Performance index influence factor processing method and device, equipment, medium and product

Abstract

The invention provides a performance index influence factor processing method and device, equipment, a medium and a product, and relates to the technical field of computers, and the method comprises the steps: constructing a mapping relation table related to performance indexes of the security and futures industry; according to the mapping relation table, constructing an input / output and parameter value tree corresponding to the performance indexes; establishing a performance influence factor tree of the performance indexes according to the input and output and the parameter value tree; determining multiple groups of influence factors according to the performance influence factor tree; and selecting different groups of influence factors for testing according to the test conditions so as to determine the influence information of the influence factors on the performance indexes. Based on the method, the influence factors of the performance indexes of the security and futures industry are extracted, the system performance condition can be analyzed more comprehensively, and operation and maintenance personnel can know system performance risks caused by business changes in time and make response measures in advance.

Description

Technical Field

[0001] The present invention relates to the field of computer technology, and in particular to a method, device, equipment, medium and product for processing performance index influencing factors. Background Art

[0002] Securities and futures industry software is a complex software system with the characteristics of high concurrency, high throughput, and low latency. Due to regulatory or online requirements, core institutions and securities companies need to perform performance testing on the system to verify whether the system performance level meets expectations.

[0003] At present, the performance testing method in the industry is based on the performance indicators of the "Securities and Futures Industry Information System Stress Testing Guide", combined with the requirements document and production data to determine the business type and data required for the indicator test, and to construct the scenario data according to the established values. The problem with this method is that the business data is fixed, there is a lack of impact analysis on it, and it is impossible to verify the impact of changes in influencing factors on the system's performance.

[0004] Therefore, there is an urgent need for a method to process the influencing factors based on performance indicators suitable for securities and futures industry software. Summary of the invention

[0005] The present invention provides a method, device, equipment, medium and product for processing factors affecting performance indicators, so as to solve the defects of the prior art in how to process factors affecting performance indicators in the securities and futures industries, realize a more comprehensive analysis of system performance, and facilitate operation and maintenance personnel to timely understand the system performance risks caused by business changes and formulate countermeasures in advance.

[0006] The present invention provides a method for processing performance index influencing factors, comprising the following steps: Construct a mapping relationship table related to the performance indicators of the securities and futures industry; According to the mapping relationship table, construct an input / output and parameter value tree corresponding to the performance indicator; According to the input-output and parameter value tree, a performance influencing factor tree of the performance indicator is established; Determining multiple groups of impact factors according to the performance impact factor tree; Different groups of influencing factors are selected for testing according to the test conditions to determine the influence information of the influencing factors on the performance indicators.

[0007] According to a method for processing a performance indicator influencing factor provided by the present invention, constructing an input / output and parameter value tree corresponding to the performance indicator according to the mapping relationship table, including: Establishing a tree-type result indicator analysis tree; the root node of the tree-type result indicator analysis tree is the performance indicator; Determine independent input and output according to the mapping relationship table; The independent input and output are used as the first-level branch nodes of the tree-type result indicator analysis tree, and the input and output that depend on the i-th-level branch nodes are used as i+1-level branch nodes, until all the input and output are added to the tree-type result indicator analysis tree; the i-th-level branch nodes include the first-level branch nodes; the first-level branch nodes are child nodes of the root node; Determining parameters and parameter values ​​of the independent input and output; The parameters are added to the next layer of branch nodes of the i-th layer of branch nodes, and the parameter values ​​are added to the leaf nodes of the layer of branch nodes corresponding to the parameters, to obtain the input-output and parameter value tree.

[0008] According to a method for processing a performance indicator influencing factor provided by the present invention, the performance influencing factor tree of the performance indicator is established according to the input / output and parameter value tree, including: Using the elements of the performance indicator to be tested as the first-level branch nodes of the performance impact factor tree; Taking all independent input-output ratios in the first-layer branch nodes of the input-output and parameter value tree as influencing factors, adding them to the elements of the performance indicator to be tested as the second-layer branch nodes of the performance influencing factor tree; The ratio of the number of inputs and outputs of the n+1th layer branch nodes to the nth layer branch nodes is taken as an influencing factor and added to the n+1th layer branch nodes of the performance influencing factor tree to establish a performance influencing factor tree for the performance indicator; the nth layer branch nodes include the second layer branch nodes.

[0009] According to a method for processing performance indicator influencing factors provided by the present invention, determining multiple groups of influencing factors according to the performance influencing factor tree includes: Collect production data of the system; Based on the performance impact factor tree, converting the production data into performance factor values; From the performance factor values, obtain the maximum value of each influencing factor; According to the maximum value of each impact factor, determine the relative value of each impact factor; The influencing factors are grouped according to the relative value of each influencing factor to obtain multiple groups of influencing factors.

[0010] According to a method for processing performance index influencing factors provided by the present invention, the influencing factors of different groups are selected for testing according to test conditions to determine the influence information of the influencing factors on the performance index, including: Construct basic scenarios for indicator testing and scenarios for adjusting indicator performance factors; The indicator test basic scenario is adopted to test the influencing factors selected based on the test conditions to obtain a first test result; According to the indicator performance factor adjustment scenario, adjusting the influencing factors selected based on the test conditions; The index is used to test the basic scenario, and the adjusted influencing factors are tested to obtain a second test result; Influence information of the influencing factor on the performance indicator is determined according to the first test result and the second test result.

[0011] According to a method for processing performance indicator influencing factors provided by the present invention, the construction of a mapping relationship table related to performance indicators of the securities and futures industry includes: Obtain technical and business documents related to the securities and futures industry; Performing structural analysis on the technical and business documents to construct a dictionary table of transaction status, business type, system module, and input and output; A mapping relationship table related to the performance indicators is constructed according to the dictionary table.

