CN112650688A

CN112650688A - Automated regression testing method, associated device and computer program product

Info

Publication number: CN112650688A
Application number: CN202011618483.3A
Authority: CN
Inventors: 邓泳笙; 曾凌子; 符敬伟; 江旻; 杨杨; 张晶
Original assignee: WeBank Co Ltd
Current assignee: WeBank Co Ltd
Priority date: 2020-12-30
Filing date: 2020-12-30
Publication date: 2021-04-13

Abstract

The application discloses an automated regression testing method, an automated regression testing device, equipment and a storage medium, and relates to the technical field of artificial intelligence, wherein the automated regression testing method comprises the following steps: when a regression test instruction is detected, acquiring flow data which is intercepted and obtained based on preset configuration information in the prior test process and comprises interface subdata and calling logic subdata; generating regression test data based on the flow data; carrying out automatic testing based on the regression testing data to obtain a first testing result; and acquiring a second test result recorded in the prior test process, and generating a final test result based on the first test result and the second test result. According to the method and the device, not only is the response change of the http interface concerned, but also the database response operation behind the http interface concerned, and the range of the detection points is widened, so that the detection is more comprehensive, and the test accuracy is improved.

Description

Automated regression testing method, associated device and computer program product

Technical Field

The present application relates to the field of artificial intelligence in financial technology (Fintech), and in particular, to an automated regression testing method, associated devices, and computer program products.

Background

With the continuous development of financial science and technology, especially internet science and technology, more and more technologies (such as distributed and artificial intelligence) are applied to the financial field, but the financial industry also puts higher requirements on the technologies, such as higher requirements on regression testing in the financial industry.

The automatic REGRESSION TESTING (AUTO REGRESSION TESTING) refers to that after an old code is modified to obtain a new code, the modified new code is tested again to confirm whether a new error is introduced into the modified new code or other associated codes are generated, and with gradual and rapid iterative development of the code, the REGRESSION TESTING is performed more frequently, and the REGRESSION TESTING is performed for a plurality of times every day to form a normal state of a tester, so that how to effectively perform the REGRESSION TESTING becomes a technical problem to be solved urgently.

At present, page operation is usually recorded in a script form, and automatic regression testing of a page http interface is realized by executing the corresponding script, and the script of the page operation, whether directly written or obtained based on an existing tool, only focuses on response change of the http interface, and a test check point is too coarse, so that partial defects are difficult to find by an automatic regression testing means. For example, code change causes a certain database operation of the a function module to be incorrect (or call logic of other systems to be incorrect), but does not affect the response of the a function module, and after the a function module is subjected to automatic regression testing, response results of interface regression testing are consistent, and finally, the existence of defects is not found.

Disclosure of Invention

The application mainly aims to provide an automatic regression testing method, device, equipment and storage medium, and aims to solve the technical problem that the existing script for executing page operation realizes the automatic regression testing of a page http interface, and the testing is not comprehensive, so that the testing accuracy is low.

In order to achieve the above object, the present application provides an automated regression testing method, including:

when a regression test instruction is detected, acquiring flow data which is intercepted and obtained based on preset configuration information in the prior test process and comprises interface subdata and calling logic subdata;

generating regression test data based on the flow data;

carrying out automatic testing based on the regression testing data to obtain a first testing result;

and acquiring a second test result recorded in the prior test process, and generating a final test result based on the first test result and the second test result.

Optionally, the step of generating regression test data based on the flow data includes:

acquiring first backup data of the regression testing instruction from a preset data warehouse;

generating regression test data based on the flow data and the first backup data.

Optionally, before the step of obtaining the first backup data from the preset data warehouse, the method includes:

receiving a data backup instruction, and acquiring a user identification code corresponding to the data backup instruction;

calling a preset data loading model based on the user identification code to execute corresponding preset query capture logic in preset source data to obtain second backup data of the user identification code;

saving the second backup data in the preset data warehouse, wherein the first backup data is a subset of the second backup data.

Optionally, the step of generating regression test data based on the flow data and the first backup data includes:

performing state reduction processing on the flow data and the first backup data to obtain a regression test case in a reduction state;

and performing time sequence translation processing on the date field of the regression test case in the reduction state to obtain the regression test case.

Optionally, the step of performing time-series translation processing on a date field of the regression test case in the reduction state to obtain the regression test case includes:

determining each date field and each corresponding retention date in the preset source data, and determining each first bill daily service date in the preset source data;

calculating the date time sequence corresponding to each date field based on each first bill daily business date;

obtaining real dates corresponding to all date time sequences based on the time sequence of the retention date corresponding to the current business date and the date time sequence corresponding to each date field;

and obtaining a regression test case based on the real date and the regression test case of the reduction state.

Optionally, the flow data includes sub-flow interface data, and the step of performing an automated test based on the regression test data to obtain a first test result includes:

performing an automated test based on the regression test data;

in the automatic test process, if any sub-flow data configuration is detected to be a preset mock response configuration, the preset call logic is not executed, and the sub-flow interface response result is directly obtained to obtain a first test result.

Optionally, the step of acquiring, when the regression test instruction is detected, flow data including interface sub data and call logic sub data intercepted and obtained based on preset configuration information in a previous test process includes:

when a regression test instruction is detected, extracting keywords in the regression test instruction, and acquiring a service system flow number in the regression test instruction;

and acquiring flow data which is intercepted and obtained based on preset configuration information in the prior test process and comprises interface subdata and calling logic subdata based on the keywords and the service system flow number.

