CN112463625A - Functional regression verification method and device based on application program interface and storage medium - Google Patents
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Abstract
The invention relates to a functional regression verification method, a device and a storage medium based on an application program interface, which comprises the following steps: s1: automatically intercepting interface request data to a specified directory file for test data collection; s2: cleaning and sampling the test data according to a strategy; s3: performing automatic playback test in the test environment before and after upgrading; s4: the interface response bodies returned by the two sets of test environment paths are compared and checked to judge whether the function regression verification passes; s5: recording the result, and if the regression verification fails, carrying out failure retry treatment; the function regression verification time is effectively shortened, the verification speed is high, and the verification cost is far lower than that of developing an automatic test script.
Description
Technical Field
The invention belongs to the technical field of regression testing, and particularly relates to a functional regression verification method and device based on an application program interface and a storage medium.
Background
With continuous development and iteration of software products, the underlying basic resources on which the software products depend also need to be continuously upgraded to ensure that the functions of the software products can stably run on the new basic resources, such as common upgrading of operating systems, dependent third-party JAR packages, third-party libraries of python, and the like. For upgrading of basic resources, in order to ensure stable availability of functions, it is necessary to perform complete regression verification on functions provided by upper-layer software products.
The software product provides huge and complex functions, and when regression verification is carried out, if each function point of the software product needs to be verified manually, a large amount of testing time is consumed, the progress of a team is slowed, and the development speed of new functions of the product is influenced; the other method is to develop an automatic test script of the software product, but the development of the automatic test script needs to invest a large amount of labor and material cost, and moreover, whether the development of the automatic test script is successful or not has great uncertainty; therefore, a software product function regression verification method and device with high verification speed and low cost are lacked at present. This is a disadvantage of the prior art.
In view of the above-mentioned drawbacks in the prior art, it is necessary to provide a functional regression verification method, device and storage medium based on application program interface to solve the problems in the prior art.
Disclosure of Invention
Aiming at the problems that the function regression test of the software product at the upper layer is long in time consumption, high in cost consumption and lack of a complete and rapid regression verification method and device when the basic component at the bottom layer is upgraded, the invention provides the function regression verification method, the function regression verification device and the storage medium based on the application program interface, so that the technical problems are solved, the function regression verification time of the software product is shortened, and the test efficiency of the software product which needs to comprehensively verify the function due to the upgrade of the basic environment is improved.
In order to achieve the purpose, the invention provides the following technical scheme:
in a first aspect, the present invention provides a functional regression verification method based on an application program interface, including the following steps:
s1: automatically intercepting interface request data to a specified directory file for test data collection;
s2: cleaning and sampling the test data according to a strategy;
s3: performing automatic playback test in the test environment before and after upgrading;
s4: the interface response bodies returned by the two sets of test environment paths are compared and checked to judge whether the function regression verification passes;
s5: and recording the result, and if the regression verification fails, performing failure retry processing.
Preferably, the interface request data interception in step S1 has two ways:
the software product with the gateway recording interface request log directly intercepts the log from an interface request log recording file by setting a log time period;
a software product without a gateway recording interface request log needs to be provided with an agent, a fixed packet capturing service running in the agent monitors interface request data on the software product, and the request data is captured and intercepted when the request on the software product is monitored;
collecting all interface request data following RestApi in both ways provides greater versatility.
Preferably, the cleaning process in step S2 is as follows:
the first step is to grade the test data and load the request data of different browser clients into different data lists;
secondly, presetting keywords of an application program interface module to be regressed and verified, and cleaning and filtering the request data in the data list through keyword matching;
thirdly, carrying out duplicate removal, scene collection and data format assembly on the cleaned data;
the interference of non-test request data on result statistics is reduced by cleaning the data.
Preferably, the step S2 performs sampling by using the policy api + request _ body + response _ code:
acquiring api, header, request _ body and response _ code for each interface data cycle, wherein if key values in the request _ body are different, the interfaces are considered to be different scenes, and response _ code returned by each interface execution is inconsistent, and the interfaces are also considered to be different scenes;
setting the maximum sampling limit times limit of an application program interface, directly discarding data when a sampling scene exceeds the limit of the limit, and otherwise, loading the data into playback data; the maximum sampling limit times limit of the application program interface is set to prevent excessive test scenes from being introduced in the initial stage, and the problem troubleshooting cost is reduced when the regression check fails.
Repeated data in the test request data are reduced through sampling, meanwhile, the diversity of the sampled data is guaranteed, and comprehensive guarantee is provided for subsequent playback request tests.