[0012] The present invention also provides a device for processing performance index influencing factors, comprising the following modules: A mapping relationship table construction module is used to construct a mapping relationship table related to performance indicators of the securities and futures industry; An input-output and parameter value tree construction module, used to construct an input-output and parameter value tree corresponding to the performance indicator according to the mapping relationship table; A performance impact factor tree establishment module, used to establish a performance impact factor tree of the performance indicator according to the input and output and parameter value tree; An impact factor grouping module, used to determine multiple groups of impact factors according to the performance impact factor tree; The influencing factor processing module is used to select different groups of influencing factors for testing according to the test conditions to determine the influence information of the influencing factors on the performance indicators.

[0013] The present invention also provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the method for processing the performance indicator influencing factor as described above is implemented.

[0014] The present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the method for processing the performance indicator influencing factor as described in any one of the above is implemented.

[0015] The present invention also provides a computer program product, including a computer program, wherein when the computer program is executed by a processor, the computer program implements any of the above-mentioned methods for processing the performance indicator influencing factors.

[0016] The processing method, device, equipment, medium and product of the performance index influencing factor provided by the present invention construct a mapping relationship table related to the performance index of the securities and futures industry; construct the input-output and parameter value tree corresponding to the performance index according to the mapping relationship table; establish the performance index influencing factor tree according to the input-output and parameter value tree; determine multiple groups of influencing factors according to the performance influencing factor tree; select different groups of influencing factors for testing according to the test conditions to determine the influence information of the influencing factors on the performance index. Based on the above method, the extraction of the influencing factors of the performance index of the securities and futures industry can be realized, and a more comprehensive analysis of the system performance can be carried out, which is convenient for operation and maintenance personnel to timely understand the system performance risks caused by business changes and formulate countermeasures in advance. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0018] Figure 1 It is a flow chart of the method for processing the performance index influencing factors provided by the present invention.

[0019] Figure 2 It is one of the structural schematic diagrams of the input, output and parameter value tree provided by the present invention.

[0020] Figure 3 It is one of the structural schematic diagrams of the performance impact factor tree provided by the present invention.

[0021] Figure 4 This is the second structural diagram of the input, output and parameter value tree provided by the present invention.

[0022] Figure 5 This is the second structural schematic diagram of the performance impact factor tree provided by the present invention.

[0023] Figure 6 It is a flow chart of the method for extracting the influencing factors of the performance indicators of the securities and futures industries provided by the present invention.

[0024] Figure 7 It is a data flow diagram of a trader's order request provided by the present invention.

[0025] Figure 8It is a structural schematic diagram of a device for processing performance indicator influencing factors provided by the present invention.

[0026] Fig. 9 It is a structural schematic diagram of the electronic device provided by the present invention. DETAILED DESCRIPTION

[0027] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be clearly and completely described below in conjunction with the drawings of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0028] The purpose of the present invention is to provide a method for extracting and applying factors affecting performance indicators in the securities and futures industry, to establish a performance factor extraction model based on indicators, and to extract the performance influencing factors corresponding to the indicators by analyzing the technical documents and codes of the system; in the application of the factors, by analyzing the production flow data, the performance factor values ​​of the basic scenario and the adjustment scenario are obtained, and whether the factors have an impact on the indicators is analyzed according to the execution results. For the factors that have an impact, future market risks can be prompted and data support can be provided for subsequent system optimization.

[0029] Combine the following Figure 1-Figure 9 The present invention describes the processing method, device, equipment, medium and product of the performance index influencing factor.

[0030] Figure 1 is a flow chart of the method for processing the performance index influencing factors provided by the present invention, such as Figure 1 As shown, the method includes the following: Step 101: Construct a mapping relationship table related to performance indicators of the securities and futures industry.

[0031] In the securities and futures industry, performance indicators can be used to measure the efficiency and responsiveness of the system. Specific performance indicators vary according to different application scenarios and business needs, and may include transaction throughput, concurrency, response time, latency, transaction success rate, etc.

[0032] In one embodiment, technical and business documents related to the securities and futures industry are obtained, and then the technical and business documents are structurally analyzed to build a dictionary table of transaction status, business type, system module and input and output, and finally a mapping relationship table is built based on the dictionary table.

[0033] For example, various technical and business documents are obtained from the specification documents and systems related to the securities and futures industry. The technical and business documents may include business requirements documents, non-functional requirements documents, detailed design documents, etc. Then, the technical and business documents are structurally analyzed to build a dictionary table of information such as transaction status, business type, system module, input and output, etc. Among them, input and output may include interface input and output, external system input and output, internal output, etc.; interface input and output and external system input and output refer to the inflow and outflow of the system under test through external interfaces and external systems, which may include request input classes and notification output classes, and the response class is included in the request class analysis data flow; internal output refers to the quantitative or timed output generated when the system module does not receive external input. Finally, the performance indicators are refined according to the transaction status, and multiple mapping relationship tables are established based on the dictionary table. It can be understood that refining the performance indicators according to the transaction status means analyzing the corresponding transaction status according to the performance indicator test content. If the same performance indicator can correspond to multiple transaction states, the indicator is split and tested separately.

[0034] The mapping relationship table may include a mapping relationship table between business type and index (i.e., performance index), a mapping relationship table between business type and input / output, a mapping relationship table between transaction status and input / output, a first mapping relationship table between input / output and module (i.e., system module), and a second mapping relationship table between input / output and module (i.e., system module). The first mapping relationship table between input / output and module refers to the data flow through the module from the interface and external input from sending a request to the system to generating a corresponding response, and the data flow through the module from the system generating an output to returning it to the user. The second mapping relationship table between input / output and module refers to the flow through the module of all messages generated after the input and its sending a request to the system.

[0035] Step 102: construct an input / output and parameter value tree corresponding to the performance indicator according to the mapping relationship table.

[0036] It can be understood that the input-output and parameter value tree is used to help understand and analyze the relationship between performance indicators, influencing factors and the interaction between different parameters, that is, to display the relationship between input-output, parameters and parameter values ​​through a tree structure.

