CN113610644B - System transaction screening method and device - Google Patents

System transaction screening method and device Download PDF

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CN113610644B
CN113610644B CN202110936506.3A CN202110936506A CN113610644B CN 113610644 B CN113610644 B CN 113610644B CN 202110936506 A CN202110936506 A CN 202110936506A CN 113610644 B CN113610644 B CN 113610644B
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dimension
performance
index
index dimension
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CN113610644A (en
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李琼宇
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Agricultural Bank of China
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Agricultural Bank of China
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q40/00—Finance; Insurance; Tax strategies; Processing of corporate or income taxes
    • G06Q40/04—Trading; Exchange, e.g. stocks, commodities, derivatives or currency exchange
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q40/00—Finance; Insurance; Tax strategies; Processing of corporate or income taxes
    • G06Q40/02—Banking, e.g. interest calculation or account maintenance

Abstract

The invention discloses a system transaction screening method and a system transaction screening device, which can determine at least one performance index dimension of a system transaction to be processed, respectively obtain test related data of the system transaction to be processed in each performance index dimension, input the test related data of the system transaction to be processed in each performance index dimension into a performance actual measurement compliance calculation model, determine the performance actual measurement compliance output by the performance actual measurement compliance calculation model as target performance actual measurement compliance, judge whether the target performance actual measurement compliance is not less than a preset performance actual measurement compliance threshold, and if so, determine the system transaction to be processed as a performance actual measurement object for performing performance test on an application system to be tested. The invention can effectively screen all transactions of the system to be processed under the condition of reducing human resource consumption, avoids the possible problems caused by manual screening and improves the screening efficiency.

Description

System transaction screening method and device
Technical Field
The present invention relates to the field of data processing technologies, and in particular, to a system transaction screening method and apparatus.
Background
With the increase of computer technology, data processing technology of banking application systems is continuously increasing.
In a banking application system, a system transaction can be a whole operation process of a business or a transaction for the banking application system, including processes of receiving a transaction request, executing a transaction processing process in response to the transaction request, feeding back a processing result to a user, and the like. For example, the system transaction may be an overall operation process of processing the user service query request for the bank application system, including processes of receiving the service query request input by the user, executing the service query process in response to the service query request, feeding back the service query result to the user, and the like.
Currently, technicians can utilize different system transactions to perform performance tests on a bank application system, and determine whether various performance indexes of the bank application system meet requirements so as to optimize a system program. Specifically, when the bank application system performs performance test, an automatic test tool can be used to simulate normal, peak value, abnormal load and other operation scenes, and then corresponding system transactions are processed under different operation scenes so as to test whether various performance indexes of the bank application system reach standards.
Because the number of the system transactions is large, performance test can not be performed on the bank application system by using all the system transactions, so that technicians can manually screen the system transactions according to working experience, screen the system transactions which possibly cause performance bottlenecks of the bank application system, and then perform performance test on the bank application system by using the screened system transactions only, thereby improving performance test efficiency.
However, when the number of system transactions is large and the human resources are limited, the manual screening method cannot effectively screen all the system transactions.
Disclosure of Invention
In view of the above problems, the present invention provides a system transaction screening method and apparatus for overcoming the above problems or at least partially solving the above problems, and the technical solution is as follows:
a system transaction screening method, comprising:
determining at least one performance index dimension of a system transaction to be processed, the performance index dimension comprising: a quantifiable index dimension and a boolean type index dimension, the quantifiable index dimension comprising: a positive correlation quantifiable index dimension and a negative correlation quantifiable index dimension;
respectively obtaining test related data of the transaction of the system to be processed in each performance index dimension;
inputting test related data of the system transaction to be processed in each performance index dimension into a performance actual measurement compliance calculation model, and determining the performance actual measurement compliance output by the performance actual measurement compliance calculation model as target performance actual measurement compliance;
and judging whether the target performance actual measurement compliance is not smaller than a preset performance actual measurement compliance threshold, if so, determining the transaction of the system to be processed as a performance actual measurement object for performing performance test on the application system to be tested.
Optionally, the test related data of the quantifiable indicator dimension includes: dimension weight, actual index value, maximum index limit and minimum index limit; the test related data of the boolean type index dimension includes: importance coefficient and coefficient reference value.
Optionally, the performance measured conformity calculation model includes: a boolean type index dimension deviation calculation sub-model and a conformity calculation sub-model.
Optionally, inputting the test related data of the transaction of the system to be processed in each performance index dimension to a performance actual measurement compliance calculation model, and determining the performance actual measurement compliance output by the performance actual measurement compliance calculation model as a target performance actual measurement compliance, including:
inputting test related data of the system transaction to be processed in each Boolean type index dimension into the Boolean type index dimension deviation calculation sub-model, and determining the Boolean type index dimension deviation output by the Boolean type index dimension deviation calculation sub-model as a target Boolean type index dimension deviation;
inputting the target Boolean type index dimension deviation and the test related data of the system transaction to be processed in each quantifiable index dimension into the coincidence degree calculation sub-model, and determining the performance actual measurement coincidence degree output by the coincidence degree calculation sub-model as the target performance actual measurement coincidence degree.
Optionally, the boolean type index dimension deviation calculation sub-model is:
d is the dimension deviation of the Boolean type index, x is the dimension sequence number of the Boolean type index dimension, A x Is the importance coefficient of the Boolean type index dimension with the sequence number of x, G x Is the coefficient reference value of the Boolean type index dimension with the sequence number x;
wherein, the coincidence degree calculation submodel is:
c is the performance actual measurement conformity, t is the dimension number of the dimension of the positive correlation quantifiable index, W t Is the dimension weight of the dimension of the positive correlation quantifiable index with the sequence number of t, R t Is the actual index value of the dimension of the positive correlation quantifiable index with the sequence number of t, m t Is the positive correlation quantifiable with sequence number tMaximum index limit, n, of index dimension t Is the minimum index limit value of the dimension of the positive correlation quantifiable index with the sequence number of t;
e is the sequence number of the dimension of the negative correlation quantifiable index, V e Is the dimension weight of the dimension of the negative correlation quantifiable index with the sequence number of e, b e Is the maximum index limit value of the negative correlation quantifiable index dimension with the sequence number of e, S e Is the actual index value of the dimension of the negative correlation quantifiable index with the sequence number of e, a e Is the minimum index limit for the negative correlation quantifiable index dimension with sequence number e.
Optionally, the determining at least one performance index dimension of the pending system transaction includes:
Searching at least one performance index dimension corresponding to the system transaction to be processed in a pre-configured performance index dimension table, wherein transaction identifications and performance index dimensions of the system transaction are correspondingly stored in the performance index dimension table.
