CN112783799B - Software daemon testing method and device - Google Patents
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Abstract
The invention provides a software daemon testing method and device, which can be used in the financial field or other fields. The method comprises the following steps: receiving application data and determining a service identity corresponding to the application data; acquiring an association rule corresponding to the service identity from a pre-established association rule; and carrying out matching test according to the application data and the corresponding association rule to generate a test result. According to the invention, the association rule formed by the interrelation relation of the application data in the software system is utilized to compare the modified application data, so that the influence of the new function or the modified function on the original software is tested, the service scene on production is more comprehensively covered, the occupied space is small, and the maintenance cost is low.
Description
Technical Field
The invention relates to the technical field of software daemon, in particular to a software daemon testing method and device.
Background
Currently, when a function is newly added and modified to a software system, whether the function has an influence on the original function is evaluated, the evaluation depends on the original daemon and the artificial evaluation. The daemon cases are used for testing cases for guaranteeing the correctness of the existing functions of the system. If the daemon has a missing scene or is manually considered to be bad, a bug may leak out to affect production. Although some companies can automatically generate cases from production data to solve some problems, the method is based on the original daemon test method, the realization is complex, the production data is complex and various, the failure cases need to be manually processed, and the maintenance cost is high.
Disclosure of Invention
Aiming at the problems existing in the prior art, the main purpose of the embodiment of the invention is to provide a software daemon testing method and device, which can realize that the original function of daemon software is not influenced by new function or modified function, and reduce the maintenance cost of software daemon.
In order to achieve the above object, an embodiment of the present invention provides a software daemon testing method, including:
receiving application data and determining a service identity corresponding to the application data;
acquiring an association rule corresponding to the service identity from a pre-established association rule;
and carrying out matching test according to the application data and the corresponding association rule to generate a test result.
Optionally, in an embodiment of the present invention, the association rule is pre-established by the following manner:
receiving a plurality of pieces of history data, and determining service identities corresponding to the pieces of history data;
and extracting the association rule from the history data belonging to the same service identity to obtain the association rule corresponding to each service identity.
Optionally, in an embodiment of the present invention, the receiving a plurality of pieces of history data and determining a service identity corresponding to each piece of history data includes: and receiving a plurality of pieces of historical data, performing data cleaning on the received plurality of pieces of historical data, and determining the service identity corresponding to the historical data after data cleaning.
Optionally, in an embodiment of the present invention, extracting association rules from the history data belonging to the same service identity to obtain association rules corresponding to each service identity includes:
and extracting association rules from each piece of history data belonging to the same service identity one by one, and taking the association rules which are met by each piece of history data as the association rules corresponding to the service identity.
The embodiment of the invention also provides a software daemon testing device, which comprises:
the service identity module is used for receiving the application data and determining the service identity corresponding to the application data;
the rule acquisition module acquires an association rule corresponding to the service identity from a pre-established association rule;
And the rule matching module is used for carrying out matching test according to the application data and the corresponding association rule to generate a test result.
Optionally, in an embodiment of the present invention, the apparatus further includes:
The historical data module is used for receiving a plurality of pieces of historical data and determining service identities corresponding to the pieces of historical data;
And the rule extraction module is used for extracting association rules from the historical data belonging to the same service identity to obtain association rules corresponding to the service identities.
Optionally, in an embodiment of the present invention, the history data module is further configured to receive a plurality of pieces of history data, perform data cleaning on the received plurality of pieces of history data, and determine a service identity corresponding to the history data after the data cleaning.
Optionally, in an embodiment of the present invention, the rule extraction module is further configured to extract association rules of each piece of history data belonging to the same service identity one by one, and use association rules that each piece of history data satisfies as association rules corresponding to the service identity.
The invention also provides an electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the above method when executing the program.
The present invention also provides a computer readable storage medium storing a computer program for executing the above method.