[0037] In one embodiment, the input / output and parameter value tree is constructed in the following manner: establish a tree-type result indicator analysis tree; the root node of the tree-type result indicator analysis tree is a performance indicator; determine independent input / output according to a mapping relationship table; use the independent input / output as the first-level branch node of the tree-type result indicator analysis tree, and use the input / output that depends on the i-th level branch node as the i+1-level branch node, until all input / output are added to the tree-type result indicator analysis tree; the i-th level branch node includes the first-level branch node; the first-level branch node is a child node of the root node; determine the parameters and parameter values ​​of the independent input / output; add the parameters to the next level branch node of the i-th level branch node, and add the parameter values ​​to the leaf nodes of the corresponding parameter level branch node to obtain the input / output and parameter value tree.

[0038] For example, first establish a tree-type result indicator analysis tree, then sort out the inputs and outputs corresponding to the indicators according to the business type and indicator mapping relationship table, and the business type and input and output mapping relationship table; obtain the modules corresponding to the inputs and outputs, and identify other inputs and outputs from the modules; according to the transaction status and input and output mapping relationship table, filter out the inputs and outputs under the transaction status corresponding to the indicators from all the inputs and outputs obtained from the above analysis; analyze all current inputs and outputs to find out whether there is a dependency relationship; if the dependency source of a certain input and output does not exist, it is an independent input and output. Take all independent inputs and outputs as the first-level branch nodes N1, N2, ..., N of the tree-type result indicator analysis tree. n ; Output the input of dependency N1 as the second-level branch node N of the tree-type result indicator analysis tree 1,1 、N 1,2 ,......,N 1,n ; If the same input and output depends on multiple source inputs and outputs, add them to each upper node respectively; and so on, until all input and output data factors are placed in the branch nodes. Further, analyze the optional parameters of independent inputs and outputs to obtain the influential parameters and parameter values; then place the parameters in the corresponding input and output N1 or N 1,n The next layer of branch nodes PN 1,1 PN 1,2 ......、PN 1,n ; Place each value in the parameter in the corresponding parameter PN 1,1 The leaf node LN of the last layer 1,1,1 , LN 1,1,2 ,......,PN 1,n , and finally get the input, output and parameter value tree, such as Figure 2 shown.

[0039] In one embodiment, optional parameters of independent input and output are analyzed to obtain influential parameters and parameter values, including: based on the indicator trading status, analyzing the interface document and system code to check whether there are different business logic processing branches for each parameter value; if there is no branch, different values ​​of the parameter have no effect on the system; if there is a code branch, different values ​​of the parameter have an impact on the system.

[0040] Step 103: Establish a performance influencing factor tree of the performance indicator according to the input / output and parameter value tree.

[0041] The performance influencing factor tree of performance indicators is a tool that uses a tree structure to show how different factors affect system performance, helping to understand the relationship between different parameters or factors in the system.

[0042] In one embodiment, a performance impact factor tree is established in the following manner: the elements of the performance indicator to be tested are used as the first-level branch nodes of the performance impact factor tree; the proportions of all independent inputs and outputs in the first-level branch nodes of the input, output and parameter value tree are used as impact factors, added to the elements of the performance indicator to be tested, as the second-level branch nodes of the performance impact factor tree; the ratio of the number of inputs and outputs of the n+1-level branch nodes to the n-level branch nodes is used as an impact factor, added to the n+1-level branch nodes of the performance impact factor tree to establish a performance impact factor tree for the performance indicator; the n-level branch nodes include the second-level branch nodes.

[0043] For example, the first layer of branch nodes in the performance impact factor tree are necessary elements for the input of the performance test scenario, which may include elements such as throughput and concurrency to test performance indicators; the second layer of branch nodes are independent inputs, which split the throughput of the previous layer into specific business throughputs, and each impact factor exists as the ratio of the current business level to the business level of all inputs; other layers of input and output branch nodes depend on the branch nodes of the previous layer, and the ratio of the number of corresponding branch nodes of the previous layer is obtained as the impact factor.

[0044] For leaf nodes, if they correspond to the same branch node, it means that in the same domain, the number of branch nodes is the same as the input and output branch nodes of the upper layer. The ratio of the number of leaf node parameter values ​​divided by the number of input and output branch nodes is calculated as the influencing factor; the sum of the influencing factor values ​​in the second-layer branch nodes and leaf nodes in the same representation domain is equal to 100%; the increase in the value of each influencing factor represents the decrease in the values ​​of other influencing factors, so this type of influencing factor is defined as a multidimensional influencing factor, and the other influencing factors are one-dimensional influencing factors; when there are only two multidimensional influencing factors in the same representation domain, the value adjustment of one influencing factor can represent the value adjustment of another factor, so only one multidimensional influencing factor is retained.

[0045] If the performance factor obtained from the above analysis is already included in the data that needs to be adjusted in the basic scenario of the indicator test, it will not be used as a factor that needs to be adjusted in the performance factor testing method.

[0046] The factor conversion formula is: ; The concurrency can be the number of concurrent connections (Concurrent Connection Rate, CCR), and the throughput can be the number of transactions per second (Transactions Per Second, TPS). Based on the factor conversion formula, the input, output and parameter value tree is converted into a performance impact factor tree, such as Figure 3 shown.

[0047] According to the dependency of the next layer of the performance impact factor tree on the impact factors of the previous layer, all performance impact factors are numbered from small to large, and a correlation matrix is ​​established, in which rows and columns represent performance impact factors.

[0048] ; in, , that is, the i-th row and j-th column in the matrix is ​​1, indicating that the i-th influencing factor depends on the j-th influencing factor.

[0049] Step 104: Determine multiple groups of impact factors according to the performance impact factor tree.

[0050] According to the performance impact factor tree, all impact factors are grouped to obtain multiple groups of impact factors. In one embodiment, production data of the system is collected; based on the performance impact factor tree, the production data is converted into performance factor values; from the performance factor values, the maximum value of each impact factor is obtained; according to the maximum value of each impact factor, the relative value of each impact factor is determined; according to the relative value of each impact factor, the impact factors are grouped to obtain multiple groups of impact factors.