A system transaction screening device, comprising: a first determination unit, a first obtaining unit, a first input unit, a second determination unit, a first judgment unit, and a third determination unit, wherein:
the first determination unit is configured to perform: determining at least one performance index dimension of a system transaction to be processed, the performance index dimension comprising: a quantifiable index dimension and a boolean type index dimension, the quantifiable index dimension comprising: a positive correlation quantifiable index dimension and a negative correlation quantifiable index dimension;
the first obtaining unit is configured to perform: respectively obtaining test related data of the transaction of the system to be processed in each performance index dimension;
the first input unit is configured to perform: inputting test related data of the system transaction to be processed in each performance index dimension into a performance actual measurement compliance calculation model;
the second determination unit is configured to perform: determining the performance measured coincidence degree output by the performance measured coincidence degree calculation model as a target performance measured coincidence degree;
The first judgment unit is configured to execute: judging whether the target performance actual measurement compliance is not smaller than a preset performance actual measurement compliance threshold, and if so, executing the second determining unit;
the third determination unit is configured to perform: and determining the transaction of the system to be processed as a performance actual measurement object for performing performance test on the application system to be tested.
Optionally, the test related data of the quantifiable indicator dimension includes: dimension weight, actual index value, maximum index limit and minimum index limit; the test related data of the boolean type index dimension includes: importance coefficient and coefficient reference value.
Optionally, the performance measured conformity calculation model includes: a boolean type index dimension deviation calculation sub-model and a conformity calculation sub-model.
Optionally, the first input unit includes: a second input unit and a third input unit, the second determination unit including: a fourth determination unit and a fifth determination unit; wherein:
the second input unit is configured to perform: inputting test related data of the system transaction to be processed in each Boolean type index dimension into the Boolean type index dimension deviation calculation sub-model;
The fourth determination unit is configured to perform: determining the Boolean type index dimension deviation output by the Boolean type index dimension deviation calculation sub-model as a target Boolean type index dimension deviation;
the third input unit is configured to perform: inputting the target Boolean type index dimension deviation and the test related data of the system transaction to be processed in each quantifiable index dimension into the conformity calculation sub-model;
the fifth determination unit is configured to perform: and determining the actually measured performance coincidence degree output by the coincidence degree calculation sub-model as the actually measured performance coincidence degree of the target.
Optionally, the boolean type index dimension deviation calculation sub-model is:
d is the dimension deviation of the Boolean type index, x is the dimension sequence number of the Boolean type index dimension, A x Is the importance coefficient of the Boolean type index dimension with the sequence number of x, G x Is the coefficient reference value of the Boolean type index dimension with the sequence number x;
wherein, the coincidence degree calculation submodel is:
c is the performance actual measurement conformity, t is the dimension number of the dimension of the positive correlation quantifiable index, W t Is the dimension weight of the dimension of the positive correlation quantifiable index with the sequence number of t, R t Is the actual index value of the dimension of the positive correlation quantifiable index with the sequence number of t, m t Is the maximum index limit value of the index dimension of the positive correlation quantifiable index with the sequence number of t, n t Is the minimum index limit value of the dimension of the positive correlation quantifiable index with the sequence number of t;
e is the sequence number of the dimension of the negative correlation quantifiable index, V e Is the dimension weight of the dimension of the negative correlation quantifiable index with the sequence number of e, b e Is the maximum index limit value of the negative correlation quantifiable index dimension with the sequence number of e, S e Is the actual index value of the dimension of the negative correlation quantifiable index with the sequence number of e, a e Is the minimum index limit for the negative correlation quantifiable index dimension with sequence number e.
Optionally, the first determining unit is configured to perform: searching at least one performance index dimension corresponding to the system transaction to be processed in a pre-configured performance index dimension table, wherein transaction identifications and performance index dimensions of the system transaction are correspondingly stored in the performance index dimension table.
The system transaction screening method and device provided by the invention can determine at least one performance index dimension of the system transaction to be processed, wherein the performance index dimension comprises the following steps: a quantifiable index dimension and a boolean type index dimension, the quantifiable index dimension comprising: the method comprises the steps of respectively obtaining test related data of a transaction of a system to be processed in each performance index dimension by positive correlation quantifiable index dimension and negative correlation quantifiable index dimension, inputting the test related data of the transaction of the system to be processed in each performance index dimension into a performance actual measurement compliance calculation model, determining the performance actual measurement compliance output by the performance actual measurement compliance calculation model as target performance actual measurement compliance, judging whether the target performance actual measurement compliance is not smaller than a preset performance actual measurement compliance threshold, and if so, determining the transaction of the system to be processed as a performance actual measurement object for performing performance test on an application system to be tested. The invention can effectively screen all transactions of the system to be processed under the condition of reducing human resource consumption, avoids the possible problems caused by manual screening and improves the screening efficiency.
The foregoing description is only an overview of the present application, and is intended to provide a more clear understanding of the technical means of the present application, as well as to provide a more clear understanding of the above and other objects, features and advantages of the present application, as exemplified by the following detailed description.
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In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings that are required to be used in the embodiments or the description of the prior art will be briefly described below, and it is obvious that the drawings in the following description are only embodiments of the present application, and that other drawings can be obtained according to the provided drawings without inventive effort for a person skilled in the art.
FIG. 1 shows a flowchart of a first system transaction screening method provided by an embodiment of the present application;
FIG. 2 is a flowchart of a second system transaction screening method according to an embodiment of the present application;
fig. 3 is a schematic structural diagram of a first system transaction screening device according to an embodiment of the present application.
Detailed Description
Exemplary embodiments of the present application will be described in more detail below with reference to the accompanying drawings. While exemplary embodiments of the present application are shown in the drawings, it should be understood that the present application may be embodied in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the application to those skilled in the art.
As shown in fig. 1, this embodiment proposes a first system transaction screening method, which may include the following steps:
s101, determining at least one performance index dimension of a system transaction to be processed, wherein the performance index dimension comprises: a quantifiable index dimension and a boolean type index dimension, the quantifiable index dimension comprising: a positive correlation quantifiable index dimension and a negative correlation quantifiable index dimension;
the system transaction to be processed may be a system transaction for determining whether to perform performance test on the application system to be tested.
Alternatively, the application system to be tested may be a certain application system in a bank to be subjected to performance testing. Alternatively, the application system to be tested may be other application systems to be tested for performance, such as an e-commerce application system and a game application system.
It should be noted that, the invention can obtain some test related data of the transaction of the system to be processed in advance, and then can use the test related data of the transaction of the system to be processed to quantitatively calculate the necessary degree of the transaction of the system to be processed for the performance test of the application system to be tested, so as to automatically evaluate the necessity of the transaction of the system to be processed for the performance test of the application system to be tested by using the quantitatively calculated value, namely the quantitative value.
The test related data of the system transaction to be processed may be collected by the application system to be tested in the process of processing the system transaction to be processed (the application system to be tested is used for actually processing the system transaction at this time), or may be obtained from processing data of the system transaction by other application systems of the bank, or may be obtained by means of historical log data of system transaction processing, a data prediction mode, and the like.
Alternatively, the invention may be applied to electronic devices such as mobile phones, tablet computers or desktop computers.
The performance index dimension may be a certain index category of the system transaction, and the index data of the system transaction in the performance index dimension may reflect the processing performance of the application system to be tested on the system transaction to a certain extent. For example, the performance index dimension may be response time of a system transaction, and the response time value of the system transaction may reflect the processing efficiency of the application system to be tested on the system transaction to a certain extent; for another example, the performance index dimension may be a user concurrency number, and the user concurrency number of the system transaction may embody the concurrency processing capability of the application system to be tested on the system transactions initiated by different users to a certain extent.