Preferably, in the step S2, the cleaned and sampled data is stored as a basic test scenario library; the subsequent test scene test can directly acquire the data for the playback test, so that the reusability of the test scene data is improved.
Preferably, the step S3 includes the following steps:
s3.1: driving postman to perform filling of playback data content;
s3.2: calling a postman interface and simultaneously sending requests to the test environment before and after upgrading;
s3.3: acquiring a response body of the postman sending interface in the two sets of test environments;
and retransmitting the interface request data in the test environments before and after upgrading through a postman interface tool, and acquiring the follow-up comparative analysis of the response bodies in the two sets of test environments.
Preferably, the comparison checking process in step S4 is as follows:
s4.1: comparing the response bodies of the two sets of test environments according to a recursive comparison mode, and comparing the key-value of each element in the return value;
s4.2: if the recursive comparison results are the same, the regression verification is considered to be passed, and if the recursive comparison results are not the same, the next filtering comparison is carried out;
s4.3: setting a dictionary storage interface name, a verification mode and an ignored field in a self-defined manner, and filtering and comparing response bodies of the two sets of test environments;
s4.4: if the filtering comparison results are the same, the regression verification is considered to be successful, and if the filtering comparison results are different, the regression verification is not passed;
the comparison is carried out according to a conventional recursion mode, the comparison of the filtering modes is carried out when the recursion mode fails, the influence of the system on the comparative analysis of the test result due to random attributes is reduced as much as possible, the success rate of the comparison of the test result is improved, in addition, the proportion of the interface which passes through the recursion comparison and the filtering comparison can be counted, and the subsequent test strategy is adjusted in real time according to the proportion.
In a second aspect, the present invention provides an apparatus for functional regression verification based on application program interface, including:
an API collection module: intercepting the interface request data to a specified directory file for test data collection; the test data can be collected by capturing log records, or the fixed packet capturing service can be started in the agent, and the software product is monitored in real time to collect the test data;
API intelligent analysis module: cleaning and sampling the test data according to a strategy;
a playback module: connecting the test environments before and after upgrading, and simultaneously performing automatic retransmission test on the test data of the application program interface in the two environments to obtain a response body returned by the interface;
a response analysis module: comparing and analyzing the interface response bodies returned by the two sets of test environment paths, and judging whether the function verification passes;
the test result generating and publishing module: and collecting the test result, calling back the data to the playback module under the limitation of the maximum number of times of re-running, executing the requested playback action again, generating a test report and issuing the test report.
Preferably, the response analysis module includes:
a conventional comparison unit: comparing interface response bodies of the two sets of test environments according to a recursive comparison mode, and comparing key-value of each element in a return value;
a filtering comparison unit: setting a dictionary storage interface name, a verification mode and an ignored field in a self-defined manner, and filtering and comparing response bodies of the two sets of test environments;
the two interface response bodies firstly enter the conventional comparison unit, are compared in a recursion mode, and then enter the filtering comparison unit when the recursion mode fails, so that the influence of the system on the comparative analysis of the test result due to random attributes is reduced as much as possible, the success rate of the comparison of the test result is improved, in addition, the proportion of the interface passing through the conventional comparison unit and the filtering comparison unit can be counted, and the subsequent test strategy is adjusted in real time according to the proportion.
In a third aspect, the present invention provides a computer storage medium having stored therein instructions that, when run on a computer, cause the computer to perform the above-described method.
In a fourth aspect, a terminal is provided, including:
a processor, a memory, wherein the memory is used for storing a computer program, and the processor is used for calling and running the computer program from the memory, so that the terminal executes the method.
The method has the advantages that the interface request data of the system used by the daily user is automatically monitored and intercepted, so that the omission of a test scene caused by manual test execution is effectively avoided, and the collection efficiency of the test data is improved; cleaning and sampling the collected test data, wherein the cleaned and sampled data can be used as a basic scene library for subsequent upgrading regression verification, and the test data has high reusability; the playback test is carried out in the test environment before and after the upgrade to obtain the interface response body, the response bodies of the two sets of test environments are compared and analyzed to obtain a conclusion, the function regression verification time is effectively shortened, the verification speed is high, and the verification cost is far lower than that of the development of an automatic test script. In addition, the invention has reliable design principle, simple structure and very wide application prospect.
Therefore, compared with the prior art, the invention has prominent substantive features and remarkable progress, and the beneficial effects of the implementation are also obvious.
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In order to more clearly illustrate the embodiments or technical solutions in the prior art of the present invention, the drawings used in the description of the embodiments or prior art will be briefly described below, and it is obvious for those skilled in the art that other drawings can be obtained based on these drawings without creative efforts.