[0051] For example, collect multi-day production data of the system, pre-process the production data to obtain the influencing factor values, that is, calculate the performance factor values ​​in the multi-day production data according to the factor conversion formula of the performance influencing factor tree. Then, divide the groups based on the fluctuation range of the influencing factors to determine multiple groups of influencing factors, which can include the following steps: obtain the maximum value Max of each influencing factor; then divide each influencing factor by the maximum value to obtain the relative value of the influencing factor; calculate the overall standard deviation of the relative value of each influencing factor in the multi-day production data; wherein, the smaller the result, the more stable the factor and the less likely it is to change. The probability of factor change analyzed according to the result value is shown in Table 1: Table 1 Factor change probability table Based on the accumulation of past tests, we can obtain the influencing factors with large, medium and small impacts on the indicators.

[0052] Step 105: Select different groups of influencing factors for testing according to the test conditions to determine the influence information of the influencing factors on the performance indicators.

[0053] Selecting influencing factors in different groups based on differences in test conditions can include: When designing project tests, performance test factors can be dynamically selected based on cycle cost and quality requirements, which can include the following: 1) For all factors, cycle & cost: no clear requirements, loose time; quality: extremely high quality requirements, the system needs to be fully tested to verify the impact of all business changes on system performance; recommended for applicable situations: new system online, first comprehensive test. 2) For factors with large, medium, and small probability of change, cycle & cost: relatively loose cycle and cost requirements; quality: high quality requirements, verify the impact of most business changes on system performance; recommended for applicable situations: the system has undergone major technical changes, and it has been clearly determined that it has an impact on performance. 3) For factors with large and medium probability of change, cycle & cost: tight cycle; quality: medium quality requirements, verify the impact of some business changes on system performance; recommended for applicable situations: the system has medium and low technical changes, which may have an impact on system performance. 4) For factors with a high probability of change and factors known to have an impact on indicators, Cycle & Cost: The cycle is extremely tight; Quality: Only basic performance requirements are made to verify the impact of business changes with a small number of orders of magnitude and frequent adjustments on system performance; Applicable situation recommendations: If only business changes occur in the system, theoretical analysis should not cause any impact on system performance.

[0054] After obtaining the impact factor, the impact factors it depends on are obtained from the correlation matrix to obtain all the impact factors. The adjustment of the impact factors it depends on also indirectly reflects the adjustment of the factor.

[0055] In one embodiment, an indicator test basic scenario and an indicator performance factor adjustment scenario are constructed; the indicator test basic scenario is used to test the influencing factors selected based on the test conditions to obtain a first test result; according to the indicator performance factor adjustment scenario, the influencing factors selected based on the test conditions are adjusted; the indicator test basic scenario is used to test the adjusted influencing factors to obtain a second test result; and the influencing factors of the performance indicators are determined based on the first test result and the second test result.

[0056] For example, building a basic scenario for indicator testing can include the following steps: 1.1) If the demander and the product designer have expectations for the value of a certain business data, the business data value is obtained according to the expected value; 1.2) If the demand side and the product designer have no expectation of the value of a certain business data, the maximum value Max, the minimum value Min, and the most frequent value Fre of the performance factor corresponding to the business data are obtained from the production flow data; 1.3) Obtain business data values ​​based on the PERT three-point analysis method: ; The formula indicates that the probability of business data in production being taken as Base is 50%; 1.4) Construct test scenarios based on the test steps and constraints described in the indicators and the business data obtained through analysis.

[0057] For example, constructing an indicator performance factor adjustment scenario may include the following steps: 2.1) In order to analyze the impact of test results, the factor values ​​must satisfy the arithmetic distribution; 2.2) Different methods are applied to calculate the adjusted factor values ​​for multi-dimensional impact factors and one-dimensional impact factors respectively; 2.3) In the multi-dimensional influencing factor algorithm, the change in the number of factors does not represent a single increase or decrease, but adjusts the overall value distribution of a parameter while the input and output quantities remain unchanged. Therefore, the direction of change is not only an increase, but also covers the upper and lower limits of production. When there are multiple days of production data, the calculation formula is as follows: ; Among them, CD represents the value of the impact factor in the basic scenario, MPD Indicates the value of the influencing factor in multi-day production data, EJ 1. EJ 2 means twice factor adjustment value; 2.4) When the performance factor exists only for a single day or there is no production data record, the calculation formula is as follows: ; 2.5) Adjustment of one-dimensional impact factor only affects its own value, so adjustment in a general direction is convenient for finding system performance bottlenecks: ; 2.6) It should be noted that when adjusting the proportional factors under the same domain, that is, the factors that need to add up to 100%, when the value of a certain factor changes, the other factors need to be redistributed in proportion. The calculation logic is as follows: When the factor values ​​in the same domain in the basic scenario are A1, A2, and A3: ; When the value of A1 is adjusted to B1, the calculation formulas for the adjusted B2 and B3 are as follows: ; .

[0058] For example, analyzing the impact of test result identification factors on indicators can include the following steps: 3.1) Analyze the indicator results and set the following formula based on the 97% effectiveness principle in securities and futures trading: Case 1: ; in, R The test value of the indicator in the basic scenario (i.e. the first test result) is obtained. R e is the test result after the influence factor is adjusted (i.e. the second test result). The above formula indicates that the change of the factor has an impact on the indicator result. When the result exceeds 50%, the factor has a large impact on the indicator; when the result is between 10% and 50%, the factor has a medium impact on the indicator; when the result is less than 10%, the factor has a small impact on the indicator.

[0059] 3.2) You can also further adjust the performance factor value for testing to clarify the degree of impact on system performance. At the same time, you need to formulate an optimization strategy and record the factor in the core factor library to facilitate subsequent project selection based on different degrees of impact.

