CN117667751B - Automatic testing method for low-coupling WEB service - Google Patents
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Abstract
The invention provides a low-coupling WEB service automatic test method, which relates to the technical field of data processing and is characterized in that a service component of a service to be tested is obtained through interaction and a service function is realized, a task set and a test scheme set are established based on the service function, a service test of the service to be tested is executed through the test scheme set, monitoring data is obtained, and the monitoring data, task grade identification and task execution data are used for carrying out coupling automatic test evaluation, so that a test evaluation result is generated. The technical problems that the coupling state test of the WEB service depends on manpower, the accuracy of the coupling degree test result is lower, and the iterative optimization reference value for the WEB service is weaker in the prior art are solved. The technical effect of obtaining the coupling degree of the unspecified WEB service with high reliability is achieved, and the technical effect of providing guidance and supporting reference for system design optimization iteration and module reconstruction is indirectly achieved.
Description
Technical Field
The invention relates to the technical field of data processing, in particular to a low-coupling WEB service automatic test method.
Background
At present, the coupling state test of the WEB service mainly depends on manual evaluation, however, the manual evaluation is often influenced by subjective factors, objective data and accurate results cannot be provided, the accuracy of the obtained coupling state test of the WEB service is low, and the reference value of the evaluation results with low accuracy for iterative optimization is limited.
In summary, in the prior art, the coupling state test of the WEB service depends on the manual work, the accuracy of the coupling degree test result is low, and the iterative optimization reference value of the WEB service is weak.
Disclosure of Invention
The application provides a low-coupling WEB service automatic test method, which is used for solving the technical problems that in the prior art, the coupling state test of the WEB service depends on manpower, the accuracy of a coupling degree test result is low, and the iterative optimization reference value for the WEB service is weak.
In view of the above problems, the present application provides a low-coupling WEB service automation test method.
In a first aspect of the present application, there is provided a method for automatically testing low-coupling WEB services, the method comprising: establishing service communication with a service to be tested, completing data interaction by the service communication, and establishing a service data set according to a data interaction result, wherein the service data set comprises a service component and a service function corresponding to the service component; inputting the realization service function into a task execution network, executing task matching of the realization service function, and establishing a task set, wherein each task in the task set is provided with a task grade identification; configuring a test scheme library through big data, carrying out scheme matching of the test scheme library by using the task set, and establishing a test scheme set; configuring a monitoring node of a service component based on the task set, and executing service test of the service to be tested through the test scheme set; acquiring monitoring data of a monitoring node, wherein the monitoring data has a corresponding relation with a testing scheme set; and carrying out coupling automation test evaluation by the monitoring data, the task grade identification and the task execution data to generate a test evaluation result.
In a second aspect of the present application, there is provided a low-coupling WEB services automated testing system, the system comprising: the service data integration unit is used for establishing service communication with the service to be tested, completing data interaction by the service communication, and establishing a service data set according to a data interaction result, wherein the service data set comprises a service component and a service function corresponding to the service component; the task matching execution unit is used for inputting the service realization function into a task execution network, executing task matching of the service realization function and establishing a task set, wherein each task in the task set is provided with a task grade identifier; the test scheme establishing unit is used for configuring a test scheme library through big data, carrying out scheme matching of the test scheme library by the task set, and establishing a test scheme set; the service test execution unit is used for configuring the monitoring node of the service component based on the task set and executing the service test of the service to be tested through the test scheme set; the monitoring data calling unit is used for acquiring monitoring data of the monitoring node, wherein the monitoring data has a corresponding relation with the testing scheme set; and the test evaluation execution unit is used for carrying out coupling automation test evaluation by the monitoring data, the task grade identification and the task execution data to generate a test evaluation result.
One or more technical schemes provided by the application have at least the following technical effects or advantages:
the method provided by the embodiment of the application completes data interaction by establishing service communication with the service to be tested and using the service communication, and establishes a service data set according to the data interaction result, wherein the service data set comprises a service component and a service function corresponding to the service component; inputting the realization service function into a task execution network, executing task matching of the realization service function, and establishing a task set, wherein each task in the task set is provided with a task grade identification; configuring a test scheme library through big data, carrying out scheme matching of the test scheme library by using the task set, and establishing a test scheme set; configuring a monitoring node of a service component based on the task set, and executing service test of the service to be tested through the test scheme set; acquiring monitoring data of a monitoring node, wherein the monitoring data has a corresponding relation with a testing scheme set; and carrying out coupling automation test evaluation by the monitoring data, the task grade identification and the task execution data to generate a test evaluation result. The technical effect of obtaining the coupling degree of the unspecified WEB service with high reliability is achieved, and the technical effect of providing guidance and supporting reference for system design optimization iteration and module reconstruction is indirectly achieved.