Optionally, before the step of obtaining a second test result recorded in a previous test process and generating a final test result based on the first test result and the second test result, the method includes:

performing multiple playback on the flow data corresponding to the preset interface scene to obtain multiple playback results;

and comparing response fields of the same flow part of the playback result, performing difference analysis on the response fields, taking different fields among the response fields as noise fields, and obtaining a transaction noise field set based on the noise fields.

Optionally, the step of obtaining a second test result recorded in a previous test process, and generating a final test result based on the first test result and the second test result, includes:

acquiring a second test result recorded in the prior test process, and comparing the first test result with the second test result;

determining whether the difference fields of the first test result and the second test result all fall within the set of transaction noise fields;

and if all the difference fields belong to the transaction noise field set, determining that the first test result is consistent with the second test result, and generating a final test result which is successful.

The present application further provides an automated regression testing apparatus, the automated regression testing apparatus includes:

the first obtaining module is used for obtaining flow data which is obtained by intercepting based on preset configuration information in the prior testing process and comprises interface subdata and calling logic subdata when a regression testing instruction is detected;

the generating module is used for generating regression testing data based on the flow data;

the second acquisition module is used for carrying out automatic testing based on the regression testing data to obtain a first testing result;

and the third obtaining module is used for obtaining a second test result recorded in the prior test process and generating a final test result based on the first test result and the second test result.

Optionally, the generating module includes:

the first obtaining unit is used for obtaining first backup data of the regression testing instruction from a preset data warehouse;

and the generating unit is used for generating regression test data based on the flow data and the first backup data.

Optionally, the automated regression testing apparatus further includes:

the fourth acquisition module is used for receiving a data backup instruction and acquiring a user identification code corresponding to the data backup instruction;

the calling module is used for calling a preset data loading model based on the user identification code so as to execute corresponding preset inquiry capture logic in preset source data and obtain second backup data of the user identification code;

and the storage module is used for storing the second backup data in the preset data warehouse, wherein the first backup data is a subset of the second backup data.

Optionally, the regression test data includes regression test cases, and the first generating unit includes:

the state reduction subunit is used for carrying out state reduction processing on the flow data and the first backup data to obtain a regression test case of a reduction state;

and the time sequence translation processing subunit is used for performing time sequence translation processing on the date field of the regression test case in the reduction state to obtain the regression test case.

Optionally, the state atomic unit is further configured to implement:

Optionally, the traffic data includes sub-traffic interface data, and the second obtaining module includes:

the automatic test unit is used for carrying out automatic test based on the regression test data;

and the second obtaining unit is used for directly obtaining the response result of the sub-flow interface without executing a preset calling logic when detecting that any sub-flow data is configured to be the preset mock response configuration in the automatic testing process so as to obtain the first testing result.

Optionally, the first obtaining module includes:

the extraction unit is used for extracting keywords in the regression testing instruction when the regression testing instruction is detected, and acquiring a service system flow number in the regression testing instruction;

and a third obtaining unit, configured to obtain, based on the keyword and the traffic number of the service system, traffic data including interface sub data and call logic sub data, which is intercepted based on preset configuration information in a previous testing process.

Optionally, the automated regression testing apparatus further includes:

the playback module is used for playing back the flow data corresponding to the preset interface scene for multiple times to obtain multiple playback results;

and the difference analysis module is used for comparing the response fields of the same flow part of the playback result, performing difference analysis on the response fields, taking different fields among the response fields as noise fields, and obtaining a transaction noise field set based on the noise fields.

Optionally, the third obtaining module includes:

a fourth obtaining unit, configured to obtain a second test result recorded in a previous test process, and compare the first test result with the second test result;

a first determining unit, configured to determine whether all of the difference fields of the first test result and the second test result belong to the transaction noise field set;

and the second determining unit is used for determining that the first test result is consistent with the second test result and generating a final test result which is successful if all the difference fields belong to the transaction noise field set.

The present application further provides an automated regression testing device, the automated regression testing device is an entity device, the automated regression testing device includes: a memory, a processor, and a program of the automated regression testing method stored on the memory and executable on the processor, the program of the automated regression testing method when executed by the processor implementing the steps of the automated regression testing method as described above.

The present application also provides a storage medium having a program stored thereon for implementing the automated regression testing method, wherein the program for implementing the automated regression testing method implements the steps of the automated regression testing method when executed by a processor.

The present application also provides a computer program product, comprising a computer program, which when executed by a processor, performs the steps of the automated regression testing method described above.

Compared with the conventional method for realizing the automatic regression test of a page http interface by executing a script of page operation, the method has the advantages that the test is incomplete, and the test accuracy is low, the method obtains flow data including interface subdata and call logic subdata which are intercepted based on preset configuration information in the prior test process when a regression test instruction is detected; generating regression test data based on the flow data; carrying out automatic testing based on the regression testing data to obtain a first testing result; and acquiring a second test result recorded in the prior test process, and generating a final test result based on the first test result and the second test result. In the application, when a regression test instruction is detected, flow data including interface sub data and call logic sub data intercepted and obtained based on preset configuration information in the prior test process is obtained, that is, in the application, besides interface sub data such as an http interface, a code function interface and the like needing to be intercepted and recorded are configured in advance, call logic sub data such as back database operation and call logic between systems behind the interface sub data are recorded in real time to form flow data, regression test data is generated based on the flow data to further obtain a first test result, and automatic regression test is completed. In this application, not only pay close attention to the response change of http interface, and pay close attention to the database response change behind one's back, widened the scope of check point, therefore, make the detection more comprehensive, also make the test accuracy promote.