According to the invention, the association rule formed by the interrelation relation of the application data in the software system is utilized to compare the modified application data, so that the influence of the new function or the modified function on the original software is tested, the service scene on production is more comprehensively covered, the occupied space is small, and the maintenance cost is low.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings that are needed in the description of the embodiments will be briefly described below, it being obvious that the drawings in the following description are only some embodiments of the present invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flow chart of a software daemon test method according to an embodiment of the present invention;
FIG. 2 is a flowchart of association rule extraction in an embodiment of the present invention;
FIG. 3 is a schematic diagram of a system architecture of an application daemon test method according to an embodiment of the present invention;
FIG. 4 is a flowchart of association rule extraction in accordance with one embodiment of the present invention;
FIG. 5 is a flow chart of association rule collation in accordance with an embodiment of the present invention;
FIG. 6 is a diagram illustrating association rule extraction according to an embodiment of the present invention;
FIG. 7 is a diagram illustrating rule of deformation equality according to an embodiment of the present invention;
FIG. 8 is a schematic diagram of a software daemon testing device according to an embodiment of the present invention;
FIG. 9 is a schematic diagram of a software daemon testing device according to an embodiment of the present invention;
fig. 10 is a schematic structural diagram of an electronic device according to an embodiment of the invention.
Detailed Description
The embodiment of the invention provides a software daemon testing method and device, which can be used in the financial field or other fields, and the application field of the software daemon testing method and device is not limited.
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Fig. 1 shows a flow chart of a software daemon test method according to an embodiment of the present invention, and an execution body of the software daemon test method according to the embodiment of the present invention includes, but is not limited to, a computer. The method shown in the figure comprises the following steps:
Step S1, receiving application data and determining a service identity corresponding to the application data;
The application data is obtained from the software system, and specifically, the application data can be obtained in a log mode or a section mode. The service identity corresponding to the application data is determined by one or several fields in the application data, specifically, the service identity corresponding to the application data can be determined by recording the number of the service identity in a specific field of the application data in advance.
And S2, acquiring the association rule corresponding to the service identity from the pre-established association rule.
Wherein, different service identities correspond to different association rules, and in particular, one service identity may correspond to one or more association rules. The association rules are pre-established and represent rules that should be satisfied by application data for different service identities. Specifically, the association rules include a perfect equality rule, a deformed equality rule, an association equality rule, and a no association rule. Wherein, the complete equality rule indicates that the data is a transparent field without any change; the deformation equality rule indicates that the data is modified, but has a certain corresponding mapping relation; the association equality rule represents a functional relation f (x) between data.
And step S3, performing a matching test according to the application data and the corresponding association rule, and generating a test result.
And carrying out a matching test according to the association rule corresponding to the application data, and specifically judging whether the application data meets the association rule. Generating a test result, specifically, if the test result is met, indicating that the acquired application data in the software system meets the functional requirement of the original software system, and indicating that the newly added function or the modified function meets the functional requirement of the original software system, wherein the test result is passed; if the association rule is not satisfied, the generated test result is not passed, alarm information is generated, and the alarm information is sent to the corresponding service terminal for processing.
As an embodiment of the present invention, as shown in fig. 2, the association rule is pre-established by:
Step S21, receiving a plurality of pieces of history data and determining service identities corresponding to the pieces of history data.
The historical data, namely the historical application data, is obtained from the software system, and specifically, the historical data can be obtained in a log mode or a section mode. The service identity corresponding to the historical data is determined by one or more fields in the historical data, which are the same as the application data, and specifically, the service identity corresponding to the historical data can be determined by recording the serial number of the service identity in a specific field of the historical data in advance.
Step S22, extracting association rules from the history data belonging to the same service identity to obtain association rules corresponding to the service identities.
The method comprises the steps of extracting association rules of historical data belonging to the same service identity, specifically, calculating the historical data by combining an interface input parameter contained in the historical data, an input parameter called by a database, an input parameter called by an external rpc and the like with a service table in the database, and judging the association rules satisfied by the historical data. Or by an existing association rule extraction algorithm, such as Apriori algorithm.
