicator from the business transaction system or the data tracking system based on the attribute information of the evaluation indicator; extracting the raw data generated by the demand item within the first time period from the data source; and processing the raw data according to the calculation method corresponding to the evaluation indicator to obtain the actual value of the indicator.

[0027] The actual values ​​of business metrics are calculated based on the business performance data resulting from the demand items. This performance data originates from business transaction systems (such as order databases and payment systems). The actual values ​​of user behavior metrics are calculated based on user interaction data related to the demand items. This interaction data originates from tracking systems (such as user behavior logs and page visit records). Based on the data source mapping relationships in the configuration information of each evaluation metric, the raw data for the first time period is extracted from the corresponding data sources. The raw data is then processed according to the calculation method corresponding to each evaluation metric to obtain the actual values ​​of each evaluation metric. Optionally, after obtaining the raw data, it can also be cleaned, denoised, and standardized.

[0028] S103. Determine the baseline values ​​of each evaluation indicator within the first time period based on the type of demand.

[0029] The baseline value of the indicator serves as a benchmark for comparison after the demand item is put into production. It is used to compare with the actual value of the indicator to measure the incremental change of the actual production effect of the demand item relative to the situation where "the demand was not implemented". This removes the interference of external environmental factors (such as natural growth, seasonal fluctuations, etc.) on the evaluation results, so that the evaluation results can accurately reflect the true contribution of the demand item itself after optimization.

[0030] For new and optimized requirements, corresponding baseline values ​​for the indicators are determined. In one embodiment, for new requirements, since the requirement is a completely new feature and there is no corresponding historical data, the baseline value of each evaluation indicator is set to 0 for the first time period. For optimized requirements, since the function corresponding to the requirement has been running for a period of time, there is historical data before optimization, so the baseline value of the indicator can be determined based on the historical data. In one example, for each evaluation indicator, the historical values ​​of the indicator before optimization are obtained for multiple historical time periods, and the average of the historical values ​​of the indicator over multiple historical time periods is determined as the baseline value of the evaluation indicator.

[0031] S104. Determine the weight coefficients corresponding to each evaluation index based on the first duration and the time decay function.

[0032] The evaluation focus differs at different stages of a requirement's lifecycle after deployment. In the initial stage of deployment, the accumulation of user behavior is the foundation for business effectiveness, so the evaluation focuses on the completion of user behavior metrics (such as page views, unique visitors, and feature usage frequency). As the requirement's runtime increases and the user base stabilizes, the evaluation gradually shifts to the completion of business metrics (such as transaction volume and transaction success rate) to measure the business effectiveness brought by the requirement.

[0033] Therefore, the weight coefficients of each evaluation indicator can be dynamically adjusted based on the first duration and the time decay function. Specifically, the weight coefficients corresponding to user behavior indicators decrease as the first duration increases, meaning the evaluation gradually reduces its focus on the completion of user behavior indicators; the weight coefficients corresponding to business indicators increase as the first duration increases, meaning the evaluation gradually increases its focus on the completion of business indicators.

[0034] In one embodiment, the weighting coefficients corresponding to user behavior metrics can be determined using the following formula or a variation thereof. : ; Furthermore, the weighting coefficients corresponding to the business indicators are determined using the following formula or a variation thereof. : ; in, , To adjust the parameters, The decay rate coefficient, This is the first duration.

[0035] S105. Determine the evaluation results of the demand items based on the target value, baseline value, actual value and weighting coefficient of the indicators.

[0036] Specifically, the target value of the indicator reflects the expected effect of the demand item's implementation, the actual value reflects the actual performance after implementation, the baseline value serves as a comparison benchmark to measure the change of the demand item relative to the "not implemented" or "zero-based" state, and the weighting coefficient reflects the importance of different evaluation indicators at the current assessment stage. For each evaluation indicator, the completion status is determined based on the target value, baseline value, and actual value. The completion status of each evaluation indicator is aggregated according to the corresponding weighting coefficient to obtain the evaluation result of the demand item. This evaluation result can be a numerical comprehensive score to quantify the overall achievement of the demand item's implementation effect; or it can be a level or status indicator determined according to the comprehensive score and preset rules to reflect the quality level of the demand item's implementation effect.