Fig. 1 is a flowchart of a functional regression verification method based on an application program interface according to embodiment 1 of the present invention.
Fig. 2 is a flowchart of the sampling process in embodiment 1.
FIG. 3 is a flow chart of comparative examination of response1 and response2 in example 1.
Fig. 4 is a schematic block diagram of a functional regression analysis apparatus based on an application program interface according to embodiment 2 of the present invention.
The system comprises a 1-API collecting module, a 2-API intelligent analysis module, a 3-playback module, a 4-response analysis module, a 4.1-conventional comparison unit, a 4.2-filtering comparison unit, a 5-test result generating and issuing module, a 6-Centos7.2 test environment and a 7-Centos8.2 test environment.
Detailed Description
The present invention will be described in detail below with reference to the accompanying drawings by way of specific examples, which are illustrative of the present invention and are not limited to the following embodiments.
The following explains key terms appearing in the present invention:
an API (Application Programming Interface) is a set of definitions, programs, and protocols, and implements communication between computer software through the API. One of the main functions of the api is to provide a common set of functions, and the api is also a middleware to provide data sharing for various platforms.
Example 1:
as shown in fig. 1 to 3, the present embodiment provides a functional regression verification method based on an application program interface, including the following steps:
firstly, preparing a test environment of a tested product, selecting a Centos7.2 test environment before upgrading on the basis of an OpenStack management platform, stably running for a period of time, selecting a Centos8.2 test environment after upgrading, and ensuring that the OpenStack management platforms on the Centos8.2 and the Centos7.2 are normal in function.
S1: automatically intercepting interface request data to an appointed directory file for test data collection by taking a test environment of Centos7.2 as a reference;
the OpenStack management platform records all requested request information into a log file through a gateway, can directly set a log time period 2020-10-1310: 00-2020-10-1312:00, and intercepts all interface request data in the time period range to a specified directory file.
The agent can also be set, the stub bale plucking service running in the agent monitors the interface request data on the software product, when the request on the software product is monitored, the request data is captured and intercepted, and the intercepted data is stored under the appointed directory file.
S2: cleaning and sampling the test data according to a strategy;
the cleaning process of the test data is as follows:
firstly, grading test data, loading request data of different browser clients into different data lists, and classifying the request data according to the difference of cookies and jessionids in request _ headers;
then presetting the keywords of the API module to be regressed and verified, and cleaning and filtering the request data in the data list through keyword matching;
finally, carrying out duplicate removal, scene collection and data format assembly on the cleaned data;
the interference of non-test request data on result statistics is reduced by cleaning the data.
After the cleaning treatment is finished, sampling by adopting a strategy of api + request _ body + response _ code:
acquiring api, header, request _ body and response _ code for each interface data cycle, wherein if key values in the request _ body are different, the interfaces are considered to be different scenes, and response _ code returned by each interface execution is inconsistent, and the interfaces are also considered to be different scenes;
setting the maximum sampling limit times limit of an application program interface, directly discarding data when a sampling scene exceeds the limit of the limit, and otherwise, loading the data into playback data; the maximum sampling limit times limit of the application program interface is set to prevent excessive test scenes from being introduced in the initial stage, and the problem troubleshooting cost is reduced when the regression check fails.
Repeated data in the test request data are reduced through sampling, meanwhile, the diversity of the sampled data is guaranteed, and comprehensive guarantee is provided for subsequent playback request tests.
Storing the cleaned and sampled data as a basic test scene library; the subsequent test scene test can directly acquire the data for the playback test, so that the reusability of the test scene data is improved.
S3: the automatic playback test is carried out under the test environment of Centos7.2 and Centos8.2, and the specific steps are as follows:
s3.1: driving postman to fill playback data content, wherein each request data in the data list is in a dictionary format, and filling request _ url, request _ method, request _ header and request _ body in sequence according to the dictionary sequence, wherein the specific data structure format is as follows:
{ "request _ url": http:// ip: port/list { "request _ url" -, url of request:// ip:// port/list {
Request _ method: "get", method of request
"request _ header": "dit", request header, dictionary format, mainly X-auth-token, accept-content, etc
Request _ body: "dit", the body of the request
}
S3.2: calling a postman interface to simultaneously send requests to the test environments of Centos7.2 and Centos 8.2;
s3.3: acquiring response bodies response1 and response2 of the postman sending interface in two sets of test environments;
interface request data is retransmitted in the test environments of Centos7.2 and Centos8.2 through a postman interface tool, and response bodies in the two sets of test environments are obtained to be subsequently compared and analyzed.