In this embodiment, receiving a plurality of pieces of history data, and determining a service identity corresponding to each piece of history data includes: and receiving a plurality of pieces of historical data, performing data cleaning on the received plurality of pieces of historical data, and determining the service identity corresponding to the historical data after data cleaning.
The method comprises the steps of receiving historical data, performing data cleaning on the historical data, for example, removing useless information in the historical data, performing data normalization, converting the historical data into structural data, and performing data storage. And after the historical data is cleaned, determining the service identity corresponding to the historical data.
In this embodiment, performing association rule extraction on historical data belonging to the same service identity to obtain association rules corresponding to each service identity includes: and extracting association rules from each piece of history data belonging to the same service identity one by one, and taking the association rules which are met by each piece of history data as the association rules corresponding to the service identity.
The method comprises the steps of extracting association rules from historical data belonging to different service identities, specifically, calculating the historical data by utilizing the fact that the historical data comprise interface input parameters, input parameters called by a database and input parameters called by an external rpc and combining a service table in the database, and judging the association rules met by the historical data. Further, each piece of history data may conform to one or more association rules, and an association rule which is satisfied by all pieces of history data belonging to the service identity is selected as the association rule corresponding to the service identity. Further, a business identity may correspond to one or more association rules.
In an embodiment of the present invention, as shown in fig. 3, a system structure diagram of an application software daemon test method in the embodiment of the present invention is shown, where a specific operation process of the software daemon test system includes association rule extraction (as shown in fig. 4 and shown in fig. 5) and association rule verification (as shown in fig. 5).
The association rule extraction process shown in fig. 4 specifically includes:
1) The software daemon test system comprises a metadata maintenance platform and a functional module with data comparison, black-and-white list and association rule extraction functions. The metadata maintenance platform configures software system metadata, and the metadata comprises association rule information, application information and service identity information. The association rule information represents the name of the association rule, the rule type and other descriptive information, and the application information represents the descriptive information of the application software system. The most important business identity (can be understood as the identity of the minimum set of the test case association rule) in the system is that in a payment business, for example, the business identity has two business identities of the same party and the cross-line transfer, metadata is the account type of the payee, and the association rule is assumed to have three types of a, b and c, wherein a is that the payment amount is equal to the collection amount, b is that the payment amount is equal to the in-transit amount plus the actual payment amount, c is that when the line number of the payee is not null, and the account type of the payee is that of the line. Ab satisfies the same-line transfer, ab is the minimum set of association rules of the same-line transfer, abc satisfies the cross-line transfer, and abc is the minimum set of association rules of the cross-line transfer. A service identity is typically determined by several fields of the entry.
2) ETL storage: the application software system is a system needing to be guarded and comprises a functional module with a plurality of functions and an application data acquisition module. And collecting the data to the data platform through a data channel in a log mode or a section mode. The data mainly collected are interface input parameters, input parameters called by a database and input parameters called by an external rpc (including cache and the like), and the data are called application data and can also be used as historical data in an association rule extraction stage. After receiving the application data, the big data platform performs data cleaning, for example, removes useless information in a log, performs data normalization, converts the application data into structural data, and stores the structural data in the big data platform.
3) And extracting association rules from the collected historical data, and storing the extracted association rules. Specific examples are:
for example, if the metadata is configured as the col2 field of reqIn of the I1 interface, the service identities are classified according to the field, and for simplicity of description, only one service identity is extracted by the rule in this embodiment, which is b1 service, that is, the service identities are: b1 traffic of the I1 interface.