[0037] The software requirement deployment effectiveness evaluation method provided in this embodiment obtains the target value, baseline value, and actual value of the indicators and determines the evaluation result based on weight coefficients. This data-driven approach achieves an objective and quantitative evaluation of the deployment effectiveness of requirement items, improving the accuracy of the evaluation results. For different requirement types, baseline values ​​for each evaluation indicator are determined. Using these baseline values ​​as a comparison benchmark, the influence of external environmental factors on the evaluation results is eliminated, thereby accurately quantifying the incremental effect brought by the requirement item itself and further improving the accuracy of the evaluation results. In addition, by introducing a time decay function, the weight coefficients of each evaluation indicator are dynamically adjusted based on the length of time after the requirement item is deployed. This allows the evaluation results of the requirement item to adaptively match the evaluation focus of the requirement item at different life cycle stages, enabling subsequent targeted optimization of the requirement item.

[0038] In one embodiment, when the requirement to be evaluated is a new type of requirement, the baseline value of each evaluation indicator is set to 0 within a first time period; the process of determining the evaluation result of the requirement based on the indicator target value, indicator baseline value, indicator actual value and weight coefficient may include: for each evaluation indicator, determining the completion degree of the evaluation indicator based on the indicator actual value and indicator target value; and determining the evaluation result of the requirement based on the completion degree of each evaluation indicator and its corresponding weight coefficient.

[0039] In one example, the ratio between the actual value of an evaluation indicator and its target value can be used to determine the completion rate of that evaluation indicator. Furthermore, the completion rates of each evaluation indicator are weighted and summed according to the weight coefficients corresponding to each evaluation indicator to obtain the evaluation result of the requirement item to be evaluated.

[0040] For example, the completion rate of evaluation indicators can be determined using the following formula or a variation thereof: ; in, Let i be the completion rate of the i-th evaluation indicator. Let i be the actual value of the i-th evaluation indicator. Let be the target value of the i-th evaluation indicator.

[0041] For example, the evaluation result of the requirement item to be evaluated can be determined by the following formula or a variation thereof: ; Where n is the number of evaluation indicators involved in the demand item. Let be the weight coefficient corresponding to the i-th evaluation index. This represents the evaluation results for the requirement items.

[0042] In one embodiment, when the requirement to be evaluated is an optimization requirement, the baseline value of each evaluation indicator in the first time period can be determined by the following process: obtaining the historical values ​​of each evaluation indicator of the requirement before optimization; processing the historical values ​​of the indicators by a preset time series prediction algorithm to obtain the predicted values ​​of each evaluation indicator in the first time period without requirement optimization; and determining the predicted values ​​of the indicators as the baseline values ​​of the corresponding evaluation indicators.

[0043] For optimization-related requirements, since the function corresponding to the requirement has been running for a period of time and there is historical data before optimization, we can obtain the historical values ​​of each evaluation indicator of the requirement in multiple historical time periods before optimization. Based on the time series prediction algorithm and the historical values ​​of the indicators in multiple historical time periods, we can predict the value of the evaluation indicator in the first time period, and obtain the value that the evaluation indicator should have reached in the first time period after production without the requirement optimization. The obtained indicator prediction value is used as the indicator baseline value of the evaluation indicator.

[0044] Furthermore, such as Figure 2 As shown, for optimization-type requirements, the process of determining the evaluation result of the requirement item based on the target value, baseline value, actual value, and weighting coefficient can include: S201. For each evaluation indicator, determine the actual incremental value of the evaluation indicator based on the actual value of the indicator and the baseline value of the indicator.

[0045] S202. Determine the target increment value of the evaluation indicator based on the target value and baseline value of the evaluation indicator.

[0046] S203. Determine the completion rate of the evaluation indicators based on the actual incremental value and the target incremental value.

[0047] S204. Determine the evaluation results of the requirements based on the completion rate of each evaluation indicator and its corresponding weight coefficient.

[0048] In one example, the difference between the actual value of the evaluation indicator and the baseline value of the indicator can be determined as the actual incremental value of the evaluation indicator, the difference between the target value of the evaluation indicator and the baseline value of the indicator can be determined as the target incremental value of the evaluation indicator, and the ratio between the actual incremental value and the target incremental value can be determined as the completion rate of the evaluation indicator. Furthermore, the completion rates of each evaluation indicator are weighted and summed according to the weight coefficients corresponding to each evaluation indicator to obtain the evaluation result of the demand item to be evaluated.

[0049] For example, the completion rate of evaluation indicators can be determined using the following formula or a variation thereof: ; in, Let i be the completion rate of the i-th evaluation indicator. Let i be the baseline value of the i-th evaluation indicator. Let i be the actual value of the i-th evaluation indicator. Let be the target value of the i-th evaluation indicator.