[0060] Case 2: ; The above formula indicates that the factor adjustment has no significant impact on the performance results.

[0061] The processing method of the performance indicator influencing factors provided by the embodiment of the present invention is through constructing a mapping relationship table related to the performance indicators of the securities and futures industry; constructing the input-output and parameter value tree corresponding to the performance indicators according to the mapping relationship table; establishing the performance influencing factor tree of the performance indicators according to the input-output and parameter value tree; determining multiple groups of influencing factors according to the performance influencing factor tree; selecting different groups of influencing factors for testing according to the test conditions to determine the impact information of the influencing factors on the performance indicators. The present invention is based on various system indicators defined in the specification documents related to the securities and futures industry, and extracts the influencing factors of each indicator through the performance influencing factor analysis method, and can establish an indicator factor library suitable for six types of systems in the securities and futures industry, including trading, clearing, market conditions, account opening, risk control, and communication; and constructing test scenarios in combination with the factors to obtain the performance impact of each influencing factor on the system when it changes, and conduct a more comprehensive analysis of the system performance, so that the operation and maintenance personnel can timely understand the system performance risks caused by business changes and formulate countermeasures in advance.

[0062] In order to further analyze and illustrate the processing method of the performance index influencing factors provided by the present invention, refer to the following examples.

[0063] It is understandable that the regulatory documents related to the securities and futures industry are stress testing guidelines within the industry issued by authoritative organizations, including stress testing indicators for six types of systems: securities core, securities operations, futures core, and trading, clearing, market conditions, account opening, risk control, and communications in futures operating institutions. Various institutions must test the results of each indicator according to the requirements of the guidelines to verify the performance level of the system.

[0064] Based on this, the embodiment of the present invention extracts the performance influencing factors corresponding to the indicators according to the characteristics of the system and the indicators, and verifies the impact of the changes in the factor values ​​on the indicator results, so as to conduct a more comprehensive analysis of the system performance, so as to facilitate the operation and maintenance personnel to timely understand the system performance risks caused by business changes and formulate countermeasures in advance.

[0065] Taking the order peak throughput rate indicator in a small trading system as an example, this embodiment introduces the factor extraction and application method of the indicator. Figure 6 As shown, the method may include the following steps: S1: Based on the relevant regulatory documents of the securities and futures industry and various technical and business documents of the system, a dictionary table of transaction status, business type, system module, input and output is constructed through structural analysis, as shown in Table 2.

[0066] Table 2 Based on the test content of order peak throughput in the stress guide, the indicators are refined into order peak throughput (call auction) and order peak throughput (continuous trading) according to the transaction status, as shown in Table 3.

[0067] Table 3 Transaction status and indicator mapping table Based on the analysis and understanding of the business corresponding to the indicator, a business type and indicator mapping relationship table and a business type and input and output mapping relationship table are established, as shown in Table 4.

[0068] Table 4 According to the analysis of system code and system detailed design documents, from the perspective of user sending request to returning corresponding response, analyze the data flow through the module, and establish the first mapping relationship table between input and output and module; according to the overall operation perspective of user request sent to the system, establish the second mapping relationship table between input and output and module. Figure 7 As shown, you can refer to the analysis of the trader's order request in the overall operation data flow of the system to establish the first mapping relationship table between input and output and the module, and the second mapping relationship table between input and output and the module, as shown in Table 5-Table 6.

[0069] Table 5 Input / output and module first mapping relationship table Table 6 Input / output and module second mapping relationship table According to the transaction status corresponding to the input and output, a transaction status and input and output mapping relationship table is established, as shown in Table 7.

[0070] Table 7 Transaction status and input / output mapping table S2: Based on the data table of S1, establish the input, output and parameter value tree corresponding to the order peak throughput rate (continuous trading) indicator, which can include the following steps: S21: Obtain the order peak throughput rate (continuous trading) indicator and the corresponding continuous trading status; S22: in the business type and indicator mapping relationship table (Table 4), the business type corresponding to the order peak throughput rate (continuous transaction) is obtained as transaction; S23: in the business type and input / output mapping relationship table (Table 4), the input / output corresponding to the transaction type is obtained, which is a trader order request, a trader order cancellation request, a trader order execution notification, and a bilateral quotation request; S24: Obtain the trader's order request, trader's order cancellation request, trader's order fulfillment notification, and bilateral quotation request flowing through the module as the trading gateway and the trading engine in the input-output and module first mapping relationship table (Table 5); S25: Obtain all inputs and outputs corresponding to the trading gateway and the trading engine from the first mapping relationship table between inputs and outputs and modules (Table 5) and the second mapping relationship table between inputs and outputs and modules (Table 6), which are trader order requests, trader order cancellation requests, trader order execution notifications, and bilateral quotation requests; S26: Obtain in the transaction status and input / output mapping relationship table (Table 7) whether the corresponding transaction status of all the inputs and outputs obtained above includes a continuous transaction; if not, remove the input / output; S26: Analyze the association relationship between the interfaces. The trader order request and the bilateral quotation request are independent requests, which are used as the first-level branch nodes; the trader order cancellation request and the trader order execution notification send notifications when the submitted order request and the bilateral quotation request are cancelled or executed, which are used as the second-level branch nodes with dependent relationships respectively; S27: Parameter analysis is performed on all requests and notifications. Taking the trader order request interface as an example, the reference values ​​are shown in Table 8. Table 8 Trader order request interface parameter value table Analyze the system code to see if there are different logic analyses in each parameter value under the continuous trading state. Determine the parameter values ​​that may have an impact, which may include: buy and sell flags - buy, buy and sell flags - sell, open and close flags - open positions, open and close flags - close positions, contract number - futures contracts, contract number - options contracts, insurance flags - speculation and insurance flags - hedging. For bilateral quotation requests, the parameter values ​​that may have an impact may include: buy and sell flags - buy, buy and sell flags - sell, open and close flags - open positions, open and close flags - close positions, contract number - futures contracts, contract number - options contracts, insurance flags - speculation and insurance flags - hedging. For cancel order requests and order execution notifications, the analysis of the parameter values ​​that may have an impact is the same as above. The business types are the same and will not be listed repeatedly. S28: After the analysis is completed, the input, output and parameter value tree is established, such as Figure 4 shown.