Specifically, the interface I1 receives a piece of data reqIn [ a1, b1], stores it in table Tb1 [ a1, c1], stores it in table Tb2 [ a1, d1], then calls the external interface S1 to enter reqIn into [ a1, d1, f1], returns ReqOut to [ a1, g1], and updates Tb2 to [ a1, g1]. After the whole process is finished, a plurality of sub-association rules (as an example only, there may be other rules) are obtained through first calculation:
I1.req.col1＝Tb1.col1
Tb1.col1＝Tb2.col1
Tb2.col1＝S1.reqIn.col1
S1.reqIn.col1＝S1.ReqOut1.col1
S1.ReqOut1.col1＝Tb2.col1
finally, the association rule R1 is obtained:
I1.req.col1＝Tb1.col1＝Tb2.col1＝S1.reqIn.col1＝S1.ReqOut1.col1＝Tb2.col1。
I2 receives the second piece of data reqIn as [ a2, b1], stores it in table Tb1 as [ a2, c2], stores it in table Tb2 as [ a3, d2], then calls the external interface S1 to enter reqIn as [ a2, d2, f2], returns ReqOut as [ a2, g2], and then updates Tb2 as [ a2, g2]. The sub-association rule is calculated as:
I1.req.col1＝Tb1.col1
S1.reqIn.col1＝S1.ReqOut1.col1
S1.ReqOut1.col1＝Tb2.col1
finally, the association rule R2 is obtained:
Rq.col1=tb1.col1 and R3: s1.reqin.col1=s1.reqit1.col1=tb2.col1.
Meanwhile, the data does not meet the association rule R1, and the data of R1 can be found to meet R2 and R3 through sub-rule matching of R1. Eventually the rules for R2 and R3 are preserved, while the rules for R1 fail.
Through multiple data calculations, the rule that all data satisfy is considered to be a success rule, and can be used for guarding the existing functions of the application system. In this embodiment, the extraction result is that the association rule of R2 and R3 exists under the b1 service of the service identity I1 interface.
The association rule checking process shown in fig. 4 is a daemon test process of the software system, and specifically includes: after the application software system adds or modifies the function, the function development and test for the added or modified function must be performed to verify the function, and when the function is verified, the corresponding application data is extracted to the data platform according to the association rule extraction process shown in fig. 3. The data platform extracts according to the association rule of the business identity related to the received application data, compares the extracted application data with the existing association rule one by one, generates different test results if the extracted application data is inconsistent with the association rule, and reports risks. Further, it may be ultimately decided by a test or developer whether the association rule is allowed to be affected, and if so, the association rule may be removed. Because different services have inconsistent requirements on association rules, a black-and-white list mode is adopted in the mode of removing the association rules, if the rules in the black list are configured, the data comparison is only carried out according to the association rules of the white list if the white list is configured, and if the white list is configured at the same time, the white list format is preferentially adopted.
In a specific embodiment of the present invention, as shown in fig. 6, a schematic diagram of association rule extraction in the embodiment of the present invention is shown, reqIn is an input parameter of an application software system, tb1, tb2 are service tables, reqOut1 is an input parameter requesting an external interface, and rspIn is an output parameter of the interface.
First, the data field relationships are divided into four categories, 1) exactly equal, 2) equal in deformation, 3) equal in association, 4) no association.
1) Completely equal, meaning that the data is a transparent field, and is not changed, such as reqInP, reqInT, reqInT, etc. the data is connected by solid lines in fig. 6. For example, the name of the user entering the parameter is called Zhang San, the field is stored in the database, when the downstream interface is called, the fields recorded in the process are called to be completely equal.
2) The deformation is equal, which means that the data is modified, but has a certain corresponding mapping relation. As in the dashed connection of fig. 6, there may be many-to-one situations. If the transaction type (01) +the transaction stage (02) during participation corresponds to a payment link (03) in the system. Then record 03 when recording the list. This time, the transaction type, the transaction stage and the payment link are of the same shape.