[0050] For example, the evaluation result of the requirement item to be evaluated can be obtained through the following formula or a variation of the formula: ; Where n is the number of evaluation indicators involved in the demand item. Let be the weight coefficient corresponding to the i-th evaluation index. This represents the evaluation results for the requirement items.

[0051] In this embodiment, the completion rate of evaluation indicators is calculated using absolute value and incremental methods for new and optimized requirements, respectively: For new requirements, the baseline value of the indicator is set to 0, and the completion rate is determined based on the absolute value of the actual indicator value and the target indicator value; for optimized requirements, the actual incremental value and the target incremental value are calculated using the predicted baseline value of the indicator, and the completion rate is determined based on the incremental value. This differentiated evaluation method avoids misjudging the existing values ​​of existing indicators in optimized requirements as the incremental effect brought about by the current optimization, thus ensuring that the evaluation results accurately reflect the true contribution of the requirement items, while also making the evaluation results of different types of requirements horizontally comparable.

[0052] In one embodiment, when the evaluation result does not meet the preset conditions, a target evaluation indicator that has a negative impact on the evaluation result is determined from the evaluation indicators corresponding to the requirement item; optimization suggestions for the requirement item are generated based on the target evaluation indicator, and the optimization suggestions are output to the user terminal.

[0053] Specifically, when the evaluation result is determined not to meet the preset conditions, a target evaluation indicator that negatively impacts the evaluation result is identified from the evaluation indicators corresponding to the requirement item. In one optional implementation, the completion degree of each evaluation indicator is compared with a preset completion degree threshold. When the completion degree of an evaluation indicator is less than the preset completion degree threshold, that evaluation indicator is identified as a target evaluation indicator that negatively impacts the evaluation result. In another optional implementation, a comprehensive judgment is made by combining the weight coefficient and completion degree of each evaluation indicator, and the contribution of each evaluation indicator is calculated (e.g., contribution degree = (completion degree - 1) × weight coefficient). When the contribution degree is negative, it indicates that the evaluation indicator has a dragging effect on the evaluation result, and this evaluation indicator can be identified as the target evaluation indicator. This method can more accurately locate the target evaluation indicator that has the greatest drag on the evaluation result (such as the evaluation indicator with the lowest completion degree and the highest weight coefficient), avoiding attribution bias caused by different weights of evaluation indicators.

[0054] After identifying the target evaluation metric, corresponding optimization suggestions can be generated based on this metric using a pre-established knowledge base. This knowledge base can include a mapping relationship between evaluation metrics and optimization suggestion templates. Different evaluation metrics and their different completion ranges correspond to different optimization suggestion templates. After identifying the target evaluation metric, optimization suggestions are matched based on the completion status of the target evaluation metric and the above mapping relationship. For example, when the target evaluation metric is "page dwell time," the optimization suggestion matched based on the knowledge base would be "suggest optimizing page content quality or interactive experience to increase user dwell time." After generating the optimization suggestion, it is output to the user end for requirements analysts to refer to in developing targeted improvement measures.

[0055] Figure 3 This is a schematic diagram of a device for evaluating the deployment effectiveness of software requirements, provided in an embodiment of this application. Figure 3 As shown, the device may include a processing module 301 and an acquisition module 302.

[0056] Specifically, the processing module 301 is used to determine the demand type of the demand item to be evaluated and the corresponding evaluation indicators; among which, the evaluation indicators include business indicators and user behavior indicators. The business indicators are determined based on the business effectiveness data brought by the demand item, and the user behavior indicators are determined based on the user's interaction behavior data with the demand item. The acquisition module 302 is used to acquire the target value and actual value of each evaluation indicator within a first time period; wherein, the first time period is the time between the production launch time of the demand item and the current evaluation time. The processing module 301 is also used to determine the baseline value of each evaluation indicator within the first time period according to the demand type; wherein the baseline value of the indicator serves as the comparison benchmark after the demand item is put into production. The processing module 301 is also used to determine the weight coefficients corresponding to each evaluation indicator based on the first duration and the time decay function; wherein, the weight coefficients corresponding to user behavior indicators decrease as the first duration increases, and the weight coefficients corresponding to business indicators increase as the first duration increases; The processing module 301 is also used to determine the evaluation result of the requirement item based on the target value of the indicator, the baseline value of the indicator, the actual value of the indicator and the weight coefficient.

[0057] Optionally, based on the above embodiments, the processing module 301 is further configured to set the baseline value of each evaluation indicator within the first time period to 0 when the demand type is a new type demand.

[0058] Based on the above embodiments, optionally, the processing module 301 is further configured to determine the completion degree of each evaluation indicator based on the actual value and target value of the evaluation indicator; and to determine the evaluation result of the requirement item based on the completion degree of each evaluation indicator and its corresponding weight coefficient.