Drawings

The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and together with the description, serve to explain the principles of the application.

In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings needed to be used in the description of the embodiments or the prior art will be briefly described below, and it is obvious for those skilled in the art to obtain other drawings without inventive exercise.

FIG. 1 is a schematic flow chart of a first embodiment of an automated regression testing method of the present application;

FIG. 2 is a flowchart illustrating a step refinement of S10 in the first embodiment of the automated regression testing method of the present application;

FIG. 3 is a schematic diagram of an apparatus configuration of a hardware operating environment according to an embodiment of the present application;

fig. 4 is a schematic view of a scenario related to an embodiment of the present application.

The objectives, features, and advantages of the present application will be further described with reference to the accompanying drawings.

Detailed Description

It should be understood that the specific embodiments described herein are merely illustrative of the present application and are not intended to limit the present application.

In a first embodiment of the automated regression testing method of the present application, referring to fig. 1, the automated regression testing method includes:

step S10, when a regression test instruction is detected, flow data including interface subdata and call logic subdata intercepted and obtained based on preset configuration information in the prior test process is obtained;

step S20, generating regression test data based on the flow data;

step S30, carrying out automatic test based on the regression test data to obtain a first test result;

step S40, obtaining a second test result recorded in the previous test process, and generating a final test result based on the first test result and the second test result.

The method comprises the following specific steps:

in this embodiment, it should be noted that the traffic includes a request call, a complete traffic includes a one-time complete request call path and corresponding access parameters, and further, the traffic data includes a request call path and corresponding access parameters.

In the present embodiment, a distinction is made between main/sub flows (MAINFLOW/SUBFLOW), where a sub flow is relative to a main flow, the main flow is an entry call of a request, and a sub flow is a request call subsequently caused by the main flow, such as a DB (database) operation, a request call of an external system, and the like.

FLOW RECORD (FLOW RECORD) refers to storing a FLOW RECORD, where the FLOW RECORD includes a request and a response of a main FLOW, a request and a response of a sub-FLOW, and the like.

FLOW play back (FLOW play) refers to the invocation of a request to trigger a previously recorded primary FLOW to enable repeated execution of the FLOW.

In this embodiment, the automated regression testing method is applied to an automated regression testing apparatus, which belongs to automated regression testing equipment, and the automated regression testing equipment may be separately arranged, or may be a system combined with other equipment. In this embodiment, it should be noted that the automated regression testing device is in communication connection with the programming end, so as to directly acquire the new code to perform the automated regression testing after the programming of the programming end is completed or after the application changes the version (the old code is modified into the new code). In addition, in this embodiment, the automated regression testing device further performs communication connection with the service system end (the end where each item of test data recorded corresponding to the old code is located) to obtain data of the service system end, and establishes a database or a data warehouse. In this embodiment, it should be noted that the end where each item of test data recorded corresponding to the old code is located may be referred to as a service system end because each item of test performed based on the service data (in an actual scene) is directly recorded, that is, at the service system end, each item of response corresponding to the interface of the service system end is recorded after each user performs a loan operation. The service system may include a plurality of subordinate systems, and thus, at the service system end, recorded responses corresponding to the interfaces of the sub-service systems may be after the user operates the sub-systems.

Overall, in this embodiment, the automated regression testing device receives a new code from the programming end, and the automated regression testing device generates regression testing data of the new code based on previous traffic data (already configured based on the configuration information) of the service system end, tests the new code, and further compares the testing result of the new code with the testing result of the old code in the previous traffic data, thereby determining whether the new code is successfully tested.

In this embodiment, it should be noted that the automated regression testing device may provide a visual interface, and each function selection of the regression test may be performed on the visual interface, where each function selection of the regression test includes: the function selection of the regression test scenario, the function selection of the regression test time, the function selection of the regression test flow, or the function selection of the regression test version, etc. it should be noted that the automated regression test equipment provides a visual interface for each function selection, and the basis for each function selection is as follows: the automatic regression testing equipment comprises a data backup and restoration module, a flow recording and playback module, a visual flow management module and other functional modules, and various visual functions are realized based on the functional modules, wherein, specifically,

the data backup and restoration module: through preset configuration information (such as time configuration, scene configuration and the like), a user can back up database data related to a test scene in real time, and restore the database data related to the test scene in an automatic regression test stage, so that the problem that the consumption of preset data construction resources is high at present is solved.

The flow recording and playback module: the module is based on a sandbox technology, database operation behind a page http interface, interface access parameter and the http interface and call logic between systems can be recorded in real time by configuring an http interface and a code function interface which need to be intercepted and recorded, flow data is formed, a test case is automatically generated based on the flow data, and the playback of flow is realized through a flow visualization management module in an automatic regression test stage.

The sandbox technology is essentially an AOP landing form, and is an open-source AOP solution for a JVM platform in a non-intrusive operation period, wherein the AOP is the continuation of the OOP and is an important content in a Spring framework, and each part of business logic can be isolated by using the AOP, so that the coupling degree between each part of the business logic is reduced, the reusability of a program is improved, and the development efficiency is improved.

Visual flow management module: the method specifically comprises 5 parts of flow management, playback management, configuration management, scene management and playback control, wherein the flow management can search and view the flow recorded in real time, the playback management can search and view the flow played back, the configuration management can configure a http interface and a code function interface which need to intercept and record in a self-defined mode, the scene management can enable a user to construct a case scene in a self-defined mode through keywords, and the playback control can perform plan pull-up and playback result comparison on the flow in a visual mode to realize automatic regression testing of a page http interface.

