Project delivery risk early warning method, device and equipment and storage medium

Abstract

The invention discloses a project delivery risk early warning method, device and equipment and a storage medium, and belongs to the technical field of artificial intelligence, and the method comprises the steps: obtaining at least one to-be-delivered demand item corresponding to a to-be-delivered project; inputting the to-be-delivered demand item into the quality evaluation model to obtain a quality evaluation result of the to-be-delivered demand item; wherein the quality evaluation model is composed of a quality evaluation index, an index weight and an index evaluation rule; and according to the quality evaluation result of each to-be-delivered demand item, carrying out delivery risk early warning on the to-be-delivered item. The project delivery risk can be recognized in advance before the project is delivered, project research and development personnel are helped to find and solve the project delivery risk in time, the project delivery quality is improved, the situation that the project needs to be returned to a research and development department to be repaired due to the quality problem in the test stage is avoided, the project repair cost and time are reduced, and the project repair efficiency is improved. And the project test period is shortened.

Description

Technical Field

[0001] The present invention relates to the field of artificial intelligence technology, and in particular, to a method, device, equipment and storage medium for early warning of project delivery risks. Background Art

[0002] Regarding project delivery, currently, it is impossible to understand in advance whether there are delivery risks in the project before delivering the project from the R & D department to the testing department. Therefore, it is impossible to resolve risks in a timely manner during the project R & D stage, which affects the project delivery quality, increases the project repair cost and time, and prolongs the project testing cycle.

[0003] Therefore, how to identify project delivery risks in advance before project delivery has become an urgent problem to be solved. Summary of the Invention

[0004] The present invention provides a method, device, equipment and storage medium for early warning of project delivery risks, so as to identify project delivery risks in advance before project delivery, thereby improving the project delivery quality, reducing the project repair cost and time, and shortening the project testing cycle.

[0005] According to one aspect of the present invention, there is provided a method for early warning of project delivery risks, the method comprising:

[0006] Obtaining at least one to-be-delivered requirement item corresponding to the to-be-delivered project;

[0007] Inputting the to-be-delivered requirement item into a quality evaluation model to obtain a quality evaluation result of the to-be-delivered requirement item; wherein, the quality evaluation model is composed of quality evaluation indicators, index weights and index evaluation rules;

[0008] Performing a delivery risk early warning on the to-be-delivered project according to the quality evaluation results of the to-be-delivered requirement items.

[0009] According to another aspect of the present invention, there is provided a device for early warning of project delivery risks, the device comprising:

[0010] A to-be-delivered requirement item obtaining module, configured to obtain at least one to-be-delivered requirement item corresponding to the to-be-delivered project;

[0011] A quality evaluation result determining module, configured to input the to-be-delivered requirement item into a quality evaluation model to obtain a quality evaluation result of the to-be-delivered requirement item; wherein, the quality evaluation model is composed of quality evaluation indicators, index weights and index evaluation rules;

[0012] A delivery risk early warning module, configured to perform a delivery risk early warning on the to-be-delivered project according to the quality evaluation results of the to-be-delivered requirement items.

[0013] According to another aspect of the present invention, there is provided an electronic device, which includes:

[0014] at least one processor; and

[0015] a memory communicatively connected to the at least one processor; wherein,

[0016] the memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor to enable the at least one processor to execute the project delivery risk warning method according to any embodiment of the present invention.

[0017] According to another aspect of the present invention, there is provided a computer-readable storage medium storing computer instructions for causing a processor to implement the project delivery risk warning method according to any embodiment of the present invention when executed.

[0018] According to another aspect of the present invention, there is provided a computer program product including a computer program, which implements the project delivery risk warning method according to any embodiment of the present invention when executed by a processor.

[0019] The technical solution of the embodiment of the present invention includes: obtaining at least one to-be-delivered requirement item corresponding to a to-be-delivered project; inputting the to-be-delivered requirement item into a quality evaluation model to obtain a quality evaluation result of the to-be-delivered requirement item; wherein, the quality evaluation model is composed of quality evaluation indicators, indicator weights, and indicator evaluation rules; and performing delivery risk warning on the to-be-delivered project according to the quality evaluation results of the to-be-delivered requirement items. The above technical solution quickly obtains the quality evaluation results of each requirement item in the project with the help of the quality evaluation model, and according to the quality evaluation results of each requirement item, the delivery risks of the project are identified in advance before project delivery, which helps project R & D personnel to discover and solve the delivery risks of the project in time, thereby improving the project delivery quality, avoiding the situation that the project needs to be returned to the R & D department for repair due to quality problems during the test phase, reducing the project repair cost and time, and shortening the project test cycle.

[0020] It should be understood that the content described in this part is not intended to identify the key or important features of the embodiments of the present invention, nor is it used to limit the scope of the present invention. Other features of the present invention will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following will briefly introduce the drawings required for the description of the embodiments. Obviously, the drawings in the following description are only some embodiments of the present invention, and those of ordinary skill in the art can also obtain other drawings based on these drawings without creative efforts.