S4: the interface response bodies response1 and response2 returned by the two sets of test environment paths are compared and checked to judge whether the functional regression verification passes, and the specific steps are as follows:
s4.1: comparing the response bodies of the two sets of test environments according to a recursive comparison mode, and comparing the key-value of each element in the return value;
s4.2: if the recursive comparison results are the same, the regression verification is considered to be passed, and if the recursive comparison results are not the same, the next filtering comparison is carried out;
s4.3: the dictionary storage interface name, the verification mode and the ignored field are set by self-definition, the response bodies of the two sets of test environments are filtered and compared, and the dictionary object format set by self-definition is as follows:
Ignore_dict＝{
“URL_1”:“response>create_time,id”
“URL_2”:“schema”
“URL_3”:“list_sort”
}
when the response keyword is set, the complete matching check is represented, fields smaller than the number are filtered, and the plurality of fields are divided by commas; when the schema key word is set, only the types of the key value and the key-value are checked, and the correctness of specific value information is not checked; when the list _ sort is set, only the existence of the data is judged, and the position information of the data in the list is not checked.
S4.4: if the filtering comparison results are the same, the regression verification is considered to be successful, and if the filtering comparison results are different, the regression verification is not passed;
the comparison is carried out according to a conventional recursion mode, the comparison of the filtering modes is carried out when the recursion mode fails, the influence of the system on the comparative analysis of the test result due to random attributes is reduced as much as possible, the success rate of the comparison of the test result is improved, in addition, the proportion of the interface which passes through the recursion comparison and the filtering comparison can be counted, and the subsequent test strategy is adjusted in real time according to the proportion.
S5: and recording the result, if the regression verification fails, performing failure retry processing, and performing automatic playback test under the test environment of Centos7.2 and Centos8.2 again under the configured failure rerun number limit, wherein the verification fails if the failure number exceeds the rerun number limit.
Example 2:
as shown in fig. 4, the present embodiment provides a functional regression verification apparatus based on application program interface, which includes an API collection module 1, an API intelligent analysis module 2, a playback module 3, a response analysis module 4, and a test result generation and release module 5.
Based on an OpenStack management platform, a Centos7.2 test environment 6 is selected as a test environment before upgrading and stably operates for a period of time, a Centos8.2 test environment 7 is selected as a test environment after upgrading, and the OpenStack management platform of the Centos8.2 test environment 7 and the Centos7.2 test environment 6 needs to be ensured to be normal in function.
API collection module 1: intercepting interface request data to a specified directory file for test data collection by taking a Centos7.2 test environment 6 as a reference; the test data can be collected by capturing log records, or the fixed packet capturing service can be started in the agent, and the software product is monitored in real time to collect the test data;
API intelligent analysis module 2: cleaning and sampling the test data according to a strategy;
the playback module 3: connecting a Centos7.2 test environment 6 and a Centos8.2 test environment 7, and simultaneously performing automatic retransmission test on test data of an application program interface in the two environments to obtain a response body returned by the interface;
the response analysis module 4: comparing and analyzing response bodies response1 and response2 of the interfaces returned by the two sets of test environment paths, and judging whether the functional verification passes;
the test result generating and issuing module 5: and collecting the test result, calling back the data to a playback module under the limitation of the maximum number of times of rerun, executing the requested playback action again, generating a test report in an html format and issuing the test result through the mailbox address.
In this embodiment, the response analysis module 4 includes:
conventional comparison unit 4.1: comparing interface response bodies of the two sets of test environments according to a recursive comparison mode, and comparing key-value of each element in a return value;
filtration and comparison unit 4.2: setting a dictionary storage interface name, a verification mode and an ignored field in a self-defined manner, and filtering and comparing response bodies of the two sets of test environments;
the interface response bodies of the two sets of test environments firstly enter the conventional comparison unit 4.1, the recursive mode is adopted for comparison, and the filtering comparison unit 4.2 is adopted when the recursive mode fails, so that the influence of the system on the comparison and analysis of the test results due to random attributes is reduced as much as possible, the success rate of comparison of the test results is improved, in addition, the proportion of the interface passing through the conventional comparison unit 4.1 and the filtering comparison unit 4.2 can be counted, and the subsequent test strategies can be adjusted in real time according to the proportion.
Example 3:
the present embodiments provide a computer storage medium having stored therein instructions that, when run on a computer, cause the computer to perform the above-described method.
Example 4:
the present embodiment provides a terminal, including:
a processor, a memory, wherein the memory is used for storing a computer program, and the processor is used for calling and running the computer program from the memory, so that the terminal executes the method.