3) The correlations are equal and represent the functional relationship f (x) between the data, such as the curved continuous portion in fig. 6. The relationship equality is a part of the known relationship equality, and the part is a part of manually inputting field relationships between systems by a developer or a tester, such as payment amount + remaining amount = original amount. Or channels 1,500 and above, such as channel quota of 500,500 or less, channel 2. In addition, the system automatically discovers the association relation, and can configure the related association rule algorithm to search the frequent item set of the data so as to set partial association rules. For example, an Apriori algorithm is configured on production for extracting association rules, 1 ten thousand pieces of data are all obtained, three attributes of col1, col2 and col3 exist in each piece of data, after algorithm calculation, col1 appears a 7000 times altogether, col2 appears 3000 times, col2 appears c7000 times, d appears 3000 times, col1 and col2 appear ab combinations 3000 pieces, cd combinations 7000 pieces, and the full strength and ab and cd are strong association rules according to calculation.
4) The remaining other data is temporarily attributed to the unassociated data.
When the data platform is entered, the system classifies all the fields into different field topologies according to the above relation, as shown in fig. 6, and records the following data:
1. perfect equality rule:
reqInP1-reqInT12-reqT21-reqInO11-reqInT21
reqInP3-reqInT14
reqInT23-reqInO12
reqInO12-reqInT24。
2. The rule of equal deformation, the data relationship in the rule of equal deformation is shown in fig. 7.
3. Association rule equal data reqInT = reqInT23+ reqInT.
4. The other data are unassociated data and are not recorded.
After the application software system is modified, the system will notify risk when reqInP and reqInT are not equal in testing the new function record data.
The invention can search the association relation between the data based on the application data from the production and the original daemon, thereby judging whether to influence the original function of the system by judging whether to destroy the association relation between the data when judging the newly added function and the modified function by using the association relation between the data.
According to the invention, the association rule formed by the interrelation relation of the application data in the software system is utilized to compare the modified application data, so that the influence of the new function or the modified function on the original software is tested, the service scene on production is more comprehensively covered, the occupied space is small, and the maintenance cost is low.
Fig. 8 is a schematic structural diagram of a software daemon testing device according to an embodiment of the present invention, where the device includes:
The service identity module 10 is configured to receive application data and determine a service identity corresponding to the application data.
The application data is obtained from the software system, and specifically, the application data can be obtained in a log mode or a section mode. The service identity corresponding to the application data is determined by one or several fields in the application data, specifically, the service identity corresponding to the application data can be determined by recording the number of the service identity in a specific field of the application data in advance.
And the rule acquisition module 20 is configured to acquire an association rule corresponding to the service identity from the pre-established association rules.
Wherein, different service identities correspond to different association rules, and in particular, one service identity may correspond to one or more association rules. The association rules are pre-established and represent rules that should be satisfied by application data for different service identities. Specifically, the association rules include a perfect equality rule, a deformed equality rule, an association equality rule, and a no association rule. Wherein, the complete equality rule indicates that the data is a transparent field without any change; the deformation equality rule indicates that the data is modified, but has a certain corresponding mapping relation; the association equality rule represents a functional relation f (x) between data.
And the rule matching module 30 is used for performing matching test according to the application data and the corresponding association rule to generate a test result.
And carrying out a matching test according to the association rule corresponding to the application data, and specifically judging whether the application data meets the association rule. Generating a test result, specifically, if the test result is met, indicating that the acquired application data in the software system meets the functional requirement of the original software system, and indicating that the newly added function or the modified function meets the functional requirement of the original software system, wherein the test result is passed; if the association rule is not satisfied, the generated test result is not passed, alarm information is generated, and the alarm information is sent to the corresponding service terminal for processing.
As an embodiment of the present invention, as shown in fig. 9, the apparatus further includes:
the historical data module 40 is configured to receive a plurality of pieces of historical data, and determine a service identity corresponding to each piece of historical data.
The historical data, namely the historical application data, is obtained from the software system, and specifically, the historical data can be obtained in a log mode or a section mode. The service identity corresponding to the historical data is determined by one or more fields in the historical data, which are the same as the application data, and specifically, the service identity corresponding to the historical data can be determined by recording the serial number of the service identity in a specific field of the historical data in advance.