[0022] Figure 1 It is a flowchart of a project delivery risk early warning method provided in Embodiment 1 of the present invention;

[0023] Figure 2 It is a flowchart of a project delivery risk early warning method provided in Embodiment 2 of the present invention;

[0024] Figure 3 It is a schematic structural diagram of a project delivery risk early warning device provided in Embodiment 3 of the present invention;

[0025] Figure 4 It is a schematic structural diagram of an electronic device for implementing the project delivery risk early warning method of the embodiments of the present invention. Detailed implementation manners

[0026] In order to enable those skilled in the art to better understand the solutions of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0027] It should be noted that the terms "target", "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and do not have to be used to describe a specific order or sequence. It should be understood that such data can be interchanged under appropriate circumstances so that the embodiments of the present invention described here can be implemented in an order other than those illustrated or described here. In addition, the terms "comprising" and "having" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product or device comprising a series of steps or units does not have to be limited to those steps or units clearly listed, but may include other steps or units not clearly listed or inherent to these processes, methods, products or devices.

[0028] Embodiment 1

[0029] Figure 1 It is a flowchart of a project delivery risk early warning method provided in Embodiment 1 of the present invention. This embodiment is applicable to the situation of early warning of project delivery risks before delivering a project from the R & D department to the testing department. This method can be executed by a project delivery risk early warning device, and this device can be implemented in the form of hardware and / or software and can be configured in an electronic device. As Figure 1 shown, this method includes:

[0030] S101. Obtain at least one to-be-delivered requirement item corresponding to the to-be-delivered project.

[0031] Herein, the to-be-delivered project refers to a project that needs to be delivered from the R & D department to the testing department; optionally, the to-be-delivered project can be a software development project. For example, developing an intelligent audit platform. The to-be-delivered requirement item refers to a requirement item involved in the to-be-delivered project.

[0032] Specifically, at least one to-be-delivered requirement item corresponding to the to-be-delivered project can be obtained from the project management system within the R & D department of the financial institution.

[0033] S102. Input the to-be-delivered requirement item into the quality assessment model to obtain the quality assessment result of the to-be-delivered requirement item; wherein, the quality assessment model consists of quality assessment indicators, indicator weights, and indicator assessment rules.

[0034] Herein, the quality assessment model refers to a pre-configured model used to assess the delivery quality of the to-be-delivered requirement items corresponding to the to-be-delivered project. The quality assessment result refers to the result of assessing the delivery quality of the to-be-delivered requirement item, which can specifically be expressed as a delivery quality score.

[0035] Herein, the quality assessment indicator refers to a parameter used in the quality assessment model to measure the delivery quality of the to-be-delivered requirement item; optionally, the quality assessment indicators include the number of unresolved bottleneck problems, the timeliness of unresolved bottleneck problems, the number of unresolved ordinary problems, the timeliness of unresolved ordinary problems, the passing rate of test cases, the number of warning personnel, and the defect density of R & D problems. Herein, the bottleneck problem refers to a problem that restricts or hinders the overall progress of project R & D during the project R & D process; correspondingly, the ordinary problem refers to a problem caused by a single link or a single module during the project R & D process. It should be noted that ordinary problems generally do not affect the overall progress of project R & D. The number of warning personnel refers to the number of personnel involved in the to-be-delivered requirement item. The defect density of R & D problems refers to the number of defects contained in every thousand lines of code corresponding to the R & D problem. It should be noted that the lower the defect density of the R & D problem, the more robust the project code.

[0036] Herein, the indicator weight refers to the weight assigned to the quality assessment indicator in the quality assessment model; optionally, the indicator weight can be pre-set according to the expert experience of those skilled in the art. For example, the weight of the number of unresolved bottleneck problems in the quality assessment model is set to 20%, the weight of the timeliness of unresolved bottleneck problems is set to 15%, the weight of the number of unresolved ordinary problems is set to 15%, the weight of the timeliness of unresolved ordinary problems is set to 10%, the weight of the passing rate of test cases is set to 15%, the weight of the number of warning personnel is set to 5%, and the weight of the defect density of R & D problems is set to 20%. It should be noted that one quality assessment indicator corresponds to one indicator weight.

[0037] Among them, the index evaluation rule refers to the evaluation rule corresponding to the quality evaluation index in the quality evaluation model, which is used to measure the importance of the to-be-delivered requirement item in terms of the quality evaluation index; optionally, the index evaluation rule can be preset according to the actual business requirements and the expert experience of those skilled in the art, and the embodiments of the present invention do not make specific limitations thereto. It should be noted that one quality evaluation index corresponds to one index evaluation rule.

[0038] Specifically, for each to-be-delivered requirement item corresponding to the to-be-delivered project, input the to-be-delivered requirement into the quality evaluation model. After being processed by the quality evaluation model, the quality evaluation result of the to-be-delivered requirement item is obtained, so that the quality evaluation results of each to-be-delivered requirement item can be obtained.

