CN117522138A - Method, device, equipment and medium for identifying testing risk of financial business system - Google Patents

Method, device, equipment and medium for identifying testing risk of financial business system Download PDF

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CN117522138A
CN117522138A CN202311565794.1A CN202311565794A CN117522138A CN 117522138 A CN117522138 A CN 117522138A CN 202311565794 A CN202311565794 A CN 202311565794A CN 117522138 A CN117522138 A CN 117522138A
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test risk
test
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林锐
叶建锋
邓立恒
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Industrial and Commercial Bank of China Ltd ICBC
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Industrial and Commercial Bank of China Ltd ICBC
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Abstract

The application relates to a method, a device, equipment, a medium and a program product for identifying testing risk of a financial business system, and relates to the fields of automatic testing and financial science and technology. The method and the device can improve accuracy and timeliness of testing risk identification of the financial business system. The method comprises the following steps: detecting a research and development stage of a financial business system, determining stage-associated test risk factors and basic test risk factors in a factor set according to the research and development stage to obtain a plurality of target factors, obtaining weighting coefficients corresponding to the plurality of target factors in the research and development stage, adjusting stage-associated factor operation positions in a preset model according to the research and development stage to obtain a target model, inputting the plurality of target factors and the corresponding weighting coefficients into the target model, outputting the stage-associated test risk factors and the weighting coefficients according to the basic test risk factors and the weighting coefficients input in the basic factor operation positions and the stage-associated test risk factors and the weighting coefficients input in the stage-associated factor operation positions, and obtaining test risk recognition results corresponding to the system in the research and development stage.

Description

Method, device, equipment and medium for identifying testing risk of financial business system
Technical Field
The present invention relates to the field of automated testing and financial technology, and in particular, to a method, apparatus, computer device, storage medium and computer program product for identifying testing risk of a financial business system.
Background
At present, the testing risk of financial business systems such as banking client information systems is usually calculated according to static factors such as project scale, research and development period, problem number and the like.
However, in the actual testing process of the financial business system, the testing risk should be dynamically changed in real time due to the influence of multiple factors, and the current testing risk identification method cannot accurately and timely identify the testing risk of the financial business system.
Disclosure of Invention
In view of the foregoing, it is desirable to provide a method, apparatus, computer device, storage medium, and computer program product for identifying risk of testing of a financial business system.
In a first aspect, the present application provides a method for identifying testing risk of a financial business system. The method comprises the following steps:
detecting the research and development stage of the financial business system in the research and development process;
determining a stage-associated test risk factor and a basic test risk factor in a preset test risk factor set according to the research and development stage to obtain a plurality of target test risk factors corresponding to the research and development stage;
Acquiring weighting coefficients corresponding to the target test risk factors in the research and development stage;
adjusting a stage correlation factor operation bit in a preset test risk result identification model according to the research and development stage to obtain a target test risk result identification model corresponding to the research and development stage; the target test risk result identification model comprises a stage correlation factor operation bit and a basic factor operation bit;
inputting the target test risk factors and the corresponding weighting coefficients into the target test risk result identification model; the target test risk result identification model is used for outputting test risk identification results corresponding to the research and development stage according to basic test risk factors input in basic factor operation bits, weighting coefficients corresponding to the basic test risk factors, stage-associated test risk factors input in stage-associated factor operation bits and weighting coefficients corresponding to the stage-associated test risk factors;
and acquiring a test risk identification result corresponding to the research and development stage output by the target test risk result identification model.
In one embodiment, the determining, according to the development stage, a stage-associated test risk factor and a basic test risk factor in a preset test risk factor set includes: determining corresponding test risk identification frequency according to the research and development stage; according to the test risk identification frequency, acquiring a stage-associated test risk factor corresponding to the research and development stage from a stage-associated test risk factor pool of the preset test risk factor set, and acquiring the basic test risk factor according to a basic test risk factor pool of the preset test risk factor set.
In one embodiment, the obtaining the weighting coefficients corresponding to the plurality of target test risk factors in the development stage includes: determining factor importance degree information of the target test risk factors in the research and development stage; and determining weighting coefficients corresponding to the target test risk factors in the research and development stage according to the factor importance degree information.
In one embodiment, the step of adjusting the stage correlation factor operation bit in the preset test risk result recognition model according to the development stage to obtain the target test risk result recognition model corresponding to the development stage includes: determining a risk test dimension sub-model to be adjusted in the preset test risk result identification model according to the research and development stage; the risk test dimension sub-model comprises the stage correlation factor operation bit; and adjusting the stage correlation factor operation bit in the risk test dimension sub-model to be adjusted according to the factor data input format information of the stage correlation factor operation bit in the research and development stage in the risk test dimension sub-model to be adjusted, so as to obtain a target test risk result identification model corresponding to the research and development stage.
In one embodiment, the target test risk result recognition model is configured to obtain risk test sub-results corresponding to each risk test dimension according to the multiple target test risk factors and the corresponding weighting coefficients through each risk test dimension sub-model, and obtain test risk recognition results corresponding to the development stage according to the risk test sub-results corresponding to each risk test dimension through a risk summary sub-model.
In one embodiment, after the obtaining the test risk identification result corresponding to the development stage output by the target test risk result identification model, the method further includes: acquiring a historical test risk identification result corresponding to the research and development stage; obtaining a test risk variation result according to the test risk identification result and the historical test risk identification result; and determining the test risk level corresponding to the research and development stage according to the test risk change result and the historical test risk identification result.
In one embodiment, the determining the test risk level corresponding to the development stage according to the test risk variation result and the historical test risk identification result includes: acquiring the ratio of the test risk change result to the historical test risk identification result; and determining the test risk level corresponding to the research and development stage according to the threshold range of the ratio.