In this embodiment, it should be noted that the automated regression test based on the http interface is mainly performed from the perspective of the http interface, the corresponding http interface triggered by the page operation and the corresponding interface entry references are recorded, and the automated regression test of the page http interface is implemented by sending the interface twice and comparing the interface responses. In this embodiment, the automated regression testing method not only includes the automated regression testing of the http interface, but also includes the response testing of the associated database, so as to realize the comprehensive automated regression testing, and further, improve the testing accuracy.

For testers, the visual flow management module enables the flow management of real-time recording to be clearer and the flow playback plan pull-up process to be more convenient. The visualized flow management module mainly comprises 5 parts of flow management, playback management, configuration management, scene management and playback control, and specifically comprises the following steps:

a traffic management section: the traffic management part mainly comprises 3 functions: recording outlines, main flow list query and sub-flow query under subsystems, wherein the recording outlines can be used for checking the flow recording conditions of various service subsystems (subordinate systems of the service systems), such as flow recording quantity and the like, and searching the flow according to a globally unique flow id;

the playback management section: the playback management part mainly comprises 3 functions of playback summary, sub-system playback flow list query and playback sub-flow query. The playback summary can be used for checking the flow playback conditions of each service subsystem, such as the flow playback quantity and the like, and meanwhile, the flow can be searched according to the globally unique flow id; the query of the playback flow list under the subsystem can check all the playback flow details under the specific service subsystem, and the playback flow can be searched through keywords, such as an identity card and the like; and playing back the sub-flow list, and inquiring the details of the corresponding sub-flow under the playback main flow.

A configuration management section: the configuration management part mainly comprises 4 functions of configuration management, playback configuration, baffle configuration and flow request replacement configuration. Configuration management configures an http interface and a code function interface which need to be intercepted and recorded, the configuration process is one-time, and the configuration of flow recording cannot be influenced by logic change of interface codes at the later stage; the playback configuration configures the types of interfaces needing to be intercepted and played back in the flow playback process, such as java interfaces, http interfaces, DB operations and the like; the baffle configuration, also called mock configuration, allows a user to customize interfaces that do not require mock during the flow playback process; and flow request replacement configuration, wherein in the flow playback process, a user can replace the request field of the main flow to adapt to more test scenarios.

A scene management section: the scene management part comprises 2 functions of scene management and scene flow inquiry. Scene management, wherein a user can define keywords by self, manually construct a flow scene to regress and test a special scene, and meanwhile, the constructed scene can be subjected to operations of increasing, deleting, modifying and checking; and (4) scene flow query, which can search and check the flow contained in the test scene.

The playback control section: the playback control part comprises 5 functions of newly building a playback task, performing playback, comparing playback results, inquiring the playback task and playing back step details. Newly building a playback task, wherein a user can build the playback task based on two modes, one mode is to search for new construction based on a service subsystem, and the other mode is to search for new construction based on the existing scene; playback execution, after the playback task is newly established, a user can execute the corresponding playback task to realize automatic regression testing; comparing the playback results, and after the flow playback is finished, comparing the playback flow results with the recorded flow to help a user to quickly analyze regression results; the playback task query can be used for performing query operation on the playback task established by the user; and the details of the playback step can be checked, and the details of the playback results of the main flow and the sub flow after the flow is played back can be checked.

When a regression test instruction is detected, flow data including interface sub data and call logic sub data intercepted and obtained based on preset configuration information in a prior test process is obtained, specifically, before the regression test instruction is detected, an automatic regression test device tests an old code, that is, a prior test process exists, before the prior test, a tester configures configuration information based on a visual interface, that is, configuration information is preset, and because the configuration information is preset, for each prior test process, flow data including the interface sub data and the call logic sub data can be intercepted and obtained based on the preset configuration information, in this embodiment, it needs to be emphasized that not only data such as a page http interface and interface access parameters are intercepted, but also database operation behind the http interface and call logic between systems are intercepted, that is, in the present embodiment, the request path and the response path of all operations are intercepted, not just the path and the response path of the interface. Specifically, how to intercept data such as a page http interface and interface access references and how to intercept database operation behind the http interface and call logic between systems are obtained in a configuration mode.

In this embodiment, in order to implement intercepting data such as a page http interface and interface access parameter, and intercepting database operations and call logic between systems behind the http interface, an interception configuration file may also be directly imported, instead of selecting only through a visualization manner, where the visualization is only one of the manners.

Step S20, generating regression test data based on the flow data;

in this embodiment, after obtaining the flow data, a regression test case is generated based on the flow data, specifically, the flow data may be combined with a preset scenario set (that is, parameters of the preset scenario set are changed based on the flow data, or a flow of the preset scenario set is changed, or the like) to generate the regression test case, that is, the regression test data is obtained.

Referring to fig. 2, the step of generating regression test data based on the flow data includes:

step S21, acquiring first backup data of the regression test instruction from a preset data warehouse;

in this embodiment, it should be noted that two technologies of backup and restoration of data and recording and playback of traffic are combined, so that the construction cost of the pre-data is reduced, and at the same time, a regression test is performed from a code function interface level, so that test checkpoints are covered more comprehensively; in the embodiment, the first backup data of the regression test instruction is obtained from the preset data warehouse instead of constructing the pre-data, so that the time cost and the resource cost are saved, and in addition, it is emphasized that the preset data warehouse is realized through the data backup and restoration module. The module can be realized by combining and calling the existing database data backup restoration tool. The database data backup and reduction tool can backup database data related to scenes in real time through data training or user configuration, and is associated with a test case automatically constructed in a flow recording and playback module, so that database data responded by the test case is reduced in an automatic regression test stage, an automatic regression plan can be pulled up, and automatic regression test of a page http interface is realized.