[0039] S103. According to the quality evaluation results of each to-be-delivered requirement item, perform a delivery risk warning on the to-be-delivered project.

[0040] Specifically, the total number of to-be-delivered requirement items corresponding to the to-be-delivered project can be counted, denoted as the first quantity; and the total number of to-be-delivered requirement items with quality evaluation results less than the quality evaluation threshold among all to-be-delivered requirement items is counted as the second quantity; if the second quantity exceeds the preset ratio of the first quantity, it is determined that the to-be-delivered project has a delivery risk, and a delivery risk warning is performed on the to-be-delivered project.

[0041] Among them, the quality evaluation threshold can be preset according to the actual business requirements. For example, the quality evaluation threshold can be 60 points, and the embodiments of the present invention do not make specific limitations thereto. The preset ratio can be preset according to the expert experience of those skilled in the art. For example, the preset ratio can be one half, and the embodiments of the present invention do not make specific limitations thereto.

[0042] The technical solution of the embodiments of the present invention obtains at least one to-be-delivered requirement item corresponding to the to-be-delivered project; inputs the to-be-delivered requirement item into the quality evaluation model to obtain the quality evaluation result of the to-be-delivered requirement item; among them, the quality evaluation model is composed of quality evaluation indexes, index weights, and index evaluation rules; according to the quality evaluation results of each to-be-delivered requirement item, a delivery risk warning is performed on the to-be-delivered project. The above technical solution quickly obtains the quality evaluation results of each requirement item in the project with the help of the quality evaluation model, and according to the quality evaluation results of each requirement item, the delivery risk of the project is identified in advance before the project is delivered, which helps the project R & D personnel to timely discover and solve the delivery risk of the project, thereby improving the project delivery quality, avoiding the situation that the project needs to be returned to the R & D department for repair due to quality problems during the test phase, reducing the project repair cost and time, and shortening the project test cycle.

[0043] Embodiment 2

[0044] Figure 2The flowchart of a project delivery risk early warning method provided in the second embodiment of the present invention. On the basis of the above embodiment, this embodiment further optimizes the "determination of index weights in the quality evaluation model" and "carrying out delivery risk early warning for the to-be-delivered project according to the quality evaluation results of each to-be-delivered requirement item", and provides an optional implementation scheme. It should be noted that for the parts not described in detail in the embodiments of the present invention, reference may be made to the relevant descriptions of other embodiments. As Figure 2 shown, the method includes:

[0045] S201. Obtain at least one to-be-delivered requirement item corresponding to the to-be-delivered project.

[0046] S202. Input the to-be-delivered requirement item into the quality evaluation model to obtain the quality evaluation result of the to-be-delivered requirement item; wherein, the quality evaluation model is composed of quality evaluation indexes, index weights and index evaluation rules.

[0047] Among them, the process of determining the index weights in the quality evaluation model is as follows: Based on the subjective weight assignment method, determine the first weight corresponding to each quality evaluation index in the quality evaluation model; Based on the objective weight assignment method, determine the second weight corresponding to each quality evaluation index in the quality evaluation model; According to the first weight and the second weight corresponding to each quality evaluation index in the quality evaluation model, determine the target weight corresponding to each quality evaluation index in the quality evaluation model.

[0048] Among them, both the subjective weight assignment method and the objective weight assignment method can be preset according to actual business needs. For example, the subjective weight assignment method can be the Analytic Hierarchy Process (AHP), the expert ranking method or the direct weight assignment method; the objective weight assignment method can be the entropy weight method or the CRITIC method (Criteria Importance Through Intercriteria Correlation).

[0049] Among them, based on the subjective weight assignment method, to determine the first weight corresponding to each quality evaluation index in the quality evaluation model, specifically, it can be: Based on the Analytic Hierarchy Process, determine the first weight corresponding to each quality evaluation index in the quality evaluation model. More specifically, based on the following Saaty scale table, according to the expert experience of those skilled in the art, compare the quality evaluation indexes in the quality evaluation model pairwise to obtain the scale values between the pairwise quality evaluation indexes; According to the scale values between the pairwise quality evaluation indexes, construct a judgment matrix; According to the scale values of each row in the judgment matrix, through the following first weight determination formula, determine the first weight corresponding to each quality evaluation index in the quality evaluation model:

[0050]

[0051] Among them, W i,AHP represents the first weight corresponding to the i-th quality evaluation index in the quality evaluation model; V represents the sum of all scale values in the judgment matrix; V i represents the sum of all scale values in the i-th row of the judgment matrix, and also represents the total scale value corresponding to the i-th quality evaluation index in the quality evaluation model.