In one embodiment, the method further comprises: and updating the historical test risk identification result according to the average processing of the test risk change result and the historical test risk identification result.
In a second aspect, the present application further provides a testing risk identification device of a financial service system. The device comprises:
the stage detection module is used for detecting the research and development stage of the financial business system in the research and development process;
the factor determining module is used for determining a stage-associated test risk factor and a basic test risk factor in a preset test risk factor set according to the research and development stage to obtain a plurality of target test risk factors corresponding to the research and development stage;
the weighting acquisition module is used for acquiring weighting coefficients corresponding to the target test risk factors in the research and development stage;
the model obtaining module is used for adjusting a stage correlation factor operation position in a preset test risk result identification model according to the research and development stage to obtain a target test risk result identification model corresponding to the research and development stage; the target test risk result identification model comprises a stage correlation factor operation bit and a basic factor operation bit;
The data input module is used for inputting the target test risk factors and the corresponding weighting coefficients into the target test risk result identification model; the target test risk result identification model is used for outputting test risk identification results corresponding to the research and development stage according to basic test risk factors input in basic factor operation bits, weighting coefficients corresponding to the basic test risk factors, stage-associated test risk factors input in stage-associated factor operation bits and weighting coefficients corresponding to the stage-associated test risk factors;
and the result acquisition module is used for acquiring the test risk identification result corresponding to the research and development stage output by the target test risk result identification model.
In a third aspect, the present application also provides a computer device. The computer device comprises a memory storing a computer program and a processor which when executing the computer program performs the steps of:
detecting the research and development stage of the financial business system in the research and development process; determining a stage-associated test risk factor and a basic test risk factor in a preset test risk factor set according to the research and development stage to obtain a plurality of target test risk factors corresponding to the research and development stage; acquiring weighting coefficients corresponding to the target test risk factors in the research and development stage; adjusting a stage correlation factor operation bit in a preset test risk result identification model according to the research and development stage to obtain a target test risk result identification model corresponding to the research and development stage; the target test risk result identification model comprises a stage correlation factor operation bit and a basic factor operation bit; inputting the target test risk factors and the corresponding weighting coefficients into the target test risk result identification model; the target test risk result identification model is used for outputting test risk identification results corresponding to the research and development stage according to basic test risk factors input in basic factor operation bits, weighting coefficients corresponding to the basic test risk factors, stage-associated test risk factors input in stage-associated factor operation bits and weighting coefficients corresponding to the stage-associated test risk factors; and acquiring a test risk identification result corresponding to the research and development stage output by the target test risk result identification model.
In a fourth aspect, the present application also provides a computer-readable storage medium. The computer readable storage medium having stored thereon a computer program which when executed by a processor performs the steps of:
detecting the research and development stage of the financial business system in the research and development process; determining a stage-associated test risk factor and a basic test risk factor in a preset test risk factor set according to the research and development stage to obtain a plurality of target test risk factors corresponding to the research and development stage; acquiring weighting coefficients corresponding to the target test risk factors in the research and development stage; adjusting a stage correlation factor operation bit in a preset test risk result identification model according to the research and development stage to obtain a target test risk result identification model corresponding to the research and development stage; the target test risk result identification model comprises a stage correlation factor operation bit and a basic factor operation bit; inputting the target test risk factors and the corresponding weighting coefficients into the target test risk result identification model; the target test risk result identification model is used for outputting test risk identification results corresponding to the research and development stage according to basic test risk factors input in basic factor operation bits, weighting coefficients corresponding to the basic test risk factors, stage-associated test risk factors input in stage-associated factor operation bits and weighting coefficients corresponding to the stage-associated test risk factors; and acquiring a test risk identification result corresponding to the research and development stage output by the target test risk result identification model.
In a fifth aspect, the present application also provides a computer program product. The computer program product comprises a computer program which, when executed by a processor, implements the steps of:
detecting the research and development stage of the financial business system in the research and development process; determining a stage-associated test risk factor and a basic test risk factor in a preset test risk factor set according to the research and development stage to obtain a plurality of target test risk factors corresponding to the research and development stage; acquiring weighting coefficients corresponding to the target test risk factors in the research and development stage; adjusting a stage correlation factor operation bit in a preset test risk result identification model according to the research and development stage to obtain a target test risk result identification model corresponding to the research and development stage; the target test risk result identification model comprises a stage correlation factor operation bit and a basic factor operation bit; inputting the target test risk factors and the corresponding weighting coefficients into the target test risk result identification model; the target test risk result identification model is used for outputting test risk identification results corresponding to the research and development stage according to basic test risk factors input in basic factor operation bits, weighting coefficients corresponding to the basic test risk factors, stage-associated test risk factors input in stage-associated factor operation bits and weighting coefficients corresponding to the stage-associated test risk factors; and acquiring a test risk identification result corresponding to the research and development stage output by the target test risk result identification model.
According to the test risk identification method, the device, the computer equipment, the storage medium and the computer program product of the financial business system, the research and development stage of the financial business system in the research and development process is detected, a plurality of target test risk factors corresponding to the research and development stage are obtained according to the stage-associated test risk factors in a preset test risk factor set and the basic test risk factors, the weighting coefficients corresponding to the target test risk factors in the research and development stage are obtained, the stage-associated factor operation bit in the preset test risk result identification model is adjusted according to the research and development stage, the target test risk result identification model corresponding to the research and development stage is obtained, the model comprises the stage-associated factor operation bit and the basic factor operation bit, the target test risk factors and the corresponding weighting coefficients are input into the target test risk result identification model, and the model outputs the test risk identification result corresponding to the research and development stage according to the basic test risk factors and the weighting coefficients input into the basic test risk factors operation bit and the stage-associated test risk factors operation bit input into the basic factor operation bit, and the test risk identification result corresponding to the financial business system in the research and development stage is obtained. The method and the system can automatically detect the research and development stage of the financial service system in the research and development process, acquire a plurality of target test risk factors including the correlation test risk factors and the basic test risk factors corresponding to the preset test risk factor set, acquire the weighting coefficient of each target test risk factor, and automatically adjust the stage correlation factor operation position of the preset model, so that the adjusted target model is applied to acquire the test risk recognition result corresponding to the financial service system in the research and development stage according to the plurality of target test risk factors and the weighting coefficient thereof, and the accuracy and timeliness of the test risk recognition of the financial service system are improved.