Wherein the quantifiable index dimension is a performance index dimension that can represent index data using numbers and units. For example, the quantifiable index dimension may be the amount of transactions in a system transaction, where the index data may be 5000 beats/day; for another example, the quantifiable index dimension may be the number of users transacting the system, where the index data may be 100.
The boolean type index dimension is the performance index dimension of which the index data only has two cases of yes and no, for example, the boolean type index dimension can be dynamic account, guest checking or adopting a new technology; for another example, when the boolean type index dimension is dynamic account, the boolean type index dimension has two cases of "dynamic account" and "not dynamic account".
It should be noted that the performance index dimension of the system transaction may also include index dimensions other than the quantifiable index dimension and the boolean type index dimension. For example, there is a certain index dimension with multiple index data evaluation levels such as good, standard and unstandard, such as overall evaluation of the transaction process of the application system processing system to be tested by the user.
The positive correlation quantifiable index dimension is the increase of the number of index data, and can represent that the system performance of the application system to be tested has the quantifiable index dimension with forward change, such as the transaction amount of system transaction, and when the transaction amount of the system transaction is increased, the better the processing performance of the application system to be tested for the system transaction can be represented;
The number of the index data is increased, which can represent that the system performance of the application system to be tested has the inversely-changed quantifiable index dimension, such as the response time of the system transaction, and when the response time of the system transaction is increased, the worse the processing performance of the application system to be tested for the system transaction.
Alternatively, the invention can determine one or more performance index dimensions related to the transaction of the system to be processed through analysis of the expansion dimension of the transaction of the system to be processed.
Optionally, step S101 may include:
searching at least one performance index dimension corresponding to the system transaction to be processed in a pre-configured performance index dimension table, wherein the transaction identifier and the performance index dimension of the system transaction are correspondingly stored in the performance index dimension table.
The transaction identifier of the system transaction can be one or more of the characters of numbers, punctuation marks or Chinese characters, and the invention is not limited to this.
It should be noted that, the invention can record the corresponding performance index dimension of different system exchanges in advance, and record the corresponding relation between each system exchange and the corresponding performance index dimension in the performance index dimension table.
Specifically, the invention can search the transaction of the system to be processed from the performance index dimension table in advance, and then determine each performance index dimension corresponding to the transaction of the system to be processed from the performance index dimension table.
S102, respectively obtaining test related data of the transaction of the system to be processed in each performance index dimension;
wherein, the test related data is index data which is calculated by quantitatively relating to the above-mentioned necessary degree on a certain performance index dimension of the system transaction. For example, when the performance index dimension is the number of user concurrency, the test related data may include actual data of the number of user concurrency, a maximum limit value and a minimum limit value of the number of user concurrency, and the like.
Specifically, the invention can respectively obtain the test related data of the transaction of the system to be processed in the performance index dimension aiming at different performance index dimensions. For example, for the first performance index dimension and the second performance index temperature, the invention can obtain the test related data of the transaction of the system to be processed in the first performance index dimension according to the first performance index dimension, and then obtain the test related data of the transaction of the system to be processed in the second performance index dimension according to the second performance index dimension.
S103, inputting test related data of the system to be processed in each performance index dimension into a performance actual measurement compliance calculation model to obtain the performance actual measurement compliance output by the performance actual measurement compliance calculation model;
the performance measured compliance may be a quantized value of a degree necessary for performing performance testing by using the system transaction for the application system to be tested.
The performance actual measurement compliance calculation model is a model capable of calculating the performance actual measurement compliance of the system transaction based on the test related data of the system transaction in the performance index dimension.
Specifically, the performance actual measurement conformity calculation model can be formulated by a technician according to actual working conditions, and the invention is not limited to this.
Specifically, the invention can input the test related data of the system transaction to be processed in each performance index dimension into the performance actual measurement compliance calculation model, and obtain the performance actual measurement compliance outputted by the performance actual measurement compliance calculation model based on the received test related data.
S104, determining the performance measured coincidence degree output by the performance measured coincidence degree calculation model as a target performance measured coincidence degree;
The target performance measured compliance may be a quantized value of a degree necessary for using the transaction of the system to be processed for performance testing of the application system to be tested.
S105, judging whether the target performance actual measurement conformity is not smaller than a preset performance actual measurement conformity threshold value, and if so, executing the step S106; otherwise, execution of step S106 may be prohibited to reduce resource consumption.
The performance actual measurement conformity threshold may be formulated by a technician according to actual working conditions, which is not limited by the present invention.
Specifically, after the measured compliance of the target performance is determined, the method and the device can compare whether the measured compliance of the target performance is not smaller than the measured compliance threshold of the performance.
If the target performance measured compliance is not less than the performance measured compliance threshold, the invention can determine that the transaction of the system to be processed reaches the necessary degree for the application system to be tested to perform performance test, thereby determining the transaction of the system to be processed as a transaction object for the application system to be tested to perform performance test;
if the target performance measured coincidence degree is smaller than the performance measured coincidence degree threshold, the invention can determine that the transaction of the system to be processed does not reach the necessary degree for the application system to be tested to perform the performance test, thereby prohibiting the determination of the transaction of the system to be processed as the transaction object of the application system to be tested to perform the performance test.
S106, determining the transaction of the system to be processed as a performance actual measurement object for performing performance test on the application system to be tested.
The performance actual measurement object may be a system transaction required for performing performance test on the application system to be tested.
Specifically, when the target performance measured compliance is not less than the performance measured compliance threshold, the invention can determine the transaction of the system to be processed as the performance measured object.
Optionally, the invention can prompt the technician to further analyze the transaction of the system to be processed when the measured coincidence degree of the target performance is not less than the threshold value of the measured coincidence degree of the performance so as to more accurately determine whether the transaction of the system to be processed has the necessity for the application system to be tested to perform the performance test;
optionally, when the measured coincidence degree of the target performance is smaller than the measured coincidence degree threshold value of the performance, the invention can directly determine that the transaction of the system to be processed is not required to be used for performance test of the application system to be tested, and the technician is not required to be notified to further analyze the transaction, so that the consumption of human resources is reduced.
It should be noted that, the invention can quantitatively calculate the necessary degree of the transaction of the system to be processed for the application system to be tested to perform the performance test, and automatically evaluate whether the transaction of the system to be processed is used for the application system to be tested to perform the performance test by utilizing the quantized value obtained by the quantitative calculation, thereby effectively completing the analysis of whether the transaction of the system to be processed is used for the application system to be tested to perform the performance test.
It should be noted that, the invention uses the machine to analyze whether the transaction of the system to be processed is used for the performance test of the application system to be tested, so the invention can effectively screen all the transactions of the system to be processed, namely screen the transaction of the system to be tested for the performance test of the application system to be tested from all the transactions of the system to be processed under the condition of reducing the human resource consumption no matter how many the transactions of the system to be processed are.
The invention also discloses a method for screening the transaction of the system to be processed by using the machine, which can avoid the problems possibly caused by manual screening (such as screening errors caused by artificial subjective experience, and the problems of reduced manual screening accuracy possibly caused by a large number of system transactions, and the like) and improve the screening efficiency.