[0052] Saaty Scale Table

[0053] Scale value Meaning 1 Equally important 3 Slightly important 5 Obviously important 7 Strongly important 9 Extremely important 2,4,6,8 Intermediate value of adjacent scales

[0054] Exemplarily, if the quality evaluation model includes the following quality evaluation indicators: the number of unresolved bottleneck problems (denoted as C1), the timeliness of unresolved bottleneck problems (denoted as C2), the number of unresolved ordinary problems (denoted as C3), the timeliness of unresolved ordinary problems (denoted as C4), the passing rate of test cases (denoted as C5), the number of warning personnel (denoted as C6), and the defect density of R & D problems (denoted as C7), then based on the Saaty scale table and the expert experience of those skilled in the art, the above 7 quality evaluation indicators are compared pairwise to obtain the scale values between the following comparison indicator pairs:

[0055] Comparison index pair Scale value C1 vs C2 3 C1 vs C3 3 C1 vs C4 5 C1 vs C5 3 C1 vs C6 7 C1 vs C7 1 C2 vs C3 1 C2 vs C4 3 C2 vs C5 1 C2 vs C6 5 C3 vs C4 3 C3 vs C5 1 C3 vs C6 5 C4 vs C6 3 C5 vs C6 5

[0056] It should be noted that if C2 is 3 times more important than C4, then C4 is 1 / 3 times more important than C2. Based on this principle, according to the scale values between the above comparison indicator pairs, the scale values between pairwise quality evaluation indicators can be obtained; then, with 1 on the matrix diagonal, according to the scale values between pairwise quality evaluation indicators, the following judgment matrix is constructed:

[0057] C1 C2 C3 C4 C5 C6 C7 C1 1 3 3 5 3 7 1 C2 1 / 3 1 1 3 1 5 1 / 3 C3 1 / 3 1 1 3 1 5 1 / 3 C4 1 / 5 1 / 3 1 / 3 1 1 / 3 3 1 / 5 C5 1 / 3 1 1 3 1 5 1 / 3 C6 1 / 7 1 / 5 1 / 5 1 / 3 1 / 5 1 1 / 7 C7 1 3 3 5 3 7 1

[0058] Then, according to the scale values in the first row of the above judgment matrix, the total scale value corresponding to C1 is obtained, that is, V1 = 1 + 3 + 3 + 5 + 3 + 7 + 1 = 23; according to the scale values in the second row of the above judgment matrix, the total scale value corresponding to C2 is obtained, that is According to the scale values in the third row of the above judgment matrix, the total scale value corresponding to C3 is obtained, that is, V3≈11.67; according to the scale values in the fourth row of the above judgment matrix, the total scale value corresponding to C4 is obtained, that is, V4 = 5.4; according to the scale values in the fifth row of the above judgment matrix, the total scale value corresponding to C5 is obtained, that is, V5≈11.67; according to the scale values in the sixth row of the above judgment matrix, the total scale value corresponding to C6 is obtained, that is, V6≈2.22; according to the scale values in the seventh row of the above judgment matrix, the total scale value corresponding to C7 is obtained, that is, V7 = 23. Thus, the sum of all scale values in the above judgment matrix can be obtained, that is, V = V1+V2+V3+V4+V5+V6+V7 = 88.63, and then based on the above first weight determination formula, the first weights corresponding to C1, C2, C3, C4, C5, C6, and C7 in the quality evaluation model can be obtained.

[0059] Among them, based on the objective weight assignment method, the second weight corresponding to each quality evaluation index in the quality evaluation model is determined. Specifically, based on the CRITIC method, the second weight corresponding to each quality evaluation index in the quality evaluation model is determined. More specifically, assuming there are k to-be-delivered requirement items, the quality evaluation model is used to evaluate these k to-be-delivered requirement items, so as to obtain k index values corresponding to each quality evaluation index in the quality evaluation model; the k index values corresponding to each quality evaluation index in the quality evaluation model are normalized to obtain k normalized index values corresponding to each quality evaluation index in the quality evaluation model; for the i-th quality evaluation index in the quality evaluation model, the average value of the k normalized index values corresponding to this quality evaluation index is obtained, and the average index value corresponding to this quality evaluation index is obtained; according to the k normalized index values corresponding to this quality evaluation index and the average index value corresponding to this quality evaluation index, through the following contrast intensity determination formula, the contrast intensity of this quality evaluation index is determined:

[0060]

[0061] Among them, σ i represents the contrast intensity of the i-th quality evaluation index in the quality evaluation model; k represents the total number of normalized index values corresponding to the i-th quality evaluation index in the quality evaluation model; x j represents the j-th normalized index value corresponding to the i-th quality evaluation index in the quality evaluation model; represents the average index value corresponding to the i-th quality evaluation index in the quality evaluation model.