Drawings
FIG. 1 is an application environment diagram of a method for identifying testing risk of a financial business system according to an embodiment of the present application;
FIG. 2 is a flow chart of a method for identifying testing risk of a financial business system according to an embodiment of the present application;
FIG. 3 is a flowchart illustrating a step of determining a test risk factor according to an embodiment of the present application;
FIG. 4 is a flowchart illustrating a step of obtaining a target model according to an embodiment of the present application;
FIG. 5 is a flowchart illustrating steps for determining a test risk level according to an embodiment of the present application;
FIG. 6 is a block diagram of a risk identification device for testing a financial transaction system according to an embodiment of the present application;
fig. 7 is an internal structural diagram of a computer device in the embodiment of the present application.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the present application will be further described in detail with reference to the accompanying drawings and examples. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the present application.
The method for identifying the testing risk of the financial service system, which is provided by the embodiment of the application, can be applied to an application environment shown in fig. 1, wherein the application environment can comprise a terminal and a server, the terminal can communicate with the server through a network, the server can be connected with the financial service system, the server can execute the method for identifying the testing risk of the financial service system, which is provided by the embodiment of the application, and is used for accurately and timely identifying the testing risk of the financial service system, and the server can send related information such as a testing risk identification result to the terminal, and is used for timely sending risk early warning to related users such as research and development of the financial service system, management personnel and the like using the terminal, so that the accuracy and timeliness of risk identification of the financial service system are improved. The terminal can be, but is not limited to, various personal computers, notebook computers, smart phones and tablet computers; the server may be implemented as a stand-alone server or as a server cluster composed of a plurality of servers.
The following describes a testing risk identification method of the financial business system according to the present application with reference to various embodiments and corresponding drawings.
In one embodiment, as shown in fig. 2, there is provided a test risk identification method of a financial service system, which may be performed by a server as shown in fig. 1, and which may include the steps of:
step S201, detecting a development stage of the financial service system in the development process.
In this step, the server may detect the development stage of the financial service system, such as the bank customer information system, during the development process, where the development stage may include a front stage, a middle stage, and a later stage, different development stages may be indicated by the financial service system through corresponding development stage identifiers, and as an example, the front stage, the middle stage, and the later stage may be identified by numbers 1, 2, and 3, respectively, and the server may determine the development stage of the financial service system during the development process by detecting the development stage identifier set by the financial service system.
Step S202, determining a stage-associated test risk factor and a basic test risk factor in a preset test risk factor set according to the research and development stage, and obtaining a plurality of target test risk factors corresponding to the research and development stage.
Specifically, the preset test risk factor set refers to a set including a plurality of test risk factors, which can be preset in a server by users such as research and development personnel and management personnel of the financial service system, each test risk factor can identify whether the test risk factor is associated with one or more research and development stages, the test risk factors required by each research and development stage can be recorded as basic test risk factors, the number of the test risk factors required by a specific research and development stage or several research and development stages can be recorded as stage-associated test risk factors, and the number of the test risk factors can be one or more. Therefore, in the step, after the server determines the research and development stage of the financial business system in the research and development process, the stage-associated test risk factors and the basic test risk factors can be obtained from the preset test risk factor set according to the research and development stage, so that a plurality of test risk factors including the stage-associated test risk factors and the basic test risk factors are obtained and serve as a plurality of target test risk factors corresponding to the research and development stage. As for the test risk factors, taking earlier examples, the stage-associated test risk factors may include the number of test earlier-stage test questions, the number of test earlier-stage environmental questions, the number of project earlier-stage environmental questions, etc., and the base test risk factors may include the coding progress, the coding efficiency, etc.
Step S203, obtaining weighting coefficients corresponding to the target test risk factors in the research and development stage.
In this step, a corresponding weighting coefficient needs to be determined for each target test risk factor so as to accurately calculate the test risk recognition result, and the weighting coefficient of each test risk factor may be different in different development stages, so that after obtaining a plurality of target test risk factors, the server needs to determine the corresponding weighting coefficient according to the development stages.
In one embodiment, the obtaining the weighting coefficients corresponding to the plurality of target test risk factors in the development stage in step S203 may include: factor importance degree information of a plurality of target test risk factors in a research and development stage is determined; and determining weighting coefficients corresponding to the multiple target test risk factors in the research and development stage according to the factor importance degree information. Specifically, after obtaining multiple target test risk factors, the server determines respective factor importance degree information of each target test risk factor, where the factor importance degree information is used to indicate importance degrees of the target test risk factors on test risk identification in the development stage, and the factor importance degree information may also be preset in the server by users such as development personnel and management personnel of the financial service system, so that the server may read the factor importance degree information of each target test risk factor, determine a weighting coefficient of each target test risk factor according to the factor importance degree information, and sum the weighting coefficients of the multiple target test risk factors is not necessarily 1, for example, the weighting coefficient of the target test risk factor a may be 80%, the weighting coefficient of the target test risk factor B may be 120%, that is, the factor importance degree information indicates that the importance degrees of the target test risk factors may be changed in different development stages, that is, the weighting coefficient of the target test risk factor a in the early stage may be 80%, the weighting coefficient in the middle stage may be 100%, and so on. According to the scheme, the factor importance degree information of each test risk factor in different research and development stages can be set in a targeted mode, and the accuracy of test risk identification of the financial business system is improved.