The system transaction screening method provided in this embodiment may determine at least one performance index dimension of a system transaction to be processed, where the performance index dimension includes: a quantifiable index dimension and a boolean type index dimension, the quantifiable index dimension comprising: the method comprises the steps of respectively obtaining test related data of a transaction of a system to be processed in each performance index dimension by positive correlation quantifiable index dimension and negative correlation quantifiable index dimension, inputting the test related data of the transaction of the system to be processed in each performance index dimension into a performance actual measurement compliance calculation model, determining the performance actual measurement compliance output by the performance actual measurement compliance calculation model as target performance actual measurement compliance, judging whether the target performance actual measurement compliance is not smaller than a preset performance actual measurement compliance threshold, and if so, determining the transaction of the system to be processed as a performance actual measurement object for performing performance test on an application system to be tested. The invention can effectively screen all transactions of the system to be processed under the condition of reducing human resource consumption, avoids the possible problems caused by manual screening and improves the screening efficiency.
Based on the steps shown in fig. 1, this embodiment proposes a second system transaction screening method. In the method, the test-related data of the quantifiable index dimension includes: dimension weight, actual index value, maximum index limit and minimum index limit; the test related data of the boolean type index dimension includes: importance coefficient and coefficient reference value.
The dimension weight is the weight of a quantifiable index dimension, and can represent the duty ratio of the influence degree of the quantifiable index dimension on the performance of the application system to be tested in all the quantifiable index dimensions. Specifically, if the influence of a quantifiable index dimension on the performance of the application system to be tested is greater, the dimension weight of the quantifiable index dimension may be greater; if a quantifiable index dimension has less impact on the performance of the application system under test, the dimension weight of the quantifiable index dimension may be less.
It should be noted that the dimension weight may be set by a technician according to the degree of influence of the quantifiable index dimension on the performance of the application system to be tested, which is not limited in the present invention.
Alternatively, the sum of the dimension weights of the quantifiable index dimensions may be 1. Of course, the sum of the dimension weights of the quantifiable index dimensions may also be other values, such as 2 or 3.
The actual index value may be an index value of a quantifiable index dimension in a process of actually processing a transaction of the system to be processed by the application system. For example, when the quantifiable indicator dimension is the amount of transactions of the system transaction, the actual indicator value may be the number of pending system transactions that the application system actually processes during the day.
The maximum index limit may be the maximum value of the index value of a certain quantifiable index dimension, and the minimum index limit may be the minimum value of the index value of a certain quantifiable index dimension.
It should be noted that, the maximum index limit value and the minimum index limit value may be set by a technician according to the index value of the quantifiable index dimension in the actual working condition of the application system, which is not limited in the present invention. For example, when the quantifiable index dimension is the amount of transactions by the system, the maximum index limit may be set to 10000 beats/day and the minimum index limit may be set to 1 beat/day.
The importance degree coefficient can represent the influence degree of the Boolean type index dimension on the performance of the application system to be tested. When the influence degree of a certain Boolean type index dimension on the performance of an application system to be tested is higher, the importance degree coefficient of the Boolean type index dimension is larger; when the influence degree of a certain Boolean type index dimension on the performance of the application system to be tested is low, the importance degree coefficient of the Boolean type index dimension is smaller.
Wherein the coefficient reference value may be a reference value of the importance coefficient.
Specifically, the importance coefficient of the boolean type index dimension may be set by a technician according to the influence degree of the boolean type index dimension on the performance of the application system to be tested and the coefficient reference value, which is not limited in the present invention.
It should be noted that, the invention can divide the performance index dimension of the transaction of the system to be processed into the positive correlation quantifiable index dimension, the negative correlation quantifiable index dimension and the boolean type index dimension, determine the test related data of the quantifiable index dimension as the dimension weight, the actual index value, the maximum index limit value and the minimum index limit value, and determine the test related data of the boolean type index dimension as the importance coefficient and the coefficient reference value, thereby effectively improving the collection efficiency of the test related data of the transaction of the system to be processed, and effectively realizing the quantitative calculation of the necessary degree of the transaction of the system to be processed for the performance test of the application system to be tested.
The system transaction screening method provided by the embodiment can effectively improve the collection efficiency of test related data of the system transaction to be processed, and effectively realize quantitative calculation of the necessary degree of the system transaction to be processed for performance test of the application system to be tested.
Based on the second system transaction screening method, as shown in fig. 2, the present invention proposes a third system transaction screening method. In a third system transaction screening method, the performance measured compliance calculation model includes: the boolean type index dimension deviation calculation sub-model and the coincidence degree calculation sub-model, steps S103 and S104 may include: s201, S202, S203, S204, S205, and S206.
It should be noted that, the present invention can implement the quantitative calculation of the necessary degree of the transaction of the system to be processed for the performance test of the application system to be tested by executing steps S201, S202, S203, S204, S205 and S206 on the basis of obtaining the boolean type index dimension deviation calculation sub-model and the coincidence degree calculation sub-model. Wherein:
s201, inputting test related data of the system transaction to be processed in each Boolean type index dimension into a Boolean type index dimension deviation calculation sub-model;
the boolean type index dimension deviation calculation sub-model can be set by a technician according to actual working conditions, and the invention is not limited to the setting.
Optionally, the boolean type index dimension deviation calculation sub-model is:
D is the dimension deviation of the Boolean type index, x is the dimension sequence number of the Boolean type index dimension, A x Is the importance coefficient of the Boolean type index dimension with the sequence number of x, G x Is the coefficient reference value of the Boolean type index dimension with the sequence number x;
it should be noted that, the boolean type index dimension deviation calculation sub-model may be the above formula (1) or may be another formula.
S202, obtaining the Boolean type index dimension deviation output by the Boolean type index dimension deviation calculation sub-model;
s203, determining the Boolean type index dimension deviation output by the Boolean type index dimension deviation calculation sub-model as a target Boolean type index dimension deviation;
s204, inputting the target Boolean type index dimension deviation and test related data of the system transaction to be processed in each quantifiable index dimension into a coincidence degree calculation sub-model;
the conformity calculation sub-model may be set by a technician according to actual working conditions, which is not limited in the present invention.
Optionally, the conformity calculation sub-model is formula (2):
c is the performance actual measurement conformity, t is the dimension number of the dimension of the positive correlation quantifiable index, W t Is the dimension weight of the dimension of the positive correlation quantifiable index with the sequence number of t, R t Is the actual index value of the dimension of the positive correlation quantifiable index with the sequence number of t, m t Is the maximum index limit value of the index dimension of the positive correlation quantifiable index with the sequence number of t, n t Is the minimum index limit value of the dimension of the positive correlation quantifiable index with the sequence number of t;
e is the sequence number of the dimension of the negative correlation quantifiable index, V e Is the dimension weight of the dimension of the negative correlation quantifiable index with the sequence number of e, b e Is the maximum index limit value of the negative correlation quantifiable index dimension with the sequence number of e, S e Is the actual index value of the dimension of the negative correlation quantifiable index with the sequence number of e, a e Is the minimum index limit for the negative correlation quantifiable index dimension with sequence number e.
It should be noted that the conformity calculation sub-model may be the above formula (2) or may be another formula.