[0062] After that, calculate the Pearson correlation coefficient between this quality evaluation index and other quality evaluation indices in the quality evaluation model, and determine the conflict degree between this quality evaluation index and other quality evaluation indices in the quality evaluation model through the following conflict degree determination formula based on the Pearson correlation coefficient between this quality evaluation index and other quality evaluation indices in the quality evaluation model:

[0063]

[0064] where N represents the total number of quality evaluation indices in the quality evaluation model, and r ij represents the Pearson correlation coefficient between the i-th quality evaluation index and the j-th quality evaluation index in the quality evaluation model; f i represents the conflict degree between the i-th quality evaluation index and other quality evaluation indices in the quality evaluation model.

[0065] After that, determine the information carrying capacity of this quality evaluation index through the following information carrying capacity determination formula based on the comparison intensity of this quality evaluation index and the conflict degree between this quality evaluation index and other quality evaluation indices in the quality evaluation model:

[0066] C i =σ i f i ;

[0067] where C i represents the information carrying capacity of the i-th quality evaluation index in the quality evaluation model; σ i represents the comparison intensity of the i-th quality evaluation index in the quality evaluation model. After that, determine the second weight corresponding to each quality evaluation index in the quality evaluation model through the following second weight determination formula based on the information carrying capacity of each quality evaluation index in the quality evaluation model:

[0068]

[0069] where W i,CRITIC represents the second weight corresponding to the i-th quality evaluation index in the quality evaluation model.

[0070] Among them, based on the first weight and the second weight corresponding to each quality evaluation index in the quality evaluation model, determine the target weight corresponding to each quality evaluation index in the quality evaluation model. Specifically, for the i-th quality evaluation index in the quality evaluation model, perform weighted summation on the first weight and the second weight corresponding to this quality evaluation index to obtain the target weight corresponding to this quality evaluation index, that is:

[0071] W i =αW i,AHP +(1 - α)Wi,CRITIC ;

[0072] Wherein, W i represents the target weight corresponding to the i-th quality evaluation index in the quality evaluation model; α represents the weight adjustment coefficient, which can be determined through simulation experiments; W i,AHP represents the first weight corresponding to the i-th quality evaluation index in the quality evaluation model; W i,CRITIC represents the second weight corresponding to the i-th quality evaluation index in the quality evaluation model.

[0073] It can be understood that for each quality evaluation index in the quality evaluation model, the first weight determined by the subjective weight assignment method and the second weight determined by the objective weight assignment method are combined to obtain the target weight corresponding to the quality evaluation index, which combines subjective experience and objective data characteristics, balances the subjective and objective factors in allocating weights for the quality evaluation indexes in the quality evaluation model, thereby making the determination of the index weights in the quality evaluation model more scientific and reasonable, improving the interpretability of the index weights in the quality evaluation model, and further making the quality evaluation results of each to-be-delivered requirement item determined based on the quality evaluation model more accurate and reliable.

[0074] S203. Determine the leading requirement item from each to-be-delivered requirement item according to the requirement item type of each to-be-delivered requirement item.

[0075] Wherein, the requirement item type refers to the type of the to-be-delivered requirement item; optionally, according to the importance degree of the requirement item, the requirement item type can be divided into a leading requirement item and a cooperating requirement item. Among them, the leading requirement item refers to the requirement item proposed, promoted and ensured to be implemented by the leading party; correspondingly, the cooperating requirement item refers to the to-be-delivered requirement item used to cooperate with the leading requirement item among all the to-be-delivered requirement items corresponding to the to-be-delivered project.

[0076] Specifically, the leading requirement item can be screened out from each to-be-delivered requirement item with the requirement item type being the leading requirement item as the retrieval condition.

[0077] S204. Determine whether there is a delivery risk for the to-be-delivered project according to the quality evaluation result of the leading requirement item.

[0078] Specifically, if it is detected that the quality evaluation result of the leading requirement item is less than the quality evaluation threshold, it is determined that there is a delivery risk for the to-be-delivered project; otherwise, it is determined that there is no delivery risk for the to-be-delivered project.

[0079] It should be noted that if the quality assessment result of the leading requirement item is less than the quality assessment threshold, it indicates that the leading requirement item fails to meet the quality standard for requirement item delivery. As the core requirement item of the project to be delivered, if the leading requirement item fails to meet the quality standard for requirement item delivery, it is determined that the project to be delivered also fails to meet the quality standard for delivery, and there is a delivery risk.

[0080] It can be understood that by only determining whether the quality assessment result of the leading requirement item corresponding to the project to be delivered is less than the quality assessment threshold, it is determined whether there is a delivery risk for the project to be delivered, without having to determine one by one the quality assessment results of each requirement item to be delivered corresponding to the project to be delivered, and then determining whether there is a delivery risk for the project to be delivered based on the quality assessment results of each requirement item to be delivered. This reduces the consumption of computing resources and improves the determination speed of the delivery risk of the project to be delivered.

[0081] S205. If there is, issue a delivery risk warning for the project to be delivered.