Step S204, adjusting a stage correlation factor operation bit in a preset test risk result recognition model according to the research and development stage to obtain a target test risk result recognition model corresponding to the research and development stage.
In this step, the server needs to adjust a preset test risk result recognition model according to the development stage, where the preset test risk result recognition model may be a mathematical model of test risk recognition originally applied to the financial service system, and may perform a certain mathematical operation by using some factors to obtain a test risk recognition result, which may be exemplarily represented as test risk=first factor×first weighting coefficient+second factor×second weighting coefficient+third factor×third weighting coefficient, and so on. Specifically, the server may adjust a stage-associated factor operation bit in the preset test risk result recognition model according to the development stage, where the stage-associated factor operation bit refers to an operation bit in which a test risk factor associated with the stage is located in the test risk result recognition model, and the preset test risk result recognition model may further include a basic factor operation bit, i.e. an operation bit in which a test risk factor not associated with the stage is located, where the test risk=first factor, first weighting coefficient+second factor, second weighting coefficient+third factor, and the server may further adjust an expression of the second factor, first weighting coefficient and third factor in the model, where the first factor, first weighting coefficient and third factor, second weighting coefficient, third factor, and the like, if the server determines that the second factor, second weighting coefficient, second factor, third weighting coefficient, and third factor are the stage-associated factor operation bit according to the development stage, and the preset risk recognition model may also obtain a target-associated risk factor operation result after the stage-associated risk recognition model is performed according to the development stage-associated risk factor operation bit.
Step S205, inputting a plurality of target test risk factors and corresponding weighting coefficients into a target test risk result identification model.
Specifically, the server inputs a plurality of target test risk factors and corresponding weighting coefficients into a target test risk result identification model, and the target test risk result identification model calculates and obtains a test risk identification result corresponding to the research and development stage according to the basic test risk factors and the weighting coefficients corresponding to the basic test risk factors input in basic factor operation positions and the stage correlation test risk factors and the weighting coefficients corresponding to the stage correlation test risk factors input in stage correlation factor operation positions, and outputs the test risk identification result corresponding to the research and development stage.
Step S206, obtaining a test risk recognition result corresponding to the research and development stage output by the target test risk result recognition model.
In this step, the server obtains the output test risk recognition result corresponding to the development stage from the target test risk recognition model, where the test risk recognition result may be a score for measuring the test risk of the financial service system in the development stage, and the server may further send the test risk recognition result to the terminal for the relevant user to refer to.
According to the method, a research and development stage of a financial business system in a research and development process is detected, a stage-associated test risk factor in a preset test risk factor set and a basic test risk factor are determined according to the research and development stage to obtain a plurality of target test risk factors corresponding to the research and development stage, weighting coefficients corresponding to the target test risk factors are obtained, a stage-associated factor operation bit in a preset test risk result identification model is adjusted according to the research and development stage to obtain a target test risk result identification model corresponding to the research and development stage, the model comprises a stage-associated factor operation bit and a basic factor operation bit, the plurality of target test risk factors and the corresponding weighting coefficients are input into a target test risk result identification model, and the model outputs a test risk identification result corresponding to the research and development stage according to the basic test risk factors and the weighting coefficients input into the basic factor operation bit and the stage-associated test risk factors and the weighting coefficients input into the stage-associated factor operation bit to obtain the test risk identification result of the financial business system in the research and development stage. The method and the system can automatically detect the research and development stage of the financial service system in the research and development process, acquire a plurality of target test risk factors including the correlation test risk factors and the basic test risk factors corresponding to the preset test risk factor set, acquire the weighting coefficient of each target test risk factor, and automatically adjust the stage correlation factor operation position of the preset model, so that the adjusted target model is applied to acquire the test risk recognition result corresponding to the financial service system in the research and development stage according to the plurality of target test risk factors and the weighting coefficient thereof, and the accuracy and timeliness of the test risk recognition of the financial service system are improved.
In one embodiment, as shown in fig. 3, determining the stage-associated test risk factors and the basic test risk factors in the preset test risk factor set according to the development stage in step S202 may include:
step S301, determining corresponding test risk identification frequency according to the research and development stage.
Step S302, according to the test risk identification frequency, acquiring a stage-associated test risk factor corresponding to the research and development stage from a stage-associated test risk factor pool of a preset test risk factor set, and acquiring a basic test risk factor according to a basic test risk factor pool of the preset test risk factor set.
In this embodiment, the server may perform identification of the test risk according to different test risk identification frequencies (such as each hour, each 5 hours, each day, etc.) in each development stage, and the frequency corresponding to each development stage may also be preset in the server by users such as development of the financial service system, management personnel, etc. In step S301, after determining the development stage in which the financial service system is located in the development process, the server may determine a corresponding test risk identification frequency according to the development stage, then determine a stage-associated test risk factor and a basic test risk factor in a preset test risk factor set according to the test risk identification frequency, and perform subsequent calculation and output processing of the test risk identification result. Specifically, in step S302, the preset test risk factor set may include a stage-associated test risk factor pool and a basic test risk factor pool, that is, each test risk factor may be classified first, and then divided into stage-associated test risk factors or basic test risk factors according to whether it is related to the development stage, where multiple stage-associated test risk factors form an associated test risk factor pool, and multiple basic test risk factors form a basic test risk factor pool, so that the server may quickly obtain stage-associated test risk factors corresponding to the development stage from the stage-associated test risk factor pool according to the test risk identification frequency, and directly obtain basic test risk factors from the basic test risk factor pool. According to the scheme of the embodiment, the test risk identification result can be obtained through the test risk identification frequency matched with the scheme in different research and development stages, and the efficiency of obtaining the test risk factors in the corresponding research and development stages can be improved.