It should be noted that the data backup and restore module solves the problem of recycling of data forms in a lifecycle, and can permanently store the data forms as long as the data forms are generated once (where a data form refers to data with a complex lifecycle, and each stage of the lifecycle of the data corresponds to one data form).

The first backup data of the regression testing instruction is obtained from a preset data warehouse, specifically, the first backup data of the regression testing instruction is obtained from the preset data warehouse through a scene identification code, and the scene identification code may be carried in the regression testing instruction.

Before the step of obtaining the first backup data from the preset data warehouse, the method includes:

step S01, receiving a data backup instruction, and acquiring a user identification code corresponding to the data backup instruction;

in this embodiment, before the step of obtaining the first backup data from the preset data warehouse, the construction of the preset data warehouse is already completed, and to complete the construction of the preset data warehouse, a data backup instruction needs to be received on a visual interface, so as to obtain a user identification code corresponding to the data backup instruction, where the user identification code may be an identification number, a client number, and specifically, triggering the data backup instruction on the visual interface includes: and clicking a triggering backup instruction by manually inputting a source card number (a bank card number of a user and the like) related to a scene, a source environment, a selection library and the like.

Step S02, based on the user identification code, calling a preset data loading model to execute corresponding preset query capture logic in preset source data to obtain second backup data of the user identification code;

based on the user identification code, calling a preset data loading model to execute corresponding preset inquiry and capture logic in preset source data to obtain second backup data of the user identification code, namely in the embodiment, the second backup data is a trained data model to capture data forms generated in the process of testing the business system and put or store the data forms into a data warehouse for later-stage restoration.

The process of calling a preset data loading model to execute a corresponding preset query capture logic in preset source data to obtain second backup data of the user identification code may be: loading a data model, executing an sql (query sql) statement to a source environment (source data) based on key data (user identification codes), namely capturing all related data, and simultaneously capturing a service date at the moment as a stay date of the form, wherein it needs to be explained that a scene id can be uniquely determined by using a source card number (user card number data), the service date of the stay date and a scene name, if the scene id does not exist in a data warehouse, storing the captured data and storing the captured data in the data warehouse, and if the scene id does not exist, prompting that the data is repeatedly stored.

Step S03, saving the second backup data in the preset data warehouse, wherein the first backup data is a subset of the second backup data.

In this embodiment, the backup instruction corresponding to the second backup data is stored in the preset data warehouse, where the first backup data is a subset of the second backup data, that is, the first backup data is extracted from the second backup data directly through a scene id (carried in the regression test instruction), or extracted through a user association number (carried in the regression test instruction).

Step S22, generating regression test data based on the flow data and the first backup data.

The regression test data includes regression test cases, and the step of generating regression test data based on the flow data and the first backup data includes:

step A1, performing state restoration processing on the flow data and the first backup data to obtain a regression test case in a restoration state;

and A2, performing time sequence translation processing of a date field on the regression test case in the reduction state to obtain the regression test case.

In this embodiment, the traffic data and the first backup data are subjected to state restoration processing to obtain a regression test case in a restoration state, and the regression test case in the restoration state is subjected to time-series translation processing of a date field to obtain a regression test case. As shown in fig. 4, that is, in this embodiment, first, according to the previously prepared data (including the previous traffic data), the data related to the test scenario is restored to the state before the test case is executed (obtained by calling the preset restoring program or the restoring logic).

The step of performing time sequence translation processing of a date field on the regression test case in the reduction state to obtain the regression test case comprises the following steps:

step B1, determining each date field and each corresponding retention date in the preset source data, and determining each first bill daily service date in the preset source data;

step B2, calculating the date time sequence corresponding to each date field based on each first bill daily business date;

step B3, obtaining the real date corresponding to all date time sequences based on the time sequence of the retention date corresponding to the current business date and the date time sequence corresponding to each date field;

and step B4, obtaining a regression test case based on the real date and the regression test case of the reduction state.

In this embodiment, it should be noted that the BUSINESS DATE (BUSINESS DATE) refers to that all systems in the loan core have a unified DATE, and this DATE is the DATE on which the system itself rolls forward, all transactions will be subject to this DATE, and the BUSINESS DATE of the production environment is daily cut at 00:00:00 pm every night, so the BUSINESS DATE is the same as the system DATE, but the test environment may be daily cut multiple times every DAY, or batch skipping may be performed, so the BUSINESS DATE is different from the system DATE (current beijing time), that is, in this embodiment, the BUSINESS DATE may be the same as or different from the system DATE, and the BUSINESS DATE is associated with the daily cut, and the retention DATE (STAY DATE): the time when the slice (data slice) is put into the data warehouse and the business date when the data form is frozen are referred to. DATE timing (BUSINESS DATE ORDER): the relative days of the business date of each transaction and the bill day are in the format of NT +/-M (representing the Nth bill day +/-M days), and if the first bill day represents 1T +0, the date time sequence of the day before the bill day is 1T-1.