[0082] Specifically, in the case of determining that there is a delivery risk for the project to be delivered, determine the target risk level of the project to be delivered; based on the target risk level, issue a delivery risk warning for the project to be delivered. Among them, the target risk level refers to the delivery risk level corresponding to the project to be delivered; optionally, the target risk level can be one of high risk, medium risk, and low risk.

[0083] More specifically, based on the quality assessment results of each requirement item to be delivered corresponding to the project to be delivered, and based on the preset risk level assessment rules, determine the target risk level of the project to be delivered to improve the scientificity and accuracy of the determination of the target risk level; match the target risk level with the risk levels in the preset relationship table to obtain the matching risk level; among them, the matching risk level refers to the risk level in the preset relationship table that matches the target risk level; based on the corresponding relationship between the risk levels, warning methods, and project adjustment suggestions in the preset relationship table, extract the warning method and project adjustment suggestion corresponding to the matching risk level from the preset relationship table as the target warning method and target project adjustment suggestion corresponding to the target risk level; issue a delivery risk warning for the project to be delivered according to the target warning method to improve the accuracy of the project delivery risk warning; and send the target project adjustment suggestion to the relevant project R & D personnel to guide the relevant project R & D personnel to timely make targeted adjustments to the project to be delivered, thereby improving the delivery quality of the project to be delivered.

[0084] The technical solution of the embodiment of the present invention includes: obtaining at least one to-be-delivered requirement item corresponding to a to-be-delivered project; inputting the to-be-delivered requirement item into a quality evaluation model to obtain a quality evaluation result of the to-be-delivered requirement item, where the quality evaluation model consists of quality evaluation indicators, index weights, and index evaluation rules; determining a leading requirement item from each to-be-delivered requirement item according to the requirement item type of each to-be-delivered requirement item; determining whether there is a delivery risk for the to-be-delivered project according to the quality evaluation result of the leading requirement item; if so, giving a delivery risk warning for the to-be-delivered project. After quickly obtaining the quality evaluation results of each requirement item in the project with the help of the quality evaluation model, the above technical solution determines whether there is a delivery risk for the to-be-delivered project by identifying the leading requirement item in each to-be-delivered requirement item and only judging whether the quality evaluation result of the leading requirement item is less than the quality evaluation threshold, without judging one by one whether the quality evaluation result of each to-be-delivered requirement item in the to-be-delivered project is less than the quality evaluation threshold to further determine whether there is a delivery risk for the to-be-delivered project, thereby reducing the consumption of computing resources and improving the determination speed of the delivery risk of the to-be-delivered project. At the same time, it is possible to identify the project delivery risk in advance before project delivery, helping project R & D personnel to discover and solve the project delivery risk in time, thereby improving the project delivery quality, avoiding the situation that the project needs to be returned to the R & D department for repair due to quality problems during the test phase, reducing the project repair cost and time, and shortening the project test cycle.

[0085] Embodiment III

[0086] Figure 3 FIG. is a schematic structural diagram of a project delivery risk warning device provided in Embodiment III of the present invention. This embodiment is applicable to the situation of giving a delivery risk warning for a project in advance before delivering the project from the R & D department to the test department. The device can be implemented in the form of hardware and / or software and can be configured in an electronic device. As Figure 3 shown, the device includes:

[0087] A to-be-delivered requirement item acquisition module 301, configured to obtain at least one to-be-delivered requirement item corresponding to a to-be-delivered project;

[0088] A quality evaluation result determination module 302, configured to input the to-be-delivered requirement item into a quality evaluation model to obtain a quality evaluation result of the to-be-delivered requirement item, where the quality evaluation model consists of quality evaluation indicators, index weights, and index evaluation rules;

[0089] A delivery risk warning module 303, configured to give a delivery risk warning for the to-be-delivered project according to the quality evaluation results of each to-be-delivered requirement item.

[0090] The technical solution of the embodiment of the present invention obtains at least one to-be-delivered requirement item corresponding to the to-be-delivered project; inputs the to-be-delivered requirement item into the quality evaluation model to obtain the quality evaluation result of the to-be-delivered requirement item; wherein, the quality evaluation model consists of quality evaluation indicators, indicator weights, and indicator evaluation rules; and performs delivery risk early warning on the to-be-delivered project according to the quality evaluation results of each to-be-delivered requirement item. The above technical solution quickly obtains the quality evaluation results of each requirement item in the project with the help of the quality evaluation model, and according to the quality evaluation results of each requirement item, the delivery risks of the project are identified in advance before project delivery, helping project R & D personnel to discover and solve the delivery risks of the project in a timely manner, thereby improving the project delivery quality, avoiding the situation that the project needs to be returned to the R & D department for repair due to quality problems during the test phase, reducing the project repair cost and time, and shortening the project test cycle.

[0091] Optionally, the quality evaluation indicators include the number of unsolved bottleneck problems, the timeliness of unsolved bottleneck problems, the number of unsolved ordinary problems, the timeliness of unsolved ordinary problems, the passing rate of test cases, the number of warning personnel, and the defect density of R & D problems.