In one embodiment, as shown in fig. 4, in step S204, adjusting a stage correlation factor operation bit in a preset test risk result recognition model according to a development stage to obtain a target test risk result recognition model corresponding to the development stage may include:
step S401, determining a risk test dimension sub-model to be adjusted in a preset test risk result identification model according to the research and development stage.
In this step, the preset test risk result recognition model may include a plurality of risk test dimension sub-models, where each risk test dimension sub-model is used to perform test risk recognition on different risk test dimensions, and the risk test dimension sub-model to be adjusted refers to a risk test dimension sub-model including a stage correlation factor operation bit in the preset test risk result recognition model. Specifically, a plurality of risk test dimension sub-models in a preset test risk result identification model can be classified, and the risk test dimension sub-models containing stage correlation factor operation bits are subjected to adjustable identification, so that a server can determine a risk test dimension sub-model to be adjusted in the risk test dimension sub-model with the adjustable identification according to a research stage, and the risk test dimension sub-model to be adjusted in the research stage can be found relatively quickly. As an example, the preset test risk result recognition model may include a risk test dimension sub-model for weighting the encoded risk dimension, a risk test dimension sub-model for weighting the bottleneck program problem, a risk test dimension sub-model for weighting the bottleneck environment problem, and the like, where the risk test dimension sub-model for weighting the encoded risk dimension may not be adjustably identified, and the risk test dimension sub-model for weighting the bottleneck program problem and the risk test dimension sub-model for weighting the bottleneck environment problem may be adjustably identified, that is, the risk test dimension sub-model for weighting the encoded risk dimension may be mainly determined by the encoding efficiency and the encoding progress, and the risk test dimension sub-model for weighting the bottleneck program problem and the risk test dimension sub-model for weighting the bottleneck environment problem may involve the influence of the variation of factors such as the number of test problems in the early stage, the middle stage or the later stage of the test, and the like, so that the adjustment is required.
Step S402, according to factor data input format information of stage association factor operation bits in the development stage in the risk test dimension sub-model to be adjusted, the stage association factor operation bits in the risk test dimension sub-model to be adjusted are adjusted, and a target test risk result identification model corresponding to the development stage is obtained.
In this step, the server may adjust the stage-associated factor calculation bit in the risk test dimension sub-model to be adjusted according to the factor data input format information of the stage-associated factor calculation bit in the development stage in the risk test dimension sub-model to be adjusted, and may refer to the above example, for example, adjust the expression of the second factor by the second weighting factor to be fourth factor by the fourth weighting factor+fifth factor by the fifth weighting factor or sixth factor by the sixth weighting factor according to the factor data input format information, so that the data input format of the corresponding factor meets the operation requirement, and the specific adjustment mode may be set according to the operation requirement of the risk test dimension in the development stage.
In an embodiment, the target test risk result recognition model corresponding to the development stage may include each risk test dimension sub-model and a risk summary sub-model, after the multiple target test risk factors and corresponding weighting coefficients are input into the target test risk result recognition model, the target test risk result recognition model may obtain a risk test sub-result corresponding to each risk test dimension through each risk test dimension sub-model according to the multiple target test risk factors and corresponding weighting coefficients, and then may further obtain a test risk recognition result corresponding to the development stage through the risk summary sub-model according to the risk test sub-result corresponding to each risk test dimension. That is, the target test risk result recognition model may calculate a risk test sub-result corresponding to each risk test dimension through each risk test dimension sub-model, aggregate the risk test sub-results through a risk aggregation sub-model to obtain a test risk recognition result corresponding to a development stage, and as an example, the target test risk result recognition model may include a risk test dimension sub-model for weighting a coded risk dimension, a risk test dimension sub-model for weighting a bottleneck program problem, a risk test dimension sub-model for weighting a bottleneck environment problem, and the like, each risk test dimension sub-model may calculate a risk test sub-result corresponding to each risk test dimension according to a corresponding target test risk factor and a corresponding weighting coefficient, and calculate what kind of target test risk factor and a corresponding weighting coefficient are specifically adopted and set by a relevant person according to a test risk operation logic, and set the risk test dimension sub-model for weighting the coded risk dimension is calculated to obtain a risk test sub-result Y1 corresponding to the coded risk dimension, the risk test dimension sub-model for weighting a bottleneck program problem weighting dimension is calculated to obtain a risk test sub-result Y2 corresponding to the risk test dimension for weighting a bottleneck program problem weighting dimension, the risk test sub-dimension for calculating a bottleneck problem weighting risk factor, and the risk test dimension is calculated to obtain a bottleneck problem weighted risk test dimension sub-dimension model for calculating a bottleneck problem risk test risk dimension, and the risk test dimension corresponding to a risk test dimension weighing factor weighing result corresponding to a risk test dimension weighing calculation result, the target test risk result recognition model can summarize the risk test sub-results through a risk summarization sub-model to obtain a test risk recognition result Y=a risk test sub-result Y1 corresponding to a weighted coding risk dimension and a risk test sub-result Y2 corresponding to a bottleneck program problem weighted risk dimension and a risk test sub-result Y3 corresponding to a bottleneck environment problem weighted risk dimension. The scheme of the embodiment can be used for calculating the testing risk of the research and development stage of the financial business system in the research and development process through multiple dimensions, so that the accuracy of testing risk identification is improved.