[0071] S3: Convert the input, output and parameter value tree of S2 into a performance factor tree of the order peak throughput index (such as Figure 5 As shown), the following steps may be included: S31: According to the formula, the necessary performance scenario inputs are throughput and the number of concurrent business operations. Because this indicator is a transaction type, the corresponding performance impact factor is defined as the total order rate and the number of concurrent order seats; because the order peak throughput indicator test process includes the adjustment of the total order rate, the total order rate is not used as a business factor that needs to be adjusted in the factor test method; S32: Obtain the trader order request and bilateral quotation request of the first-level branch nodes, and convert them into ratios: trader order request ratio = trader order request / total order request, bilateral quotation request ratio = bilateral quotation request / total order request, the sum of the two is 100%, the adjustment of one factor can represent another factor, so only the trader order request ratio is retained; S33: Obtain the trader's order cancellation request and trader's order execution notification of the second-layer branch node, and convert them into ratios: ordinary order cancellation ratio = order cancellation volume / trader order request volume, ordinary execution ratio = execution volume / trader order request volume, bilateral order cancellation ratio = order cancellation volume / bilateral quotation request volume, bilateral order execution ratio = execution volume / bilateral quotation request volume; S34: Obtain the branch node parameter value. In the buy and sell flag, since there are only two values, buy and sell, only one value ratio is retained. Ordinary order buy ratio = ordinary order buy direction value order quantity / trader order request quantity, ordinary order open position ratio = ordinary order open direction value order quantity / trader order request quantity.

[0072] S35: The number of concurrent order seats, the total order rate, the trader order request ratio, the general order cancellation ratio, the general order transaction ratio, the general order buy direction ratio, the general order opening ratio, the general order futures ratio, the general order speculation ratio, the bilateral order cancellation ratio, the bilateral order transaction ratio, the bilateral order buy direction ratio, the bilateral order opening ratio, the bilateral order futures ratio, the bilateral order speculation ratio, and the number of concurrent business operation seats are 1, 2, 3...16 in order, wherein the bilateral quotation request ratio is designed by the trader order request ratio, and the dependency relationship under it is also subordinate to the trader order request ratio accordingly. The number of concurrent order seats is a necessary condition for performance testing, and the correlation matrix is ​​established as follows: .

[0073] S4: Collect production data for multiple days, perform preprocessing, obtain the influencing factor values, divide the data into groups based on the fluctuation range of the influencing factors, determine multiple groups of influencing factors, and select the influencing factors in different groups according to the differences in test conditions.

[0074] S41: The original production data for multiple days is shown in Table 9: Table 9: Raw data table of multi-day production data S42: The values ​​converted into impact factors are shown in Table 10: Table 10 Multi-day impact factor value table S43: The impact factor is converted into relative values ​​as shown in Table 11: Table 11 Relative values ​​of impact factors S44: Calculate the standard deviation of each impact factor as shown in Table 12: Table 12 Standard deviation of impact factors S45: Classify the impact factors according to the standard deviation, as shown in Table 13: Table 13 Impact factor classification table S46: Based on past testing experience, the normal order cancellation ratio, normal order transaction ratio, and bilateral order cancellation ratio affect the indicator test results; S47: According to the project characteristics, quality and time requirements, select the factors with large and medium probability of change and those that have an impact on the indicators, such as the ordinary order cancellation ratio, ordinary order transaction ratio, bilateral order cancellation ratio, bilateral order transaction ratio, and bilateral order futures ratio; S48: According to the dependency matrix, obtain the number of seats and the total order rate of the impact factors that are dependent on it; S5: Construct the basic scenario of indicator testing and the scenario of adjusting the influencing factors; analyze the impact of the test results and identification factors on the indicators, which may include the following steps: S51: This project test does not have any expectation on the value of business data. The test results of the PERT three-point analysis method are calculated based on the production data results, and the performance factor values ​​are shown in Table 14: Table 14 Business data value table S52: According to the test steps and constraints of the order peak throughput index in the guide, generate the test scenario as shown in Table 15: Table 15 S53: The transaction ratio of ordinary orders in the basic scenario is 10%, and the maximum and minimum values ​​in the production data are 22% and 7% respectively. The adjusted values ​​calculated according to the formula are 22% and 16%; S54: Analyze the test results. The peak order throughput rate measured in the basic scenario is 100,000 orders / second. When the ordinary order transaction ratio is adjusted to 16%, the calculated peak order throughput rate is 90,000 orders / second. The result deviation is 10%, indicating that the change in the transaction ratio has an impact on the system's peak order throughput rate. S55: The transaction ratio can be further adjusted from 10% to 16% for testing. It is finally found that when the transaction ratio exceeds 13%, it will affect the order peak throughput result. It is necessary to formulate subsequent optimization strategies and record the transaction ratio in the core factor library as a reference for subsequent trading system tests of order peak throughput indicators.

[0075] The embodiment of the present invention is based on various system indicators defined in the specification documents related to the securities and futures industry. The influencing factors of each indicator are extracted through the performance influencing factor analysis method, and an indicator factor library suitable for six types of systems in the securities and futures industry, namely trading, clearing, market conditions, account opening, risk control, and communication, can be established; and a test scenario is constructed in combination with the factors to obtain the performance impact of each influencing factor on the system when it changes, and a more comprehensive analysis of the system performance is performed, so that operation and maintenance personnel can promptly understand the system performance risks caused by business changes and formulate countermeasures in advance.

[0076] The device for processing the performance indicator influencing factor provided by the present invention is described below. The device for processing the performance indicator influencing factor described below and the method for processing the performance indicator influencing factor described above can be referred to each other.