[0092] Optionally, the device further includes an indicator weight determination module, and the indicator weight determination module is specifically used for:

[0093] Based on the subjective weight assignment method, determine the first weight corresponding to each quality evaluation indicator in the quality evaluation model;

[0094] Based on the objective weight assignment method, determine the second weight corresponding to each quality evaluation indicator in the quality evaluation model;

[0095] According to the first weight and the second weight corresponding to each quality evaluation indicator in the quality evaluation model, determine the target weight corresponding to each quality evaluation indicator in the quality evaluation model.

[0096] Optionally, the delivery risk early warning module 303 includes:

[0097] The leading requirement item determination unit is used to determine the leading requirement item from each to-be-delivered requirement item according to the requirement item type of each to-be-delivered requirement item;

[0098] The delivery risk determination unit is used to determine whether there is a delivery risk for the to-be-delivered project according to the quality evaluation result of the leading requirement item;

[0099] The delivery risk early warning unit is used to perform delivery risk early warning on the to-be-delivered project if there is a risk.

[0100] Optionally, the delivery risk determination unit is specifically used for:

[0101] If the quality assessment result of the leading requirement item is detected to be less than the quality assessment threshold, it is determined that there is a delivery risk for the project to be delivered;

[0102] Otherwise, it is determined that there is no delivery risk for the project to be delivered.

[0103] Optionally, the delivery risk warning unit is specifically used for:

[0104] Determine the target risk level of the project to be delivered;

[0105] According to the target risk level, give a delivery risk warning for the project to be delivered.

[0106] The project delivery risk warning device provided by the embodiments of the present invention can execute the project delivery risk warning method provided by any embodiment of the present invention, and has the corresponding functional modules and beneficial effects for executing each project delivery risk warning method.

[0107] According to the embodiments of the present invention, the present invention also provides an electronic device, a readable storage medium, and a computer program product.

[0108] Embodiment 4

[0109] Figure 4 FIG. shows a schematic structural diagram of an electronic device 10 that can be used to implement the embodiments of the present invention. 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 (such as helmets, glasses, watches, etc.) and other similar computing devices. The components shown herein, their connections and relationships, and their functions are only examples and are not intended to limit the implementation of the present invention described and / or claimed herein.

[0110] As Figure 4 shown, the electronic device 10 includes at least one processor 11, and a memory communicatively connected to at least one processor 11, such as a read-only memory (ROM) 12, a random access memory (RAM) 13, etc. Among them, the memory stores a computer program executable by at least one processor, and the processor 11 can execute various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 12 or the computer program loaded from the storage unit 18 into the random access memory (RAM) 13. In the RAM 13, various programs and data required for the operation of the electronic device 10 can also be stored. The processor 11, the ROM 12, and the RAM 13 are connected to each other through a bus 14. The input / output (I / O) interface 15 is also connected to the bus 14.

[0111] Multiple components in the electronic device 10 are connected to the I / O interface 15, including: an input unit 16, such as a keyboard, a mouse, etc.; an output unit 17, such as various types of displays, speakers, etc.; a storage unit 18, such as a disk, an optical disc, etc.; and a communication unit 19, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0112] The processor 11 can be various general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of the processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. The processor 11 executes the various methods and processes described above, such as the project delivery risk warning method.

[0113] In some embodiments, the project delivery risk warning method can be implemented as a computer program, which is tangibly contained in a computer-readable storage medium, such as the storage unit 18. In some embodiments, part or all of the computer program can be loaded and / or installed onto the electronic device 10 via the ROM 12 and / or the communication unit 19. When the computer program is loaded into the RAM 13 and executed by the processor 11, one or more steps of the project delivery risk warning method described above can be executed. Alternatively, in other embodiments, the processor 11 can be configured to execute the project delivery risk warning method by any other suitable means (e.g., by means of firmware).

[0114] The various embodiments of the systems and technologies described above in this article 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 a chip (SOCs), complex programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments can include: implemented in one or more computer programs, the one or more computer programs can be executed and / or interpreted on a programmable system including at least one programmable processor, the programmable processor can be a special or general programmable processor, can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit the data and instructions to the storage system, the at least one input device, and the at least one output device.

[0115] A computer program for implementing the method of the present invention can be written in any combination of one or more programming languages. These computer programs can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when the computer programs are executed by the processor, the functions / operations specified in the flowchart and / or block diagram are implemented. The computer programs can be executed entirely on the machine, partially on the machine, as a stand-alone software package partially on the machine and partially on a remote machine, or entirely on a remote machine or server.

[0116] In the context of the present invention, a computer-readable storage medium can be a tangible medium that can contain or store a computer program for use by or in connection with an instruction execution system, apparatus, or device. The computer-readable storage medium can include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. Alternatively, the computer-readable storage medium can be a machine-readable signal medium. More specific examples of the machine-readable storage medium would include an electrical connection based on one or more wires, 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 disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0117] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device 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 a pointing device (e.g., a mouse or a trackball) by which the user can provide input to the electronic device. Other kinds 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).