In one embodiment, as shown in fig. 5, after the test risk recognition result corresponding to the development stage of obtaining the target test risk result recognition model output in step S206, the method of the present application may further include the following steps:
step S501, obtaining a historical test risk identification result corresponding to the development stage.
In this step, the server obtains a historical test risk recognition result corresponding to the development stage, where the historical test risk recognition result may be obtained by performing an average treatment on each test risk recognition result obtained when the development stage performs test risk recognition for the past time, and if the historical test risk recognition result is a test risk recognition result C1 obtained when the development stage performs test risk recognition for the first time, after the development stage performs test risk recognition for the second time, the test risk recognition result C2 obtained when the development stage performs test risk recognition for the second time and the first test risk recognition result C1 may be averaged to be used as a historical test risk recognition result when the development stage performs test risk recognition for the third time.
Step S502, obtaining a test risk change result according to the test risk identification result and the historical test risk identification result.
In this step, the server may obtain a test risk variation result according to a difference between the test risk identification result and the historical test risk identification result. Specifically, the test risk recognition result may be expressed as a score of the test risk, and the server may obtain a test risk variation result according to a difference between the test risk recognition result and the historical test risk recognition result.
Step S503, determining a test risk level corresponding to the research and development stage according to the test risk change result and the historical test risk identification result.
In this step, the server may determine, according to the test risk change result and the historical test risk identification result, a change degree of the current test risk compared with the historical test risk, so as to accurately determine a test risk level corresponding to the research and development stage in the current test risk identification, where the test risk level may be further set to include no risk, low risk, medium risk, high risk, and so on, so that the test risk identification has higher accuracy.
In one embodiment, further, determining the test risk level corresponding to the development stage in step S503 according to the test risk variation result and the historical test risk identification result specifically includes:
Acquiring the ratio of a test risk change result to a historical test risk identification result; and determining a test risk level corresponding to the research and development stage according to the threshold range of the ratio.
In this embodiment, the server may obtain a ratio of the test risk change result to the historical test risk identification result, and obtain a preset plurality of threshold ranges, for example, less than 10%, greater than or equal to 10% and less than 20%, greater than or equal to 20% and less than 30%, greater than or equal to 30%, and the like, based on this, the server may determine a threshold range in which the ratio of the test risk change result to the historical test risk identification result is located, so as to determine a test risk level corresponding to the development stage, where if the ratio is in the threshold range of less than 10%, the test risk level corresponding to the development stage may be determined to be risk-free, if the ratio is in the threshold range of greater than or equal to 10% and less than 20%, the test risk level may be determined to be low, if the ratio is in the threshold range of greater than or equal to 20% and less than 30%, the test risk level may be determined to be high, and the like. The scheme of the embodiment can more accurately determine the test risk of the financial service system in the research and development stage in the research and development process so that relevant personnel can take corresponding countermeasures.
In one embodiment, further, the method of the present application may further comprise the steps of: and updating the historical test risk identification result according to the average processing of the test risk change result and the historical test risk identification result.
Specifically, as described in the foregoing embodiment, the historical test risk recognition result may be obtained by averaging each test risk recognition result obtained when the test risk recognition is performed for the past time in the development stage, for example, after the test risk recognition is performed for the second time in the development stage, the second obtained test risk recognition result C2 may be averaged with the first test risk recognition result C1, so as to obtain the historical test risk recognition result used when the test risk recognition is performed for the third time in the development stage, and thus, in this embodiment, after the test risk level is calculated, the historical test risk recognition result may be updated for the next test risk calculation, for which the server may average the test risk change result obtained this time with the historical test risk recognition result, and the obtained average value may be used as the updated historical test risk recognition result in the next test risk recognition in the development stage.
It should be understood that, although the steps in the flowcharts related to the embodiments described above are sequentially shown as indicated by arrows, these steps are not necessarily sequentially performed in the order indicated by the arrows. The steps are not strictly limited to the order of execution unless explicitly recited herein, and the steps may be executed in other orders. Moreover, at least some of the steps in the flowcharts described in the above embodiments may include a plurality of steps or a plurality of stages, which are not necessarily performed at the same time, but may be performed at different times, and the order of the steps or stages is not necessarily performed sequentially, but may be performed alternately or alternately with at least some of the other steps or stages.
Based on the same inventive concept, the embodiment of the application also provides a testing risk identification device of the financial business system for realizing the testing risk identification method of the financial business system. The implementation of the solution provided by the device is similar to the implementation described in the above method, so the specific limitation in the embodiments of the test risk identification device for one or more financial service systems provided below may refer to the limitation of the test risk identification method for a financial service system hereinabove, and will not be repeated herein.
In one embodiment, as shown in fig. 6, there is provided a test risk identification apparatus of a financial business system, the apparatus 600 may include:
the stage detection module 601 is configured to detect a development stage of the financial service system in a development process;
the factor determining module 602 is configured to determine a stage-associated test risk factor and a basic test risk factor in a preset test risk factor set according to the development stage, so as to obtain a plurality of target test risk factors corresponding to the development stage;
the weighting obtaining module 603 is configured to obtain weighting coefficients corresponding to the plurality of target test risk factors in the development stage;
the model obtaining module 604 is configured to adjust a stage correlation factor operation bit in a preset test risk result identification model according to the development stage, so as to obtain a target test risk result identification model corresponding to the development stage; the target test risk result identification model comprises a stage correlation factor operation bit and a basic factor operation bit;
a data input module 605, configured to input the multiple target test risk factors and corresponding weighting coefficients into the target test risk result recognition model; the target test risk result identification model is used for outputting test risk identification results corresponding to the research and development stage according to basic test risk factors input in basic factor operation bits, weighting coefficients corresponding to the basic test risk factors, stage-associated test risk factors input in stage-associated factor operation bits and weighting coefficients corresponding to the stage-associated test risk factors;
The result obtaining module 606 is configured to obtain a test risk identification result corresponding to the development stage output by the target test risk result identification model.