S205, obtaining the performance actual measurement coincidence degree output by the coincidence degree calculation sub-model;
s206, determining the performance measured coincidence degree output by the coincidence degree calculation sub-model as the target performance measured coincidence degree.
It should be further noted that, by setting and using the boolean type index dimension deviation calculation sub-model and the coincidence degree calculation sub-model, the invention can perform quantization calculation on the necessary degree of the transaction of the system to be processed for performing performance test on the application system to be tested based on the test related data of the transaction of the system to be processed, obtain the corresponding quantization value, effectively realize the quantization calculation on the necessary degree of the transaction of the system to be processed for performing performance test on the application system to be tested, and determine whether to use the transaction of the system to be processed for performing performance test on the application system to be tested by using the quantization value.
According to the system transaction screening method, the Boolean type index dimension deviation calculation sub-model and the coincidence degree calculation sub-model can be set and utilized, the necessary degree of the system transaction to be processed for performing performance test on the application system to be tested can be quantitatively calculated based on the test related data of the system transaction to be processed, the corresponding quantized value is obtained, the necessary degree of the system transaction to be processed for performing performance test on the application system to be tested is effectively calculated, and whether the system transaction to be processed is used for performing performance test on the application system to be tested can be determined by utilizing the quantized value.
Based on the system transaction screening method, the invention provides a fourth system transaction screening method. In the fourth system transaction screening method, after determining the transaction T of the system to be processed, the invention analyzes the expansion dimension of the transaction T of the system to be processed, determines one or more quantifiable index dimensions related to the transaction T of the system to be processed, and classifies each determined quantifiable index dimension to obtain corresponding positive correlation quantifiable index dimensions and negative correlation quantifiable index dimensions.
Specifically, the invention can be created aiming at the dimension of the positive correlation quantifiable index of T Building corresponding dimension set p= (P) 1 ，P 2 ，…，P i ) The quantifiable index dimension for T runs a corresponding set of dimensions N= (N) 1 ，N 2 ，…，N j )；
According to the influence degree of each dimension in P and N on the performance of the application system to be tested, the dimension weights are distributed, and corresponding dimension weight sets W= (W) are respectively established 1 ，W 2 ，…，W i ) Sum v= (V 1 ，V 2 ，…，V j ) Wherein W corresponds one-to-one to the elements in P, e.g. W 1 Is P 1 Dimension weight, W 2 Is P 2 Is a dimension weight of (a); the elements in the set V correspond one-to-one to N, e.g. V 1 Is N 1 Dimension weight of V 2 Is N 2 Is a dimension weight of (a).
The sum of the elements in W and V is 1, namely:
the invention can respectively set the maximum index limit value and the minimum index limit value of each dimension in P, namely, set the index data value range of each dimension to obtain a set R= (R) 1 ，R 2 ，…，R i )，(n 1 ≤R 1 ≤m 1 ，n 2 ≤R 2 ≤m 2 ,……，n i ≤R i ≤m i )，n i And m i Respectively P i A minimum index limit and a maximum index limit of (2); setting a maximum index limit value and a minimum index limit value of each dimension in N, namely setting an index data value range of each dimension to obtain a set S= (S) 1 ，S 2 ，…，S j )，(a 1 ≤S 1 ≤b 1 ，a 2 ≤S 2 ≤b 2 ,……，a j ≤S i ≤b j )。
Specifically, the invention can determine at least one Boolean type index dimension of T aiming at T expansion dimension analysisDegree, create the corresponding dimension set b= (B 1 ，B 2 ，…，B k ) The actual condition of each element in B is assigned to obtain a corresponding set A= (A) 1 ，A 2 ，…，A k ) Wherein the case where the boolean value is "no" is taken as the coefficient reference value 1, and the case where the boolean value is "yes" is set to the importance coefficient of 1.1.
Specifically, the invention can calculate the dimension deviation of the Boolean type index in advance, namely A= (A) 1 ，A 2 ，…，A k ) Substituted into the above formula (1):
at this time, the maximum value of x in the formula may be k, G x May be 1.
The invention can substitute the Boolean type index dimension deviation output in the formula (1) and the test related data of each quantifiable index dimension into the formula (2):
wherein t in the formula (2) may be i as described above, and e in the formula (2) may be j as described above.
In order to better explain the above process, the present embodiment proposes and sets example 1 to explain the above process.
Example 1: after dimension analysis is performed on the system transaction A serving as the system transaction to be processed, the method can determine that the dimension of the positive correlation quantifiable index of the system transaction A comprises the following steps: user concurrency, transaction amount, and throughput (Transactions Per Second, TPS), the negatively-correlated quantifiable indicator dimension may include: the response time, boolean type index dimension may include: accounting and checking guests.
The invention can establish a set P= { user concurrency number, transaction amount, TPS } of positive correlation quantifiable index dimensions of the system transaction A, a set N= { response time }, a set B= { whether account is moved, whether account is checked for guests };
According to the invention, the dimensionality weights of the P and N dimensionalities can be assigned according to the influence degree of the performance of the application system to be tested, and the sum of the dimensionality weights is equal to 1. Specifically, the invention can assign the dimension weight of the user concurrency number to 0.2, the dimension weight of the transaction amount to 0.3, the dimension weight of TPS to 0.25, and the dimension weight of response time to 0.25.
The invention can carry out range value on index data of each element in P and N, and the user concurrency number is not less than 1 and not more than 10000, the daily transaction amount is not less than 1 and not more than 10000, TPS is not less than 1 and not more than 100, and response time is not less than 1 and not more than 10.
The invention can configure the importance coefficient and the coefficient reference value of each element in the B, wherein the coefficient reference value is set to be 1, and the importance coefficient and the coefficient reference value are respectively used for judging whether account is moved: setting 1 when not, and setting 1.1 when yes; for whether to the guest: and if not, setting to 1, and if yes, setting to 1.1.
The invention can firstly substitute the importance coefficient and coefficient reference value of each element in the B into the Boolean type index dimension deviation calculation submodel, and the Boolean type index dimension deviation is as follows:
(1.1+1.1-1-1)＝0.2；
the invention can input the Boolean type index dimension deviation and the test related data of each quantifiable index dimension into the conformity calculation sub-model, and the actual measured conformity of the target performance is:
0.2*[0.2*(100-1)/(10000-1)+0.3*(3000-1)/(10000-1)+0.25*(50-1)/(100-1)+0.25*(10-3)/(10-1)]≈49.4％；
When the performance measured compliance threshold is 60%, the target performance measured compliance is smaller than the performance measured compliance threshold, and the system transaction A does not need to be determined as a performance measured object, namely the system transaction A does not need to be used for performance testing of an application system to be tested.
The system transaction screening method provided by the embodiment provides a specific mode of system transaction screening, and can effectively conduct system transaction screening to complete effective screening of the system transaction to be processed.