[0118] The systems and techniques described herein can be implemented in a computing system including backend components (e.g., as a data server), or a computing system including middleware components (e.g., an application server), or a computing system including frontend components (e.g., a user computer having a graphical user interface or a web browser through which a user can interact with an implementation of the systems and techniques described herein), or a computing system including any combination of such backend components, middleware components, or frontend components. The components of the system can be interconnected with each other by digital data communication in any form or medium (e.g., a communication network). Examples of communication networks include: local area network (LAN), wide area network (WAN), blockchain network, and the Internet.

[0119] A computing system can include a client and a server. The client and the server are generally remote from each other and typically interact via a communication network. The client-server relationship is created by computer programs running on respective computers and having a client-server relationship with each other. The server can 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, solving the defects of difficult management and weak business scalability existing in traditional physical hosts and VPS services.

[0120] It should be understood that various forms of the processes shown above can be used, steps can be reordered, added, or deleted. For example, the steps recited in the present invention can be executed in parallel, sequentially, or in a different order, as long as the desired results of the technical solution of the present invention can be achieved, and no limitation is imposed herein.

[0121] The above specific embodiments do not constitute a limitation on the protection scope of the present invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention shall be included within the protection scope of the present invention.

Claims

1. A project delivery risk early warning method, characterized in that Including: Obtain at least one to-be-delivered requirement item corresponding to the to-be-delivered project; Input the to-be-delivered requirement item into a quality evaluation model to obtain a quality evaluation result of the to-be-delivered requirement item; wherein, the quality evaluation model consists of quality evaluation indicators, indicator weights, and indicator evaluation rules; Based on the quality evaluation results of each to-be-delivered requirement item, conduct a delivery risk warning for the to-be-delivered project.

2. The method according to claim 1, characterized in that, The quality evaluation indicators include the number of unsolved bottleneck problems, the timeliness of unsolved bottleneck problems, the number of unsolved general problems, the timeliness of unsolved general problems, the passing rate of test cases, the number of warning personnel, and the defect density of R & D problems.

3. The method according to claim 1, wherein The process for determining the indicator weights in the quality evaluation model is as follows: Based on the subjective weight assignment method, determine the first weight corresponding to each quality evaluation indicator in the quality evaluation model; Based on the objective weight assignment method, determine the second weight corresponding to each quality evaluation indicator in the quality evaluation model; According to the first weight and the second weight corresponding to each quality evaluation indicator in the quality evaluation model, determine the target weight corresponding to each quality evaluation indicator in the quality evaluation model.

4. The method according to claim 1, wherein The conducting a delivery risk warning for the to-be-delivered project according to the quality evaluation results of each to-be-delivered requirement item includes: According to the requirement item types of each to-be-delivered requirement item, determine the leading requirement item from each to-be-delivered requirement item; Based on the quality evaluation result of the leading requirement item, determine whether there is a delivery risk for the to-be-delivered project; If so, conduct a delivery risk warning for the to-be-delivered project.

5. The method according to claim 4, wherein The determining whether there is a delivery risk for the to-be-delivered project based on the quality evaluation result of the leading requirement item includes: If it is detected that the quality evaluation result of the leading requirement item is less than the quality evaluation threshold, determine that there is a delivery risk for the to-be-delivered project; Otherwise, determine that there is no delivery risk for the to-be-delivered project.

6. The method according to claim 4, wherein The conducting a delivery risk warning for the to-be-delivered project includes: Determine the target risk level of the to-be-delivered project; According to the target risk level, conduct a delivery risk warning for the to-be-delivered project.

7. An early warning device for project delivery risks, characterized in that, Including: A to-be-delivered requirement item acquisition module, configured to obtain at least one to-be-delivered requirement item corresponding to the to-be-delivered project; A quality evaluation result determination module, configured to input the to-be-delivered requirement item into a quality evaluation model to obtain a quality evaluation result of the to-be-delivered requirement item; wherein, the quality evaluation model consists of quality evaluation indicators, indicator weights, and indicator evaluation rules; A delivery risk warning module, configured to conduct a delivery risk warning for the to-be-delivered project according to the quality evaluation results of each to-be-delivered requirement item.

8. An electronic device, characterized in that, The electronic device includes: At least one processor; and A memory communicatively connected to the at least one processor; wherein, The memory stores a computer program executable by the at least one processor, and when the computer program is executed by the at least one processor, the at least one processor is enabled to execute the project delivery risk warning method according to any one of claims 1 - 6.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions for implementing the project delivery risk warning method according to any one of claims 1-6 when the computer instructions are executed by a processor.

10. A computer program product comprising a computer program which implements the project delivery risk warning method according to any one of claims 1-6 when executed by a processor.

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