The above disclosure is only for the preferred embodiments of the present invention, but the present invention is not limited thereto, and any non-inventive changes that can be made by those skilled in the art and several modifications and amendments made without departing from the principle of the present invention shall fall within the protection scope of the present invention.
Claims (10)
1. A functional regression verification method based on an application program interface is characterized by comprising the following steps:
s1: intercepting the interface request data to a specified directory file for test data collection;
s2: cleaning and sampling the test data according to a strategy;
s3: performing automatic playback test in the test environment before and after upgrading;
s4: the interface response bodies returned by the two sets of test environment paths are compared and checked to judge whether the function regression verification passes;
s5: and recording the result, and if the regression verification fails, performing failure retry processing.
2. The method for functional regression verification based on application program interface as claimed in claim 1, wherein the interface request data interception in step S1 has two modes:
the software product with the gateway recording interface request log directly intercepts the log from an interface request log recording file by setting a log time period;
the software product without the gateway recording interface request log needs to set an agent, a fixed packet capturing service running in the agent monitors the interface request data on the software product, and captures and intercepts the request data when the request on the software product is monitored.
3. The method for functional regression based on application program interface of claim 2, wherein the cleaning process in step S2 is as follows:
the first step is to grade the test data and load the request data of different browser clients into different data lists;
presetting API module keywords to be regressed and verified, and cleaning and filtering the request data in the data list through keyword matching;
and thirdly, carrying out duplicate removal, scene collection and data format assembly on the cleaned data.
4. The method for functional regression verification based on application program interface of claim 3, wherein the api + request _ body + response _ code sampling policy is selected when the test data is sampled in step S2:
acquiring api, header, request _ body and response _ code for each interface data cycle, wherein if key values in the request _ body are different, the interfaces are considered to be different scenes, and response _ code returned by each interface execution is inconsistent, and the interfaces are also considered to be different scenes;
and secondly, setting the maximum sampling limit times limit of the application program interface, directly discarding the data when the sampling scene exceeds the limit of the limit, and otherwise, loading the data into the playback data.
5. The method for functional regression verification based on application program interface of claim 4, wherein the cleaned and sampled data is stored as a base test scenario library in step S2.
6. The method for functional regression based on application program interface of claim 5, wherein the step S3 comprises the following steps:
s3.1: driving postman to perform filling of playback data content;
s3.2: calling a postman interface and simultaneously sending requests to the test environment before and after upgrading;
s3.3: and acquiring a response body of the postman sending interface in two sets of test environments.
7. The method for functional regression verification based on application program interface of claim 6, wherein the comparison checking process in step S4 is as follows:
s4.1: comparing the response bodies of the two sets of test environments according to a recursive comparison mode;
s4.2: if the recursive comparison results are the same, the regression verification is considered to be passed, and if the recursive comparison results are not the same, the next filtering comparison is carried out;
s4.3: setting a dictionary storage interface name, a verification mode and an ignored field in a self-defined manner, and filtering and comparing response bodies of the two sets of test environments;
s4.4: if the filtering comparison results are the same, the regression verification is considered to be successful, and if the filtering comparison results are different, the regression verification is not passed.
8. An apparatus for functional regression verification based on application program interface, comprising:
an API collection module: intercepting the interface request data to a specified directory file for test data collection;
API intelligent analysis module: cleaning and sampling the test data according to a strategy;
a playback module: connecting the test environments before and after upgrading, and simultaneously performing automatic retransmission test on the test data of the application program interface in the two environments to obtain a response body returned by the interface;
a response analysis module: comparing and analyzing the interface response bodies returned by the two sets of test environment paths, and judging whether the function verification passes;
the test result generating and publishing module: and collecting the test result, calling back the data to the playback module under the limitation of the maximum number of times of re-running, executing the requested playback action again, generating a test report and issuing the test report.
9. The apparatus of claim 8, wherein the response analysis module comprises:
a conventional comparison unit: comparing interface response bodies of the two sets of test environments according to a recursive comparison mode, and comparing key-value of each element in a return value;
a filtering comparison unit: and (4) setting the dictionary storage interface name, the verification mode and the ignored field in a self-defined manner, and filtering and comparing the response bodies of the two sets of test environments.
10. A computer storage medium having stored therein instructions that, when executed on a computer, cause the computer to perform the method of any one of claims 1-7.
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| CN117931681A (en) * | 2024-03-22 | 2024-04-26 | 云筑信息科技(成都)有限公司 | Interface diff test method based on API gateway log playback |
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