Corresponding to the steps shown in fig. 1, as shown in fig. 3, this embodiment proposes a first system transaction screening device, which may include: a first determination unit 101, a first obtaining unit 102, a first input unit 103, a second determination unit 104, a first judgment unit 105, and a third determination unit 106, wherein:
the first determination unit 101 is configured to perform: determining at least one performance index dimension of a system transaction to be processed, wherein the performance index dimension comprises: a quantifiable index dimension and a boolean type index dimension, the quantifiable index dimension comprising: a positive correlation quantifiable index dimension and a negative correlation quantifiable index dimension;
the system transaction to be processed may be a system transaction for determining whether to perform performance test on the application system to be tested.
Alternatively, the application system to be tested may be a certain application system in a bank to be subjected to performance testing. Alternatively, the application system to be tested may be other application systems to be tested for performance, such as an e-commerce application system and a game application system.
It should be noted that, the invention can obtain some test related data of the transaction of the system to be processed in advance, and then can use the test related data of the transaction of the system to be processed to quantitatively calculate the necessary degree of the transaction of the system to be processed for the performance test of the application system to be tested, so as to automatically evaluate the necessity of the transaction of the system to be processed for the performance test of the application system to be tested by using the quantitatively calculated value, namely the quantitative value.
The test related data of the system transaction to be processed may be collected by the application system to be tested in the process of processing the system transaction to be processed (the application system to be tested is used for actually processing the system transaction at this time), or may be obtained from processing data of the system transaction by other application systems of the bank, or may be obtained by means of historical log data of system transaction processing, a data prediction mode, and the like.
Alternatively, the invention may be applied to electronic devices such as mobile phones, tablet computers or desktop computers.
The performance index dimension may be a certain index category of the system transaction, and the index data of the system transaction in the performance index dimension may reflect the processing performance of the application system to be tested on the system transaction to a certain extent.
Wherein the quantifiable index dimension is a performance index dimension that can represent index data using numbers and units.
Wherein, the Boolean type index dimension is the performance index dimension of which the index data only has two cases of yes and no.
It should be noted that the performance index dimension of the system transaction may also include index dimensions other than the quantifiable index dimension and the boolean type index dimension.
The positive correlation quantifiable index dimension is an increase in the number of index data, and can represent that the system performance of the application system to be tested has the quantifiable index dimension of forward variation.
The negative correlation quantifiable index dimension is an increase in the number of index data, and can represent the quantifiable index dimension with inverse variation in the system performance of the application system to be tested.
Alternatively, the invention can determine one or more performance index dimensions related to the transaction of the system to be processed through analysis of the expansion dimension of the transaction of the system to be processed.
Optionally, the first determining unit 101 is configured to perform:
searching at least one performance index dimension corresponding to the system transaction to be processed in a pre-configured performance index dimension table, wherein the transaction identifier and the performance index dimension of the system transaction are correspondingly stored in the performance index dimension table.
The transaction identifier of the system transaction can be one or more of the characters of numbers, punctuation marks or Chinese characters, and the invention is not limited to this.
It should be noted that, the invention can record the corresponding performance index dimension of different system exchanges in advance, and record the corresponding relation between each system exchange and the corresponding performance index dimension in the performance index dimension table.
Specifically, the invention can search the transaction of the system to be processed from the performance index dimension table in advance, and then determine each performance index dimension corresponding to the transaction of the system to be processed from the performance index dimension table.
The first obtaining unit 102 is configured to perform: respectively obtaining test related data of the transaction of the system to be processed in each performance index dimension;
wherein, the test related data is index data which is calculated by quantitatively relating to the above-mentioned necessary degree on a certain performance index dimension of the system transaction.
Specifically, the invention can respectively obtain the test related data of the transaction of the system to be processed in the performance index dimension aiming at different performance index dimensions.
The first input unit 103 is configured to perform: inputting test related data of the system transaction to be processed in each performance index dimension into a performance actual measurement compliance calculation model to obtain the performance actual measurement compliance output by the performance actual measurement compliance calculation model;
the performance measured compliance may be a quantized value of a degree necessary for performing performance testing by using the system transaction for the application system to be tested.
The performance actual measurement compliance calculation model is a model capable of calculating the performance actual measurement compliance of the system transaction based on the test related data of the system transaction in the performance index dimension.
Specifically, the performance actual measurement conformity calculation model can be formulated by a technician according to actual working conditions, and the invention is not limited to this.
Specifically, the invention can input the test related data of the system transaction to be processed in each performance index dimension into the performance actual measurement compliance calculation model, and obtain the performance actual measurement compliance outputted by the performance actual measurement compliance calculation model based on the received test related data.
The second determination unit 104 is configured to perform: determining the performance measured coincidence degree output by the performance measured coincidence degree calculation model as a target performance measured coincidence degree;
the target performance measured compliance may be a quantized value of a degree necessary for using the transaction of the system to be processed for performance testing of the application system to be tested.
The first judging unit 105 is configured to perform: judging whether the target performance measured compliance is not less than a preset performance measured compliance threshold, if so, executing the second determining unit 104; otherwise, triggering of the third determination unit 106 is prohibited to reduce the resource consumption.
The performance actual measurement conformity threshold may be formulated by a technician according to actual working conditions, which is not limited by the present invention.
Specifically, after the measured compliance of the target performance is determined, the method and the device can compare whether the measured compliance of the target performance is not smaller than the measured compliance threshold of the performance.
If the target performance measured compliance is not less than the performance measured compliance threshold, the invention can determine that the transaction of the system to be processed reaches the necessary degree for the application system to be tested to perform performance test, thereby determining the transaction of the system to be processed as a transaction object for the application system to be tested to perform performance test;
If the target performance measured coincidence degree is smaller than the performance measured coincidence degree threshold, the invention can determine that the transaction of the system to be processed does not reach the necessary degree for the application system to be tested to perform the performance test, thereby prohibiting the determination of the transaction of the system to be processed as the transaction object of the application system to be tested to perform the performance test.
The third determination unit 106 is configured to perform: and determining the transaction of the system to be processed as a performance actual measurement object for performing performance test on the application system to be tested.
The performance actual measurement object may be a system transaction required for performing performance test on the application system to be tested.
Specifically, when the target performance measured compliance is not less than the performance measured compliance threshold, the invention can determine the transaction of the system to be processed as the performance measured object.
Optionally, the invention can prompt the technician to further analyze the transaction of the system to be processed when the measured coincidence degree of the target performance is not less than the threshold value of the measured coincidence degree of the performance so as to more accurately determine whether the transaction of the system to be processed has the necessity for the application system to be tested to perform the performance test;
optionally, when the measured coincidence degree of the target performance is smaller than the measured coincidence degree threshold value of the performance, the invention can directly determine that the transaction of the system to be processed is not required to be used for performance test of the application system to be tested, and the technician is not required to be notified to further analyze the transaction, so that the consumption of human resources is reduced.
It should be noted that, the invention can quantitatively calculate the necessary degree of the transaction of the system to be processed for the application system to be tested to perform the performance test, and automatically evaluate whether the transaction of the system to be processed is used for the application system to be tested to perform the performance test by utilizing the quantized value obtained by the quantitative calculation, thereby effectively completing the analysis of whether the transaction of the system to be processed is used for the application system to be tested to perform the performance test.
The system transaction screening device provided by the embodiment can effectively screen all the system transactions to be processed under the condition of reducing human resource consumption, avoids the problem possibly caused by manual screening and improves the screening efficiency.