In this embodiment, because the regression testing time is not consistent with the recording testing time, the date field shift processing is required for the time data related to the service logic and the service life cycle to adapt to the application requirement of cross-environment and cross-service dates, wherein the date field time sequence shift adopts a date field time sequence shift algorithm, and the steps are as follows:

determining each date field and each corresponding retention day in the preset source data, determining each first bill day service date in the preset source data, and calculating the date time sequence corresponding to each date field based on each first bill day service date; obtaining real dates corresponding to all date time sequences based on the time sequence of the retention date corresponding to the current business date and the date time sequence corresponding to each date field; and obtaining a regression test case based on the real date and the regression test case of the reduction state. Specifically, each date field and the stop date of the source data are extracted according to the date field in the data model; finding out the first bill day business date of the source data according to the bill day sql statement configured in the data model; and then, calculating the date time sequence (NT +/-M (representing the Nth bill day +/-M day) of each date field of the source data based on the business date of the first bill day, wherein if the first bill day represents 1T +0, the date time sequence of the day before the bill day is 1T-1), namely, the date time sequence of each date field can be obtained through the expression of the business date of each bill day, and the true dates corresponding to all the date time sequences are obtained based on the time sequence of the stay day corresponding to the current business date and the date time sequence corresponding to each date field, namely, the true dates of each date time sequence of the date field can be determined based on the relationship between the true dates and the stay days and the date time sequence and the stay day of each date field.

in this embodiment, after obtaining the regression test data, an automated test is performed based on the regression test data to obtain a first test result, and a specific test process is not described in detail.

In this embodiment, a second test result recorded in a previous test process is obtained, the first test result is compared with the second test result, whether the first test result is identical to the second test result is determined, if so, the automatic regression test corresponding to the regression test instruction is successfully completed, and if not, the automatic regression test is not successful, and subsequent relief processing is required.

If not, the following relief processing method comprises the following steps:

if not, determining whether different parts are transaction noise fields, and if so, determining that the automatic regression test corresponding to the regression test instruction is successfully completed without subsequent relief processing;

if the two parts are not completely the same and the different parts are not transaction noise fields, a subsequent relief process is performed, wherein the relief process can be a process of generating prompt information for the tester to process.

Compared with the automatic regression testing of a page http interface realized by executing a script of page operation at present, so that the testing accuracy is low, the method obtains flow data which is obtained by intercepting based on preset configuration information in the prior testing process and comprises interface subdata and calling logic subdata when a regression testing instruction is detected; generating regression test data based on the flow data; carrying out automatic testing based on the regression testing data to obtain a first testing result; and acquiring a second test result recorded in the prior test process, and generating a final test result based on the first test result and the second test result. In the application, when a regression test instruction is detected, flow data including interface sub data and call logic sub data intercepted based on preset configuration information in the prior test process is obtained, that is, in the application, besides interface sub data such as an http interface, a code function interface and the like needing to be intercepted and recorded are configured in advance, call logic sub data such as back database operation and call logic between systems behind the interface sub data are recorded in real time to form flow data, and regression test data is generated based on the flow data to further automate regression test. In this application, not only pay close attention to the response change of http interface, and pay close attention to the database response change behind one's back, widened the scope of check point, therefore, make the detection more comprehensive, also make the test accuracy promote.

In another embodiment of the present application, in the step of performing an automated regression test based on the regression test data to obtain a first test result, the method includes:

step C1, performing an automated test based on the regression test data;

and step C2, in the automatic test process, if any sub-flow data configuration is detected to be a preset mock response configuration, the preset call logic is not executed, and the sub-flow interface response result is directly obtained to obtain a first test result.

In this embodiment, in the process of the automated testing, if it is detected that any sub-traffic data is configured as the preset mock response configuration, the preset call logic is not executed, and the response result of the sub-flow interface is directly obtained to obtain the first test result, that is, when the flow playback is carried out (automatic test is carried out based on regression test data), a preset repeater monitors the sub-flow of the system A, if the sub-flow is set to mock in the configuration, the repeater acquires the sub-flow response and directly returns the sub-flow response to the system A, and real call does not need to be generated, otherwise, if mock is not set, real call is generated, it should be noted that, the mock function is applied in a regression test scenario, by not performing mock setting on a change point (to avoid an inability to accurately determine whether a change point would cause an error), and the mock setting is carried out in a non-changed place, so that the problems of environment deployment and the like of non-changed point testing can be reduced.

In the embodiment, an automatic test is performed based on the regression test data; in the automatic test process, if any sub-flow data configuration is detected to be a preset mock response configuration, the preset call logic is not executed, and the sub-flow interface response result is directly obtained to obtain a first test result. In this embodiment, if it is detected that any sub-flow data configuration is the preset mock response configuration, the preset call logic is not executed, so that failure of the automated regression test due to instability of an external system is avoided, and the execution success rate of the test case is improved.

In another embodiment of the automated regression testing method, the step of obtaining flow data including interface sub data and call logic sub data intercepted based on preset configuration information in a prior testing process when a regression testing instruction is detected includes:

step C1, when a regression testing instruction is detected, extracting keywords in the regression testing instruction, and acquiring a service system flow number in the regression testing instruction;

and step C2, based on the keyword and the traffic number of the service system, obtaining the traffic data which is intercepted and obtained based on the preset configuration information in the prior test process and comprises the interface subdata and the call logic subdata.

In this embodiment, it should be noted that, because the traffic data of the service system is many (any loan client is recorded in real time), an elk-based traffic search engine may be established to query all traffic related to the transaction of the service system in a related manner, and specifically, all related traffic may be queried according to the serial number of the service system or keywords selected by the user.