The rule extraction module 50 is configured to perform association rule extraction on the historical data belonging to the same service identity, so as to obtain association rules corresponding to each service identity.
The method comprises the steps of extracting association rules of historical data belonging to the same service identity, specifically, calculating the historical data by combining an interface input parameter contained in the historical data, an input parameter called by a database, an input parameter called by an external rpc and the like with a service table in the database, and judging the association rules satisfied by the historical data. Or by an existing association rule extraction algorithm, such as Apriori algorithm.
In this embodiment, the history data module is further configured to receive a plurality of pieces of history data, perform data cleaning on the received plurality of pieces of history data, and determine a service identity corresponding to the history data after the data cleaning.
In this embodiment, the rule extraction module is further configured to extract association rules of each piece of history data belonging to the same service identity one by one, and use the association rule that each piece of history data satisfies as the association rule corresponding to the service identity.
Based on the same application conception as the software daemon testing method, the invention also provides the software daemon testing device. Because the principle of the software daemon testing device for solving the problem is similar to that of a software daemon testing method, the implementation of the software daemon testing device can refer to the implementation of the software daemon testing method, and the repetition is not repeated.
According to the invention, the association rule formed by the interrelation relation of the application data in the software system is utilized to compare the modified application data, so that the influence of the new function or the modified function on the original software is tested, the service scene on production is more comprehensively covered, the occupied space is small, and the maintenance cost is low.
The invention also provides an electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the above method when executing the program.
The present invention also provides a computer readable storage medium storing a computer program for executing the above method.
As shown in fig. 10, the electronic device 600 may further include: a communication module 110, an input unit 120, an audio processing unit 130, a display 160, a power supply 170. It is noted that the electronic device 600 need not include all of the components shown in fig. 10; in addition, the electronic device 600 may further include components not shown in fig. 10, to which reference is made to the related art.
As shown in fig. 10, the central processor 100, sometimes also referred to as a controller or operational control, may include a microprocessor or other processor device and/or logic device, which central processor 100 receives inputs and controls the operation of the various components of the electronic device 600.
The memory 140 may be, for example, one or more of a buffer, a flash memory, a hard drive, a removable media, a volatile memory, a non-volatile memory, or other suitable device. The information about failure may be stored, and a program for executing the information may be stored. And the central processor 100 can execute the program stored in the memory 140 to realize information storage or processing, etc.
The input unit 120 provides an input to the central processor 100. The input unit 120 is, for example, a key or a touch input device. The power supply 170 is used to provide power to the electronic device 600. The display 160 is used for displaying display objects such as images and characters. The display may be, for example, but not limited to, an LCD display.
The memory 140 may be a solid state memory such as Read Only Memory (ROM), random Access Memory (RAM), SIM card, or the like. But also a memory which holds information even when powered down, can be selectively erased and provided with further data, an example of which is sometimes referred to as EPROM or the like. Memory 140 may also be some other type of device. Memory 140 includes a buffer memory 141 (sometimes referred to as a buffer). The memory 140 may include an application/function storage 142, the application/function storage 142 for storing application programs and function programs or a flow for executing operations of the electronic device 600 by the central processor 100.
The memory 140 may also include a data store 143, the data store 143 for storing data, such as contacts, digital data, pictures, sounds, and/or any other data used by the electronic device. The driver storage 144 of the memory 140 may include various drivers of the electronic device for communication functions and/or for performing other functions of the electronic device (e.g., messaging applications, address book applications, etc.).
The communication module 110 is a transmitter/receiver 110 that transmits and receives signals via an antenna 111. A communication module (transmitter/receiver) 110 is coupled to the central processor 100 to provide an input signal and receive an output signal, which may be the same as in the case of a conventional mobile communication terminal.