Based on the illustration in fig. 3, the present embodiment proposes a second system transaction screening device. In the apparatus, the test-related data of the quantifiable index dimension includes: dimension weight, actual index value, maximum index limit and minimum index limit; the test related data of the boolean type index dimension includes: importance coefficient and coefficient reference value.
The dimension weight is the weight of a quantifiable index dimension, and can represent the duty ratio of the influence degree of the quantifiable index dimension on the performance of the application system to be tested in all the quantifiable index dimensions. Specifically, if the influence of a quantifiable index dimension on the performance of the application system to be tested is greater, the dimension weight of the quantifiable index dimension may be greater; if a quantifiable index dimension has less impact on the performance of the application system under test, the dimension weight of the quantifiable index dimension may be less.
It should be noted that the dimension weight may be set by a technician according to the degree of influence of the quantifiable index dimension on the performance of the application system to be tested, which is not limited in the present invention.
Alternatively, the sum of the dimension weights of the quantifiable index dimensions may be 1.
The actual index value may be an index value of a quantifiable index dimension in a process of actually processing a transaction of the system to be processed by the application system.
The maximum index limit may be the maximum value of the index value of a certain quantifiable index dimension, and the minimum index limit may be the minimum value of the index value of a certain quantifiable index dimension.
It should be noted that, the maximum index limit value and the minimum index limit value may be set by a technician according to the index value of the quantifiable index dimension in the actual working condition of the application system, which is not limited in the present invention.
The importance degree coefficient can represent the influence degree of the Boolean type index dimension on the performance of the application system to be tested. When the influence degree of a certain Boolean type index dimension on the performance of an application system to be tested is higher, the importance degree coefficient of the Boolean type index dimension is larger; when the influence degree of a certain Boolean type index dimension on the performance of the application system to be tested is low, the importance degree coefficient of the Boolean type index dimension is smaller.
Wherein the coefficient reference value may be a reference value of the importance coefficient.
Specifically, the importance coefficient of the boolean type index dimension may be set by a technician according to the influence degree of the boolean type index dimension on the performance of the application system to be tested and the coefficient reference value, which is not limited in the present invention.
It should be noted that, the invention can divide the performance index dimension of the transaction of the system to be processed into the positive correlation quantifiable index dimension, the negative correlation quantifiable index dimension and the boolean type index dimension, determine the test related data of the quantifiable index dimension as the dimension weight, the actual index value, the maximum index limit value and the minimum index limit value, and determine the test related data of the boolean type index dimension as the importance coefficient and the coefficient reference value, thereby effectively improving the collection efficiency of the test related data of the transaction of the system to be processed, and effectively realizing the quantitative calculation of the necessary degree of the transaction of the system to be processed for the performance test of the application system to be tested.
The system transaction screening device provided by the embodiment can effectively improve the collection efficiency of test related data of the system transaction to be processed, and effectively realize quantitative calculation of the necessary degree of the system transaction to be processed for performance test of the application system to be tested.
Based on the second system transaction screening device, the invention provides a third system transaction screening device. In a third system transaction screening device, the performance measured compliance calculation model includes: a boolean type index dimension deviation calculation sub-model and a conformity calculation sub-model. The first input unit 103 includes: a second input unit and a third input unit, the second determination unit 104 includes: a fourth determination unit and a fifth determination unit; wherein:
a second input unit configured to perform: inputting test related data of the system transaction to be processed in each Boolean type index dimension into a Boolean type index dimension deviation calculation sub-model;
a fourth determination unit configured to perform: determining the Boolean type index dimension deviation output by the Boolean type index dimension deviation calculation sub-model as a target Boolean type index dimension deviation;
a third input unit configured to perform: inputting the target Boolean type index dimension deviation and test related data of the system transaction to be processed on each quantifiable index dimension into a coincidence degree calculation sub-model;
a fifth determination unit configured to perform: and determining the performance measured coincidence degree output by the coincidence degree calculation sub-model as the target performance measured coincidence degree.
It should be noted that, the present invention can implement the quantitative calculation of the necessary degree of the transaction of the system to be processed for the performance test of the application system to be tested by triggering the second input unit, the third input unit, the fourth determination unit and the fifth determination unit on the basis of obtaining the boolean type index dimension deviation calculation sub-model and the coincidence degree calculation sub-model.
The boolean type index dimension deviation calculation sub-model can be set by a technician according to actual working conditions, and the invention is not limited to the setting.
Optionally, the boolean type index dimension deviation calculation sub-model is:
d is the dimension deviation of the Boolean type index, x is the dimension sequence number of the Boolean type index dimension, A x Is the importance coefficient of the Boolean type index dimension with the sequence number of x, G x Is the coefficient reference value of the Boolean type index dimension with the sequence number x;
it should be noted that, the boolean type index dimension deviation calculation sub-model may be the above formula (1) or may be another formula.
The conformity calculation sub-model may be set by a technician according to actual working conditions, which is not limited in the present invention.
Optionally, the conformity calculation sub-model is formula (2):
C is the performance actual measurement conformity, t is the dimension number of the dimension of the positive correlation quantifiable index, W t Is the dimension weight of the dimension of the positive correlation quantifiable index with the sequence number of t, R t Is the actual index value of the dimension of the positive correlation quantifiable index with the sequence number of t, m t Is the maximum index limit value of the index dimension of the positive correlation quantifiable index with the sequence number of t, n t Is the sequence ofA minimum index limit for the positive correlation quantifiable index dimension with the number t;
e is the sequence number of the dimension of the negative correlation quantifiable index, V e Is the dimension weight of the dimension of the negative correlation quantifiable index with the sequence number of e, b e Is the maximum index limit value of the negative correlation quantifiable index dimension with the sequence number of e, S e Is the actual index value of the dimension of the negative correlation quantifiable index with the sequence number of e, a e Is the minimum index limit for the negative correlation quantifiable index dimension with sequence number e.
It should be noted that the conformity calculation sub-model may be the above formula (2) or may be another formula.
It should be further noted that, by setting and using the boolean type index dimension deviation calculation sub-model and the coincidence degree calculation sub-model, the invention can perform quantization calculation on the necessary degree of the transaction of the system to be processed for performing performance test on the application system to be tested based on the test related data of the transaction of the system to be processed, obtain the corresponding quantization value, effectively realize the quantization calculation on the necessary degree of the transaction of the system to be processed for performing performance test on the application system to be tested, and determine whether to use the transaction of the system to be processed for performing performance test on the application system to be tested by using the quantization value.
According to the system transaction screening device provided by the embodiment, the Boolean type index dimension deviation calculation sub-model and the coincidence degree calculation sub-model can be set and utilized, the necessary degree of the system transaction to be processed for performing performance test on the application system to be tested can be quantitatively calculated based on the test related data of the system transaction to be processed, the corresponding quantized value is obtained, the necessary degree of the system transaction to be processed for performing performance test on the application system to be tested is effectively calculated, and whether the system transaction to be processed is used for performing performance test on the application system to be tested can be determined by utilizing the quantized value.
It should also be noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article or apparatus that comprises an element.