[0077] refer to Figure 8The performance indicator influencing factor processing device provided by the present invention includes a mapping relationship table construction module 801, an input-output and parameter value tree construction module 802, a performance influencing factor tree establishment module 803, an influencing factor grouping module 804 and an influencing factor processing module 805.

[0078] A mapping relationship table construction module 801 is used to construct a mapping relationship table related to performance indicators of the securities and futures industry; An input-output and parameter value tree construction module 802 is used to construct an input-output and parameter value tree corresponding to the performance indicator according to the mapping relationship table; A performance impact factor tree establishment module 803 is used to establish a performance impact factor tree of the performance indicator according to the input and output and parameter value tree; An impact factor grouping module 804 is used to determine multiple groups of impact factors according to the performance impact factor tree; The impact factor processing module 805 is used to select different groups of impact factors for testing according to the test conditions to determine the impact information of the impact factors on the performance indicators.

[0079] The processing device of the performance index influencing factor provided by the embodiment of the present invention constructs a mapping relationship table related to the performance index of the securities and futures industry; constructs the input-output and parameter value tree corresponding to the performance index according to the mapping relationship table; establishes the performance influencing factor tree of the performance index according to the input-output and parameter value tree; determines multiple groups of influencing factors according to the performance influencing factor tree; selects different groups of influencing factors for testing according to the test conditions to determine the influence information of the influencing factors on the performance index. The present invention is based on various system indicators defined in the specification documents related to the securities and futures industry, and extracts the influencing factors of each indicator through the performance influencing factor analysis method, and can establish an indicator factor library suitable for six types of systems in the securities and futures industry, including trading, clearing, market conditions, account opening, risk control, and communication; and constructs a test scenario in combination with the factors to obtain the performance impact of each influencing factor on the system when it changes, and conducts a more comprehensive analysis of the system performance, so that the operation and maintenance personnel can timely understand the system performance risks caused by business changes and formulate countermeasures in advance.

[0080] In one embodiment, the input / output and parameter value tree construction module 802 is used to: Establish a tree-type result indicator analysis tree; the root node of the tree-type result indicator analysis tree is the performance indicator; determine independent inputs and outputs according to the mapping relationship table; use the independent inputs and outputs as the first-level branch nodes of the tree-type result indicator analysis tree, and use the inputs and outputs that depend on the i-th level branch nodes as the i+1-level branch nodes, until all the inputs and outputs are added to the tree-type result indicator analysis tree; the i-th level branch nodes include the first-level branch nodes; the first-level branch nodes are child nodes of the root node; determine the parameters and parameter values ​​of the independent inputs and outputs; add the parameters to the next level branch nodes of the i-th level branch nodes, and add the parameter values ​​to the leaf nodes of the level branch nodes where the corresponding parameters are located, to obtain the input-output and parameter value tree.

[0081] In one embodiment, the performance impact factor tree building module 803 is used to: The elements of the performance indicator to be tested are used as the first-level branch nodes of the performance impact factor tree; the proportions of all independent inputs and outputs in the first-level branch nodes of the input, output and parameter value tree are used as impact factors, added to the elements of the performance indicator to be tested, as the second-level branch nodes of the performance impact factor tree; the ratio of the number of inputs and outputs of the n+1-level branch nodes to the n-level branch nodes is used as an impact factor, added to the n+1-level branch nodes of the performance impact factor tree, so as to establish a performance impact factor tree for the performance indicator; the n-level branch nodes include the second-level branch nodes.

[0082] In one embodiment, the impact factor grouping module 804 is used to: Collect production data of the system; based on the performance impact factor tree, convert the production data into performance factor values; obtain the maximum value of each impact factor from the performance factor values; determine the relative value of each impact factor according to the maximum value of each impact factor; group the impact factors according to the relative value of each impact factor to obtain multiple groups of impact factors.

[0083] In one embodiment, the impact factor processing module 805 is used to: Construct an indicator test basic scenario and an indicator performance factor adjustment scenario; use the indicator test basic scenario to test the influencing factors selected based on the test conditions to obtain a first test result; according to the indicator performance factor adjustment scenario, adjust the influencing factors selected based on the test conditions; use the indicator test basic scenario to test the adjusted influencing factors to obtain a second test result; determine the influence information of the influencing factors on the performance indicator based on the first test result and the second test result.

[0084] In one embodiment, the mapping relationship table construction module 801 is used to: Acquire technical and business documents related to the securities and futures industry; perform structural analysis on the technical and business documents to construct a dictionary table of transaction status, business type, system module and input and output; and construct a mapping relationship table related to the performance indicators based on the dictionary table.

[0085] Fig. 9 An example of a physical structure diagram of an electronic device is shown in FIG. Fig. 9 As shown, the electronic device may include: a processor 910, a communication interface 920, a memory 930 and a communication bus 940, wherein the processor 910, the communication interface 920 and the memory 930 communicate with each other through the communication bus 940. The processor 910 may call the logic instructions in the memory 930 to execute the processing method of the performance index influencing factor, the method comprising: constructing a mapping relationship table related to the performance index of the securities and futures industry; constructing the input and output and parameter value tree corresponding to the performance index according to the mapping relationship table; establishing the performance influencing factor tree of the performance index according to the input and output and parameter value tree; determining multiple groups of influencing factors according to the performance influencing factor tree; selecting different groups of influencing factors for testing according to the test conditions to determine the influence information of the influencing factors on the performance index.

[0086] In addition, the logic instructions in the above-mentioned memory 930 can be implemented in the form of a software functional unit and can be stored in a computer-readable storage medium when it is sold or used as an independent product. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk and other media that can store program codes.