That is, when a regression test instruction is detected, a keyword in the regression test instruction is extracted, a service system flow number in the regression test instruction is obtained, and flow data including interface subdata and call logic subdata intercepted and obtained based on preset configuration information in a previous test process is obtained based on the keyword and the service system flow number, that is, in a complete service transaction scene, a plurality of subsystems are involved, and not all flows contain keywords provided by a user, so that a scene is established only based on the flow containing the keyword selected by the user, and the problem of flow omission exists. In order to solve the problem, a mark capable of associating the whole transaction flow is needed, and in a service transaction scene, the flow numbers (service system flow numbers) of all service subsystems involved in the whole transaction can be uniquely associated based on the service system flow numbers, so that flow data can be comprehensively obtained, flow regression data can be quickly constructed, and then regression testing can be quickly carried out.

In this embodiment, when a regression test instruction is detected, extracting a keyword in the regression test instruction, and obtaining a service system traffic number in the regression test instruction; and acquiring flow data which is intercepted and obtained based on preset configuration information in the prior test process and comprises interface subdata and calling logic subdata based on the keywords and the service system flow number. In the embodiment, the flow data is accurately and quickly intercepted, and a foundation is laid for quickly carrying out regression testing.

In another embodiment of the automated regression testing method, before the step of uploading the installation package file to a server side for the server side to search a feature record matched with the key feature to be detected based on a preset second malicious record information base, the method includes:

before the step of obtaining a second test result recorded in a previous test process and generating a final test result based on the first test result and the second test result, the method includes:

d1, performing multiple playback on the flow data corresponding to the preset interface scene to obtain multiple playback results;

and D2, comparing the response fields of the same flow part of the playback result, performing difference analysis on the response fields, taking different fields among the response fields as noise fields, and obtaining a transaction noise field set based on the noise fields.

In this embodiment, a user may newly create a playback task based on a playback control portion on a visual interface, specifically, the user may create the playback task based on two ways, one is to search for the new playback task based on a service subsystem, the other is to search for the new playback task based on an existing scene, after the playback task is newly created, the user may execute a corresponding playback task to implement an automated regression test, after the traffic playback is finished, compare a result of the playback traffic result with a result of the recorded traffic to quickly analyze the regression result, specifically, in this embodiment, after the traffic playback is finished, a preset tool background performs polling monitoring on the playback task, and checks whether the playback state is finished; when the playback state of the flow playback is monitored to be finished, comparing the played back main flow response with the recorded main flow response, specifically, comparing the playback result with the response fields of the same flow part, performing difference analysis on the response fields, taking different fields among the response fields as noise fields, obtaining a transaction noise field set based on the noise fields, performing comparison on the playback result with the response fields of the same flow part, wherein the response fields of the main flow can be firstly compared, and if the recorded and played back responses of the main flow are not different, the requests of the sub flow are continuously compared, and the existing difference fields are analyzed; and finally, returning the analysis result to the user to help the user to quickly analyze the regression result.

In the process of comparing the playback results, due to the existence of "noise", the comparison of the playback results has a high false alarm rate. For example, the fields of the service system flow number, CASENO, APPNO, and the like are different in each service transaction, but the difference in the flow playback result caused by these fields is not the difference in the playback result that the user really needs to pay attention to. For the transaction noise fields, in order to avoid influencing the playback result difference which really needs to be concerned, in this embodiment, a mode of automated construction of the transaction noise field set and iterative incremental maintenance of the noise field set is adopted.

Specifically, the construction method may be: when there is no code change, the playback results should be identical for multiple playbacks of traffic for one stable interface scenario. Based on the point, the preset tool script periodically plays back stable flow of each service system for multiple times, and difference analysis is carried out on playback results so as to automatically construct a transaction noise field set.

Iterative incremental maintenance of a set of transaction noise fields. Based on the transaction noise field set constructed automatically, the false alarm rate of the flow playback result is greatly reduced, but the transaction noise field still exists, so that a user can artificially mark the transaction noise field and perform iterative incremental maintenance on the transaction noise field set in the using process of the user.

In the embodiment, multiple playback results are obtained by performing multiple playback on the flow data corresponding to the preset interface scene; and comparing response fields of the same flow part of the playback result, performing difference analysis on the response fields, taking different fields among the response fields as noise fields, and obtaining a transaction noise field set based on the noise fields. In this embodiment, the transaction noise field set is accurately obtained, and in this embodiment, the transaction noise field set is accurately obtained, so that influence of irrelevant difference fields on the test result is avoided.

the step of obtaining a second test result recorded in a previous test process and generating a final test result based on the first test result and the second test result comprises:

step E1, obtaining a second test result recorded in the prior test process, and comparing the first test result with the second test result;

step E2, determining whether the difference fields of the first test result and the second test result all belong to the transaction noise field set;

and E3, if all the difference fields belong to the transaction noise field set, determining that the first test result is consistent with the second test result, and generating a final test result which is successful.

In this embodiment, it is determined whether all of the difference fields of the first test result and the second test result belong to the transaction noise field set, if all of the difference fields belong to the transaction noise field set, it is determined that the first test result is consistent with the second test result, a test result that the final test is successful is generated, and if not, a test result that the final test is failed is generated, that is, it is determined that the automated regression test corresponding to the regression test instruction is not successfully completed, and prompt information is generated, so that a subsequent tester can query the test result.