The foregoing is merely exemplary of the present application and is not intended to limit the present application. Various modifications and variations of the present application will be apparent to those skilled in the art. Any modification, equivalent replacement, improvement, etc. which come within the spirit and principles of the application are to be included in the scope of the claims of the present application.

Claims (5)

1. A system transaction screening method, comprising:
determining at least one performance index dimension of a system transaction to be processed, the performance index dimension comprising: a quantifiable index dimension and a boolean type index dimension, the quantifiable index dimension comprising: a positive correlation quantifiable index dimension and a negative correlation quantifiable index dimension;
respectively obtaining test related data of the transaction of the system to be processed in each performance index dimension;
inputting test related data of the system transaction to be processed in each performance index dimension into a performance actual measurement compliance calculation model, and determining the performance actual measurement compliance output by the performance actual measurement compliance calculation model as target performance actual measurement compliance;
judging whether the target performance actual measurement compliance is not smaller than a preset performance actual measurement compliance threshold, if so, determining the transaction of the system to be processed as a performance actual measurement object for performing performance test on the application system to be tested;
Wherein, the performance actual measurement conformity calculation model includes: a Boolean type index dimension deviation calculation sub-model and a coincidence degree calculation sub-model;
the Boolean type index dimension deviation calculation sub-model is as follows:
，
Dfor the boolean type index dimension deviation,xfor the dimension number of the boolean type index dimension,A x is of sequence numberxThe importance coefficient of the boolean type index dimension,G x is of sequence numberxA coefficient reference value for the boolean type index dimension;
wherein, the coincidence degree calculation submodel is:
，
Cfor the measured compliance of the performance,ta dimension number that is the dimension of the positive correlation quantifiable index,W t is of sequence numbertThe positive correlation of quantifiable index dimensions,R t is of sequence numbertThe positive correlation of the quantifiable index dimension,m t is of sequence numbertA maximum index limit for the quantifiable index dimension of the positive correlation,n t is of sequence numbertA minimum index limit for the quantifiable index dimension of the positive correlation;
ea sequence number of a dimension of the quantifiable index for negative correlation,V e is of sequence numbereThe negative correlation of quantifiable index dimensions,b e is of sequence numbereA maximum index limit for the negative correlation quantifiable index dimension,S e is of sequence numbereThe negative correlation of the quantifiable index dimension, a e Is of sequence numbereA minimum index limit for the negative correlation quantifiable index dimension;
correspondingly, inputting the test related data of the system transaction to be processed in each performance index dimension into a performance actual measurement compliance calculation model, and determining the performance actual measurement compliance output by the performance actual measurement compliance calculation model as a target performance actual measurement compliance, wherein the method comprises the following steps:
inputting test related data of the system transaction to be processed in each Boolean type index dimension into the Boolean type index dimension deviation calculation sub-model, and determining the Boolean type index dimension deviation output by the Boolean type index dimension deviation calculation sub-model as a target Boolean type index dimension deviation;
inputting the target Boolean type index dimension deviation and the test related data of the system transaction to be processed in each quantifiable index dimension into the coincidence degree calculation sub-model, and determining the performance actual measurement coincidence degree output by the coincidence degree calculation sub-model as the target performance actual measurement coincidence degree.
2. The method of claim 1, wherein the test-related data of the quantifiable indicator dimension comprises: dimension weight, actual index value, maximum index limit and minimum index limit; the test related data of the boolean type index dimension includes: importance coefficient and coefficient reference value.
3. The method of claim 1, wherein determining at least one performance indicator dimension of a pending system transaction comprises:
searching at least one performance index dimension corresponding to the system transaction to be processed in a pre-configured performance index dimension table, wherein transaction identifications and performance index dimensions of the system transaction are correspondingly stored in the performance index dimension table.
4. A system transaction screening device, comprising: a first determination unit, a first obtaining unit, a first input unit, a second determination unit, a first judgment unit, and a third determination unit, wherein:
the first determination unit is configured to perform: determining at least one performance index dimension of a system transaction to be processed, the performance index dimension comprising: a quantifiable index dimension and a boolean type index dimension, the quantifiable index dimension comprising: a positive correlation quantifiable index dimension and a negative correlation quantifiable index dimension;
the first obtaining unit is configured to perform: respectively obtaining test related data of the transaction of the system to be processed in each performance index dimension;
the first input unit is configured to perform: inputting test related data of the system transaction to be processed in each performance index dimension into a performance actual measurement compliance calculation model;
The second determination unit is configured to perform: determining the performance measured coincidence degree output by the performance measured coincidence degree calculation model as a target performance measured coincidence degree;
the first judgment unit is configured to execute: judging whether the target performance actual measurement compliance is not smaller than a preset performance actual measurement compliance threshold, and if so, executing the second determining unit;
the third determination unit is configured to perform: determining the transaction of the system to be processed as a performance actual measurement object for performing performance test on the application system to be tested;
wherein, the performance actual measurement conformity calculation model includes: a Boolean type index dimension deviation calculation sub-model and a coincidence degree calculation sub-model;
the Boolean type index dimension deviation calculation sub-model is as follows:
，
Dfor the boolean type index dimension deviation,xfor the dimension number of the boolean type index dimension,A x is of sequence numberxThe importance coefficient of the boolean type index dimension,G x is of sequence numberxA coefficient reference value for the boolean type index dimension;
wherein, the coincidence degree calculation submodel is:
，
Cfor the measured compliance of the performance,ta dimension number that is the dimension of the positive correlation quantifiable index, W t Is of sequence numbertThe positive correlation of quantifiable index dimensions,R t is of sequence numbertThe positive correlation of the quantifiable index dimension,m t is of sequence numbertA maximum index limit for the quantifiable index dimension of the positive correlation,n t is of sequence numbertA minimum index limit for the quantifiable index dimension of the positive correlation;
ea sequence number of a dimension of the quantifiable index for negative correlation,V e is of sequence numbereThe negative correlation of quantifiable index dimensions,b e is of sequence numbereA maximum index limit for the negative correlation quantifiable index dimension,S e is of sequence numbereThe negative correlation of the quantifiable index dimension,a e is of sequence numbereMinimum index limit for the negative correlation quantifiable index dimension of (2)
The first input unit includes: a second input unit and a third input unit, the second determination unit including: a fourth determination unit and a fifth determination unit; wherein:
the second input unit is configured to perform: inputting test related data of the system transaction to be processed in each Boolean type index dimension into the Boolean type index dimension deviation calculation sub-model;
the fourth determination unit is configured to perform: determining the Boolean type index dimension deviation output by the Boolean type index dimension deviation calculation sub-model as a target Boolean type index dimension deviation;
The third input unit is configured to perform: inputting the target Boolean type index dimension deviation and the test related data of the system transaction to be processed in each quantifiable index dimension into the conformity calculation sub-model;
the fifth determination unit is configured to perform: and determining the actually measured performance coincidence degree output by the coincidence degree calculation sub-model as the actually measured performance coincidence degree of the target.
5. The apparatus of claim 4, wherein the test-related data of the quantifiable indicator dimension comprises: dimension weight, actual index value, maximum index limit and minimum index limit; the test related data of the boolean type index dimension includes: importance coefficient and coefficient reference value.
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