[0087] On the other hand, the present invention also provides a computer program product, which includes a computer program. The computer program can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can execute the processing method of the performance indicator influencing factors provided by the above-mentioned methods, and the method includes: constructing a mapping relationship table related to the performance indicators of the securities and futures industry; based on the mapping relationship table, constructing an input, output and parameter value tree corresponding to the performance indicator; based on the input, output and parameter value tree, establishing a performance influencing factor tree for the performance indicator; based on the performance influencing factor tree, determining multiple groups of influencing factors; and selecting different groups of influencing factors for testing according to test conditions to determine the impact information of the influencing factors on the performance indicators.

[0088] On the other hand, the present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, is implemented to execute a method for processing performance indicator influencing factors provided by the above-mentioned methods, the method comprising: constructing a mapping relationship table related to performance indicators of the securities and futures industry; based on the mapping relationship table, constructing an input, output and parameter value tree corresponding to the performance indicator; based on the input, output and parameter value tree, establishing a performance influencing factor tree for the performance indicator; based on the performance influencing factor tree, determining multiple groups of influencing factors; and selecting different groups of influencing factors for testing according to test conditions to determine the influence information of the influencing factors on the performance indicators.

[0089] The device embodiments described above are merely illustrative, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Ordinary technicians in this field can understand and implement it without paying creative labor.

[0090] Through the description of the above implementation methods, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus a necessary general hardware platform, and of course, can also be implemented by hardware. Based on this understanding, the above technical solution is essentially or the part that contributes to the prior art can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a disk, an optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0091] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for processing performance index influencing factors, characterized in that: include: Construct a mapping relationship table related to the performance indicators of the securities and futures industry; According to the mapping relationship table, construct an input / output and parameter value tree corresponding to the performance indicator; According to the input-output and parameter value tree, a performance influencing factor tree of the performance indicator is established; Determining multiple groups of impact factors according to the performance impact factor tree; Different groups of influencing factors are selected for testing according to the test conditions to determine the influence information of the influencing factors on the performance indicators.

2. The method for processing performance index influencing factors according to claim 1, characterized in that: The step of constructing the input / output and parameter value tree corresponding to the performance indicator according to the mapping relationship table includes: Establishing a tree-type result indicator analysis tree; the root node of the tree-type result indicator analysis tree is the performance indicator; Determine independent input and output according to the mapping relationship table; The independent input and output are used as the first-level branch nodes of the tree-type result indicator analysis tree, and the input and output that depend on the i-th-level branch nodes are used as i+1-level branch nodes, until all the input and output are added to the tree-type result indicator analysis tree; the i-th-level branch nodes include the first-level branch nodes; the first-level branch nodes are child nodes of the root node; Determining parameters and parameter values ​​of the independent input and output; The parameters are added to the next layer of branch nodes of the i-th layer of branch nodes, and the parameter values ​​are added to the leaf nodes of the layer of branch nodes corresponding to the parameters, to obtain the input-output and parameter value tree.

3. The method for processing performance index influencing factors according to claim 1 or 2, characterized in that: The step of establishing a performance influencing factor tree of the performance indicator according to the input / output and parameter value tree comprises: Using the elements of the performance indicator to be tested as the first-level branch nodes of the performance impact factor tree; Taking all independent input-output ratios in the first-layer branch nodes of the input-output and parameter value tree as influencing factors, adding them to the elements of the performance indicator to be tested as the second-layer branch nodes of the performance influencing factor tree; The ratio of the number of inputs and outputs of the n+1th layer branch nodes to the nth layer branch nodes is taken as an influencing factor and added to the n+1th layer branch nodes of the performance influencing factor tree to establish a performance influencing factor tree for the performance indicator; the nth layer branch nodes include the second layer branch nodes.

4. The method for processing performance index influencing factors according to claim 1, characterized in that: Determining multiple groups of impact factors according to the performance impact factor tree includes: Collect production data of the system; Based on the performance impact factor tree, converting the production data into performance factor values; From the performance factor values, obtain the maximum value of each influencing factor; According to the maximum value of each impact factor, determine the relative value of each impact factor; The influencing factors are grouped according to the relative value of each influencing factor to obtain multiple groups of influencing factors.

5. The method for processing performance index influencing factors according to claim 1, characterized in that: The selecting different groups of influencing factors for testing according to the test conditions to determine the influence information of the influencing factors on the performance indicators includes: Construct basic scenarios for indicator testing and scenarios for adjusting indicator performance factors; The indicator test basic scenario is adopted to test the influencing factors selected based on the test conditions to obtain a first test result; According to the indicator performance factor adjustment scenario, adjusting the influencing factors selected based on the test conditions; The index is used to test the basic scenario, and the adjusted influencing factors are tested to obtain a second test result; According to the first test result and the second test result, influence information of the influencing factor on the performance indicator is determined.

6. The method for processing performance index influencing factors according to claim 1, characterized in that: The construction of a mapping relationship table related to the performance indicators of the securities and futures industry includes: Obtain technical and business documents related to the securities and futures industry; Performing structural analysis on the technical and business documents to construct a dictionary table of transaction status, business type, system module and input and output; A mapping relationship table related to the performance indicators is constructed according to the dictionary table.

7. A device for processing performance index influencing factors, characterized in that: include: A mapping relationship table construction module is used to construct a mapping relationship table related to performance indicators of the securities and futures industry; An input-output and parameter value tree construction module, used to construct an input-output and parameter value tree corresponding to the performance indicator according to the mapping relationship table; A performance impact factor tree establishment module, used to establish a performance impact factor tree of the performance indicator according to the input output and parameter value tree; An impact factor grouping module, used to determine multiple groups of impact factors according to the performance impact factor tree; The influencing factor processing module is used to select different groups of influencing factors for testing according to the test conditions to determine the influence information of the influencing factors on the performance indicators.

8. An electronic device comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that: When the processor executes the computer program, the method for processing the performance indicator influencing factor according to any one of claims 1 to 6 is implemented.

9. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method for processing the performance indicator influencing factor according to any one of claims 1 to 6 is implemented.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the method for processing the performance indicator influencing factor according to any one of claims 1 to 6 is implemented.

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