[0059] Based on the above embodiments, optionally, the processing module 301 is further configured to, when the demand type is an optimization demand, obtain the historical values ​​of each evaluation indicator of the demand item before optimization; process the historical values ​​of the indicators through a preset time series prediction algorithm to obtain the predicted values ​​of each evaluation indicator of the demand item within a first time period without demand optimization; and determine the predicted values ​​of the indicators as the baseline values ​​of the corresponding evaluation indicators.

[0060] Based on the above embodiments, optionally, the processing module 301 is further configured to, for each evaluation indicator, determine the actual incremental value of the evaluation indicator based on the actual value of the evaluation indicator and the baseline value of the evaluation indicator; determine the target incremental value of the evaluation indicator based on the target value of the evaluation indicator and the baseline value of the evaluation indicator; determine the completion degree of the evaluation indicator based on the actual incremental value and the target incremental value; and determine the evaluation result of the requirement item based on the completion degree of each evaluation indicator and its corresponding weight coefficient.

[0061] Based on the above embodiments, optionally, the processing module 301 is further configured to determine the target evaluation index that has a negative impact on the evaluation result from the evaluation index corresponding to the requirement item when the evaluation result does not meet the preset conditions; generate optimization suggestions for the requirement item according to the target evaluation index; and output the optimization suggestions to the user terminal.

[0062] Optionally, based on the above embodiments, the acquisition module 302 is further configured to, for each evaluation indicator, determine the data source corresponding to the evaluation indicator from the business transaction system or the data tracking system according to the attribute information of the evaluation indicator; extract the original data generated by the demand item within the first time period from the data source; and process the original data according to the calculation method corresponding to the evaluation indicator to obtain the actual value of the indicator.

[0063] Figure 4 A schematic diagram of the structure of an electronic device provided in an embodiment of this application, such as... Figure 4 As shown, the device includes a processor 40, a memory 41, an input device 42, and an output device 43; the number of processors 40 in the device can be one or more. Figure 4 Taking a processor 40 as an example; the processor 40, memory 41, input device 42, and output device 43 in this device can be connected via a bus or other means. Figure 4 Taking the example of a connection between China and Israel via a bus.

[0064] The memory 41, as a computer-readable storage medium, can be used to store software programs, computer-executable programs, and modules, such as the program instructions / modules corresponding to the software requirement deployment effectiveness evaluation method in the embodiments of this application (e.g., the processing module 301 and the acquisition module 302 in the software requirement deployment effectiveness evaluation device). The processor 40 executes various functional applications and data processing of the device by running the software programs, instructions, and modules stored in the memory 41, thereby realizing the aforementioned software requirement deployment effectiveness evaluation method.

[0065] The memory 41 may primarily include a program storage area and a data storage area. The program storage area may store the operating system and at least one application program required for a given function; the data storage area may store data involved in evaluating the effectiveness of software requirements for deployment. Furthermore, the memory 41 may include high-speed random access memory and non-volatile memory, such as at least one disk storage device, flash memory, or other non-volatile solid-state storage device. In some instances, the memory 41 may further include memory remotely located relative to the processor 40, which can be connected to a device / terminal / server via a network. Examples of such networks include, but are not limited to, the Internet, intranets, local area networks, mobile communication networks, and combinations thereof.

[0066] Input device 42 can be used to receive input digital or character information, and to generate key signal inputs related to user settings and function control of the electronic device. Output device 43 may include display devices such as a display screen.

[0067] In one embodiment, a computer-readable storage medium is also provided, on which a computer program is stored, wherein when the computer program is executed by a processor, the steps of the method for evaluating the deployment effect of software requirements provided in any of the above embodiments are implemented.

[0068] In one embodiment, a computer program product is also provided, on which a computer program is stored, and when the computer program is executed by a processor, it implements the steps of the evaluation method for the production effectiveness of software requirements provided in any of the above embodiments.

[0069] The software requirement deployment effect evaluation apparatus, electronic device, computer-readable storage medium, and computer program product provided in the above embodiments can execute the software requirement deployment effect evaluation method provided in any embodiment of this application, and have the corresponding functional modules and beneficial effects for executing the method. Technical details not described in detail in the above embodiments can be found in the software requirement deployment effect evaluation method provided in any embodiment of this application.

[0070] Based on the above description of the implementation methods, those skilled in the art can clearly understand that this application can be implemented using software and necessary general-purpose hardware, and of course, it can also be implemented using hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as a computer floppy disk, read-only memory, random access memory, flash memory, hard disk, or optical disk, and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods of the various embodiments of this application.