Based on different communication technologies, a plurality of communication modules 110, such as a cellular network module, a bluetooth module, and/or a wireless local area network module, etc., may be provided in the same electronic device. The communication module (transmitter/receiver) 110 is also coupled to a speaker 131 and a microphone 132 via an audio processor 130 to provide audio output via the speaker 131 and to receive audio input from the microphone 132 to implement usual telecommunication functions. The audio processor 130 may include any suitable buffers, decoders, amplifiers and so forth. In addition, the audio processor 130 is also coupled to the central processor 100 so that sound can be recorded locally through the microphone 132 and so that sound stored locally can be played through the speaker 131.
It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
The principles and embodiments of the present invention have been described in detail with reference to specific examples, which are provided to facilitate understanding of the method and core ideas of the present invention; meanwhile, as those skilled in the art will have variations in the specific embodiments and application scope in accordance with the ideas of the present invention, the present description should not be construed as limiting the present invention in view of the above.
Claims (8)
1. A software daemon testing method, the method comprising:
receiving application data and determining a service identity corresponding to the application data; wherein, the business identity corresponding to the application data is determined according to one or more fields of the application data for recording business identity numbers;
Acquiring an association rule corresponding to the service identity from a pre-established association rule; wherein the association rules comprise a complete equality rule, a deformation equality rule, an association equality rule and a no association rule; the data is represented by the complete equality rule as a transparent field, the deformed equality rule represents that the data is modified but has a certain corresponding mapping relation, and the associated equality rule represents a functional relation among the data;
performing a matching test according to the application data and the corresponding association rule to generate a test result;
Wherein, the association rule is pre-established by the following method:
receiving a plurality of pieces of history data, and determining service identities corresponding to the pieces of history data;
and extracting the association rule from the history data belonging to the same service identity to obtain the association rule corresponding to each service identity.
2. The method of claim 1, wherein receiving the plurality of pieces of history data and determining the service identity corresponding to each piece of history data comprises: and receiving a plurality of pieces of historical data, performing data cleaning on the received plurality of pieces of historical data, and determining the service identity corresponding to the historical data after data cleaning.
3. The method of claim 1, wherein the extracting association rules of the history data belonging to the same service identity to obtain association rules corresponding to each service identity comprises:
and extracting association rules from each piece of history data belonging to the same service identity one by one, and taking the association rules which are met by each piece of history data as the association rules corresponding to the service identity.
4. A software daemon testing apparatus, the apparatus comprising:
The service identity module is used for receiving the application data and determining the service identity corresponding to the application data; wherein, the business identity corresponding to the application data is determined according to one or more fields of the application data for recording business identity numbers;
The rule acquisition module is used for acquiring the association rule corresponding to the service identity from the pre-established association rule; wherein the association rules comprise a complete equality rule, a deformation equality rule, an association equality rule and a no association rule; the data is represented by the complete equality rule as a transparent field, the deformed equality rule represents that the data is modified but has a certain corresponding mapping relation, and the associated equality rule represents a functional relation among the data;
the rule matching module is used for carrying out matching test according to the application data and the corresponding association rule to generate a test result;
Wherein the apparatus further comprises:
The historical data module is used for receiving a plurality of pieces of historical data and determining service identities corresponding to the pieces of historical data;
And the rule extraction module is used for extracting association rules from the historical data belonging to the same service identity to obtain association rules corresponding to the service identities.
5. The apparatus of claim 4, wherein the history data module is further configured to receive a plurality of pieces of history data, perform data cleansing on the received plurality of pieces of history data, and determine a service identity corresponding to the data-cleansed history data.
6. The apparatus of claim 4, wherein the rule extraction module is further configured to extract association rules from each piece of history data belonging to the same service identity one by one, and use association rules that each piece of history data satisfies as association rules corresponding to the service identity.
7. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the processor implements the method of any one of claims 1 to 3 when executing the computer program.
8. A computer readable storage medium, characterized in that the computer readable storage medium stores a computer program for executing the method of any one of claims 1 to 3 by a computer.
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