In one embodiment, the factor determining module 602 is configured to determine a corresponding test risk identification frequency according to the development stage; according to the test risk identification frequency, acquiring a stage-associated test risk factor corresponding to the research and development stage from a stage-associated test risk factor pool of the preset test risk factor set, and acquiring the basic test risk factor according to a basic test risk factor pool of the preset test risk factor set.
In one embodiment, the weight obtaining module 603 is configured to determine factor importance information of the plurality of target test risk factors in the development stage; and determining weighting coefficients corresponding to the target test risk factors in the research and development stage according to the factor importance degree information.
In one embodiment, the model obtaining module 604 is configured to determine, according to the development stage, a risk test dimension sub-model to be adjusted in the preset test risk result identification model; the risk test dimension sub-model comprises the stage correlation factor operation bit; and adjusting the stage correlation factor operation bit in the risk test dimension sub-model to be adjusted according to the factor data input format information of the stage correlation factor operation bit in the research and development stage in the risk test dimension sub-model to be adjusted, so as to obtain a target test risk result identification model corresponding to the research and development stage.
In one embodiment, the target test risk result recognition model is configured to obtain risk test sub-results corresponding to each risk test dimension according to the multiple target test risk factors and the corresponding weighting coefficients through each risk test dimension sub-model, and obtain test risk recognition results corresponding to the development stage according to the risk test sub-results corresponding to each risk test dimension through a risk summary sub-model.
In one embodiment, the result obtaining module 606 is further configured to obtain a historical test risk identification result corresponding to the development stage; obtaining a test risk variation result according to the test risk identification result and the historical test risk identification result; and determining the test risk level corresponding to the research and development stage according to the test risk change result and the historical test risk identification result.
In one embodiment, the result obtaining module 606 is further configured to obtain a ratio of the test risk variation result and the historical test risk identification result; and determining the test risk level corresponding to the research and development stage according to the threshold range of the ratio.
In one embodiment, the result obtaining module 606 is further configured to update the historical test risk identification result according to an average process of the test risk variation result and the historical test risk identification result.
The modules in the test risk identification device of the financial service system can be all or partially implemented by software, hardware and a combination thereof. The above modules may be embedded in hardware or may be independent of a processor in the computer device, or may be stored in software in a memory in the computer device, so that the processor may call and execute operations corresponding to the above modules.
In one embodiment, a computer device is provided, which may be a server, the internal structure of which may be as shown in fig. 7. The computer device includes a processor, a memory, an Input/Output interface (I/O) and a communication interface. The processor, the memory and the input/output interface are connected through a system bus, and the communication interface is connected to the system bus through the input/output interface. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The database of the computer device may be used to store data such as test risk identification results. The input/output interface of the computer device is used to exchange information between the processor and the external device. The communication interface of the computer device is used for communicating with an external terminal through a network connection. The computer program, when executed by a processor, implements a method of identifying test risk for a financial transaction system.
It will be appreciated by those skilled in the art that the structure shown in fig. 7 is merely a block diagram of some of the structures associated with the present application and is not limiting of the computer device to which the present application may be applied, and that a particular computer device may include more or fewer components than shown, or may combine certain components, or have a different arrangement of components.
In one embodiment, a computer device is provided, comprising a memory and a processor, the memory having stored therein a computer program, the processor implementing the steps of the method embodiments described above when the computer program is executed.
In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored which, when executed by a processor, implements the steps of the method embodiments described above.
In an embodiment, a computer program product is provided, comprising a computer program which, when executed by a processor, implements the steps of the method embodiments described above.
It should be noted that, the user information (including, but not limited to, user equipment information, user personal information, etc.) and the data (including, but not limited to, data for analysis, stored data, presented data, etc.) referred to in the present application are information and data authorized by the user or sufficiently authorized by each party, and the collection, use and processing of the related data are required to comply with the related laws and regulations and standards of the related countries and regions.
Those skilled in the art will appreciate that implementing all or part of the above described methods may be accomplished by way of a computer program stored on a non-transitory computer readable storage medium, which when executed, may comprise the steps of the embodiments of the methods described above. Any reference to memory, database, or other medium used in the various embodiments provided herein may include at least one of non-volatile and volatile memory. The nonvolatile Memory may include Read-Only Memory (ROM), magnetic tape, floppy disk, flash Memory, optical Memory, high density embedded nonvolatile Memory, resistive random access Memory (ReRAM), magnetic random access Memory (Magnetoresistive RandomAccess Memory, MRAM), ferroelectric Memory (Ferroelectric RandomAccess Memory, FRAM), phase change Memory (Phase Change Memory, PCM), graphene Memory, and the like. Volatile memory can include random access memory (RandomAccess Memory, RAM) or external cache memory, and the like. By way of illustration, and not limitation, RAM can be in the form of a variety of forms, such as static random access memory (Static RandomAccess Memory, SRAM) or dynamic random access memory (Dynamic RandomAccess Memory, DRAM), and the like. The databases referred to in the various embodiments provided herein may include at least one of relational databases and non-relational databases. The non-relational database may include, but is not limited to, a blockchain-based distributed database, and the like. The processors referred to in the embodiments provided herein may be general purpose processors, central processing units, graphics processors, digital signal processors, programmable logic units, quantum computing-based data processing logic units, etc., without being limited thereto.
The technical features of the above embodiments may be arbitrarily combined, and all possible combinations of the technical features in the above embodiments are not described for brevity of description, however, as long as there is no contradiction between the combinations of the technical features, they should be considered as the scope of the description.