[0071] It is worth noting that the units and modules included in the above embodiments are only divided according to functional logic, but are not limited to the above division, as long as the corresponding functions can be achieved; in addition, the specific names of each functional unit are only for easy differentiation and are not used to limit the scope of protection of this application.

[0072] Note that the above description is merely a preferred embodiment and the technical principles employed in this application. Those skilled in the art will understand that this application is not limited to the specific embodiments described herein, and various obvious changes, readjustments, and substitutions can be made without departing from the scope of protection of this application. Therefore, although this application has been described in detail through the above embodiments, this application is not limited to the above embodiments. Many other equivalent embodiments may be included without departing from the concept of this application, and the scope of this application is determined by the scope of the appended claims.

Claims

1. A method for evaluating the effectiveness of software requirement deployment, characterized in that, include: Determine the demand type of the demand item to be evaluated and the corresponding evaluation indicators; wherein, the evaluation indicators include business indicators and user behavior indicators, the business indicators are determined based on the business effectiveness data brought by the demand item, and the user behavior indicators are determined based on the user's interaction behavior data with the demand item. Obtain the target value and actual value of each evaluation indicator within a first time period; wherein, the first time period is the time between the production launch time of the demand item and the current evaluation time. Based on the demand type, determine the baseline value of each evaluation indicator within the first time period; wherein, the baseline value of the indicator serves as the comparison benchmark after the demand item is put into production; The weight coefficients corresponding to each evaluation indicator are determined based on the first duration and the time decay function; wherein, the weight coefficients corresponding to the user behavior indicators decrease as the first duration increases, and the weight coefficients corresponding to the business indicators increase as the first duration increases; The evaluation result of the requirement item is determined based on the target value of the indicator, the baseline value of the indicator, the actual value of the indicator, and the weighting coefficient.

2. The method according to claim 1, characterized in that, Based on the aforementioned demand type, determine the baseline values ​​of each evaluation indicator within the first time period, including: When the demand type is a new demand, the baseline value of each evaluation indicator within the first time period is set to 0.

3. The method according to claim 2, characterized in that, Based on the target value of the indicator, the baseline value of the indicator, the actual value of the indicator, and the weighting coefficient, the evaluation result of the requirement item is determined, including: For each evaluation indicator, the degree of completion of the evaluation indicator is determined based on the actual value and the target value of the indicator. The evaluation result of the requirement item is determined based on the completion degree of each evaluation indicator and its corresponding weight coefficient.

4. The method according to claim 1, characterized in that, Based on the aforementioned demand type, determine the baseline values ​​of each evaluation indicator within the first time period, including: When the requirement type is an optimization requirement, obtain the historical values ​​of each evaluation indicator of the requirement item before optimization; The historical values ​​of the indicators are processed by a preset time series prediction algorithm to obtain the predicted values ​​of each evaluation indicator of the demand item within the first time period without demand optimization. The predicted value of the indicator is determined as the baseline value of the corresponding evaluation indicator.

5. The method according to claim 4, characterized in that, Based on the target value of the indicator, the baseline value of the indicator, the actual value of the indicator, and the weighting coefficient, the evaluation result of the requirement item is determined, including: For each evaluation indicator, the actual incremental value of the evaluation indicator is determined based on the actual value of the indicator and the baseline value of the indicator; the target incremental value of the evaluation indicator is determined based on the target value of the indicator and the baseline value of the indicator; and the completion rate of the evaluation indicator is determined based on the actual incremental value and the target incremental value. The evaluation result of the requirement item is determined based on the completion degree of each evaluation indicator and its corresponding weight coefficient.

6. The method according to claim 1, characterized in that, Also includes: When the evaluation result does not meet the preset conditions, a target evaluation indicator that has a negative impact on the evaluation result is determined from the evaluation indicators corresponding to the requirement item. Optimization suggestions for the required items are generated based on the target evaluation indicators, and the optimization suggestions are output to the user.

7. The method according to claim 1, characterized in that, The process of obtaining the actual values ​​of each evaluation indicator within the first time period includes: For each evaluation indicator, the data source corresponding to the evaluation indicator is determined from the business transaction system or the data tracking system based on the attribute information of the evaluation indicator. Extract the original data generated by the demand item within the first time period from the data source; The original data is processed according to the calculation method corresponding to the evaluation index to obtain the actual value of the index.

8. An electronic device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 7.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 7.

10. A computer program product having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 7.

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