In the embodiment, the first test result and the second test result are compared by obtaining the second test result recorded in the prior test process; determining whether the difference fields of the first test result and the second test result all fall within the set of transaction noise fields; and if all the difference fields belong to the transaction noise field set, determining that the first test result is consistent with the second test result, and generating a final test result which is successful. In this embodiment, by determining whether all the difference fields of the first test result and the second test result belong to the transaction noise field set, the influence of the irrelevant difference fields on the test results is avoided.

Referring to fig. 3, fig. 3 is a schematic device structure diagram of a hardware operating environment according to an embodiment of the present application.

As shown in fig. 3, the automated regression testing apparatus may include: a processor 1001, such as a CPU, a memory 1005, and a communication bus 1002. The communication bus 1002 is used for realizing connection communication between the processor 1001 and the memory 1005. The memory 1005 may be a high-speed RAM memory or a non-volatile memory (e.g., a magnetic disk memory). The memory 1005 may alternatively be a memory device separate from the processor 1001 described above.

Optionally, the automated regression testing device may further include a rectangular user interface, a network interface, a camera, RF (Radio Frequency) circuitry, a sensor, audio circuitry, a WiFi module, and so on. The rectangular user interface may comprise a Display screen (Display), an input sub-module such as a Keyboard (Keyboard), and the optional rectangular user interface may also comprise a standard wired interface, a wireless interface. The network interface may optionally include a standard wired interface, a wireless interface (e.g., WI-FI interface).

Those skilled in the art will appreciate that the automated regression testing device configuration shown in FIG. 3 does not constitute a limitation of automated regression testing devices, and may include more or fewer components than shown, or some components in combination, or a different arrangement of components.

As shown in fig. 3, the memory 1005, which is a kind of computer storage medium, may include therein an operating system, a network communication module, and an automated regression test program. The operating system is a program that manages and controls the hardware and software resources of the automated regression testing equipment, supporting the operation of the automated regression testing program as well as other software and/or programs. The network communication module is used for realizing communication among the components in the memory 1005 and communication with other hardware and software in the automated regression testing system.

In the automated regression testing apparatus shown in fig. 3, the processor 1001 is configured to execute an automated regression testing program stored in the memory 1005 to implement the steps of any one of the automated regression testing methods described above.

The specific implementation of the automated regression testing device of the present application is substantially the same as that of the above-mentioned automated regression testing method, and is not described herein again.

The present application further provides an automated regression testing apparatus, the automated regression testing method including:

the automated regression testing apparatus includes:

Optionally, the generating module includes:

Optionally, the automated regression testing apparatus further includes:

Optionally, the state atomic unit is further configured to implement:

Optionally, the first obtaining module includes:

Optionally, the automated regression testing apparatus further includes:

Optionally, the third obtaining module includes:

The specific implementation of the automated regression testing apparatus of the present application is substantially the same as that of the above-mentioned automated regression testing method, and is not described herein again.

The present embodiments provide a storage medium, and the storage medium stores one or more programs, which may also be executed by one or more processors for implementing the steps of any one of the automated regression testing methods described above.

The specific implementation of the storage medium of the present application is substantially the same as the embodiments of the automated regression testing method, and is not described herein again.

The specific implementation of the computer program product of the present application is substantially the same as the embodiments of the automated regression testing method, and is not described herein again.

The above description is only a preferred embodiment of the present application, and not intended to limit the scope of the present application, and all modifications of equivalent structures and equivalent processes, which are made by the contents of the specification and the drawings, or which are directly or indirectly applied to other related technical fields, are included in the scope of the present application.

Claims

1. An automated regression testing method, comprising:

generating regression test data based on the flow data;

2. The automated regression testing method of claim 1, wherein the step of generating regression test data based on the flow data comprises:

3. The automated regression testing method of claim 2, wherein said step of obtaining the first backup data from the predetermined data repository is preceded by the step of:

4. The automated regression test method of claim 3, wherein the regression test data comprises regression test cases, and the step of generating regression test data based on the flow data and the first backup data comprises:

5. The automated regression testing method of claim 4, wherein said step of performing time-series translation of date field on the regression test case in the reduced state to obtain the regression test case comprises:

6. The automated regression testing method of claim 1, wherein the flow data comprises sub-flow interface data, and wherein performing the automated test based on the regression test data to obtain the first test result comprises:

performing an automated test based on the regression test data;

7. The automated regression testing method of claim 1, wherein the step of obtaining flow data including interface sub data and call logic sub data intercepted based on preset configuration information in a prior testing process when the regression testing instruction is detected comprises:

8. The automated regression testing method of any one of claims 1 to 7,

9. The automated regression testing method of claim 8, wherein the step of obtaining a second test result recorded during a previous test and generating a final test result based on the first test result and the second test result comprises:

10. An automated regression test apparatus, comprising:

11. An automated regression testing device, characterized in that the automated regression testing device comprises: a memory, a processor, and a program stored on the memory for implementing the automated regression testing method,

the memory is used for storing a program for realizing the automatic regression testing method;

the processor is configured to execute a program implementing the automated regression testing method to implement the steps of the automated regression testing method according to any one of claims 1 to 9.

12. A storage medium having stored thereon a program for implementing an automated regression testing method, the program being executed by a processor to implement the steps of the automated regression testing method according to any one of claims 1 to 9.

13. A computer program product comprising a computer program, characterized in that the computer program realizes the method of any of claims 1 to 9 when executed by a processor.