The above examples only represent a few embodiments of the present application, which are described in more detail and are not to be construed as limiting the scope of the present application. It should be noted that it would be apparent to those skilled in the art that various modifications and improvements could be made without departing from the spirit of the present application, which would be within the scope of the present application. Accordingly, the scope of protection of the present application shall be subject to the appended claims.

Claims (12)

1. A method for identifying test risk of a financial business system, the method comprising:
detecting the research and development stage of the financial business system in the research and development process;
determining a stage-associated test risk factor and a basic test risk factor in a preset test risk factor set according to the research and development stage to obtain a plurality of target test risk factors corresponding to the research and development stage;
Acquiring weighting coefficients corresponding to the target test risk factors in the research and development stage;
adjusting a stage correlation factor operation bit in a preset test risk result identification model according to the research and development stage to obtain a target test risk result identification model corresponding to the research and development stage; the target test risk result identification model comprises a stage correlation factor operation bit and a basic factor operation bit;
inputting the target test risk factors and the corresponding weighting coefficients into the target test risk result identification model; the target test risk result identification model is used for outputting test risk identification results corresponding to the research and development stage according to basic test risk factors input in basic factor operation bits, weighting coefficients corresponding to the basic test risk factors, stage-associated test risk factors input in stage-associated factor operation bits and weighting coefficients corresponding to the stage-associated test risk factors;
and acquiring a test risk identification result corresponding to the research and development stage output by the target test risk result identification model.
2. The method of claim 1, wherein determining phase-associated test risk factors and base test risk factors in a set of pre-set test risk factors from the development phase comprises:
Determining corresponding test risk identification frequency according to the research and development stage;
according to the test risk identification frequency, acquiring a stage-associated test risk factor corresponding to the research and development stage from a stage-associated test risk factor pool of the preset test risk factor set, and acquiring the basic test risk factor according to a basic test risk factor pool of the preset test risk factor set.
3. The method of claim 1, wherein the obtaining the weighting coefficients corresponding to the plurality of target test risk factors during the development stage comprises:
determining factor importance degree information of the target test risk factors in the research and development stage;
and determining weighting coefficients corresponding to the target test risk factors in the research and development stage according to the factor importance degree information.
4. The method of claim 1, wherein the step of adjusting the stage-associated factor operation bits in the preset test risk result recognition model according to the development stage to obtain the target test risk result recognition model corresponding to the development stage includes:
determining a risk test dimension sub-model to be adjusted in the preset test risk result identification model according to the research and development stage; the risk test dimension sub-model comprises the stage correlation factor operation bit;
And adjusting the stage correlation factor operation bit in the risk test dimension sub-model to be adjusted according to the factor data input format information of the stage correlation factor operation bit in the research and development stage in the risk test dimension sub-model to be adjusted, so as to obtain a target test risk result identification model corresponding to the research and development stage.
5. The method according to any one of claims 1 to 4, wherein the target test risk result recognition model is configured to obtain, by using each risk test dimension sub-model, a risk test sub-result corresponding to each risk test dimension according to the plurality of target test risk factors and the corresponding weighting coefficients, and obtain, by using a risk summary sub-model, a test risk recognition result corresponding to the development stage according to the risk test sub-result corresponding to each risk test dimension.
6. The method according to claim 1, wherein after the obtaining the test risk identification result corresponding to the development stage output by the target test risk result identification model, the method further comprises:
acquiring a historical test risk identification result corresponding to the research and development stage;
obtaining a test risk variation result according to the test risk identification result and the historical test risk identification result;
And determining the test risk level corresponding to the research and development stage according to the test risk change result and the historical test risk identification result.
7. The method of claim 6, wherein determining the test risk level corresponding to the development stage based on the test risk variation result and the historical test risk identification result comprises:
acquiring the ratio of the test risk change result to the historical test risk identification result;
and determining the test risk level corresponding to the research and development stage according to the threshold range of the ratio.
8. The method according to claim 6 or 7, characterized in that the method further comprises:
and updating the historical test risk identification result according to the average processing of the test risk change result and the historical test risk identification result.
9. A test risk identification device for a financial transaction system, the device comprising:
the stage detection module is used for detecting the research and development stage of the financial business system in the research and development process;
the factor determining module is used for determining a stage-associated test risk factor and a basic test risk factor in a preset test risk factor set according to the research and development stage to obtain a plurality of target test risk factors corresponding to the research and development stage;
The weighting acquisition module is used for acquiring weighting coefficients corresponding to the target test risk factors in the research and development stage;
the model obtaining module is used for adjusting a stage correlation factor operation position in a preset test risk result identification model according to the research and development stage to obtain a target test risk result identification model corresponding to the research and development stage; the target test risk result identification model comprises a stage correlation factor operation bit and a basic factor operation bit;
the data input module is used for inputting the target test risk factors and the corresponding weighting coefficients into the target test risk result identification model; the target test risk result identification model is used for outputting test risk identification results corresponding to the research and development stage according to basic test risk factors input in basic factor operation bits, weighting coefficients corresponding to the basic test risk factors, stage-associated test risk factors input in stage-associated factor operation bits and weighting coefficients corresponding to the stage-associated test risk factors;
and the result acquisition module is used for acquiring the test risk identification result corresponding to the research and development stage output by the target test risk result identification model.
10. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor implements the steps of the method of any one of claims 1 to 8 when the computer program is executed.
11. A computer readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, implements the steps of the method of any of claims 1 to 8.
12. A computer program product comprising a computer program, characterized in that the computer program, when executed by a processor, implements the steps of the method of any one of claims 1 to 8.
CN202311565794.1A 2023-11-22 2023-11-22 Method, device, equipment and medium for identifying testing risk of financial business system Pending CN117522138A (en)

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