Drawings
Fig. 1 is a schematic flow chart of a low-coupling WEB service automation test method provided by the application.
Fig. 2 is a schematic flow chart of task set establishment in the low-coupling WEB service automation test method provided by the application.
Fig. 3 is a schematic structural diagram of an automated testing system for low-coupling WEB services according to the present application.
Reference numerals illustrate: the system comprises a service data integration unit 1, a task matching execution unit 2, a test scheme establishment unit 3, a service test execution unit 4, a monitoring data calling unit 5 and a test evaluation execution unit 6.
Detailed Description
The application provides a low-coupling WEB service automatic test method, which is used for solving the technical problems that in the prior art, the coupling state test of the WEB service depends on manpower, the accuracy of a coupling degree test result is low, and the iterative optimization reference value for the WEB service is weak. The technical effect of obtaining the coupling degree of the unspecified WEB service with high reliability is achieved, and the technical effect of providing guidance and supporting reference for system design optimization iteration and module reconstruction is indirectly achieved.
The technical scheme of the invention accords with related regulations on data acquisition, storage, use, processing and the like.
In the following, the technical solutions of the present invention will be clearly and completely described with reference to the accompanying drawings, and it should be understood that the described embodiments are only some embodiments of the present invention, but not all embodiments of the present invention, and that the present invention is not limited by the exemplary embodiments described herein. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention. It should be further noted that, for convenience of description, only some, but not all of the drawings related to the present invention are shown.
Example 1
As shown in fig. 1, the present application provides a method for automatically testing low-coupling WEB services, which includes:
A100, establishing service communication with the service to be tested, completing data interaction by the service communication, and establishing a service data set according to the data interaction result, wherein the service data set comprises a service component and a service function corresponding to the service component.
Specifically, it should be understood that the WEB service is an internet-based software system, and cross-platform and cross-language data exchange and function call between different application programs are implemented through a standardized network protocol, and in this embodiment, the service to be tested is a low-coupling WEB service of an unspecified type.
The low-coupling WEB service automatic test method is applied to a low-coupling WEB service automatic test system, and the premise of executing test on the service to be tested is that the low-coupling WEB service automatic test system is established to communicate with the service of the service to be tested so as to ensure that effective communication can be carried out between the test system and the service to be tested, so that the test system sends a request and receives a response to the service to be tested based on the effective communication, the data exchange process is completed, and a data interaction result is obtained.
And further, a service data set is constructed according to the data interaction result, wherein the service data set comprises service components and corresponding service realization functions, the service components represent different modules or functional units in the service to be tested, and the service realization functions refer to a plurality of specific functions provided by the service components. By establishing the service data set, the method can be used for testing each component of the service to be tested later and verifying whether the function of the component is correct and meets the expectations, and the function of the service component is used for reversely pushing and judging whether the WEB service to be tested is abnormal.
And A200, inputting the realization service function into a task execution network, executing task matching of the realization service function, and establishing a task set, wherein each task in the task set is provided with a task grade identification.
In one embodiment, as shown in fig. 2, the method step a200 provided in the present application further includes:
a210, acquiring a test precision requirement, and configuring granularity constraint according to the test precision requirement.
A220, initializing network parameters of the task execution network through the granularity constraint.
A230, the task execution network after the initialization of the input parameters of the service function is realized, and task matching is completed.
In particular, it should be understood that one service component generally corresponds to one service function, but such a service function may perform a variety of tasks, for example, the service function corresponding to a mail service component is sending mail, but within this mail service component, a variety of different tasks may be implemented, such as sending plain text mail, sending mail with attachments, sending mail in HTML format.
Based on the above, in this embodiment, all service functions corresponding to the multiple sample service components of the same type of the service to be tested and all service task sets corresponding to all service functions are obtained interactively, so as to obtain the multiple groups of service component-service function-service task sets which necessarily include the service components of the service to be tested, and the multiple groups of service component-service function-service task sets are stored in an associated manner based on a knowledge graph, so as to complete the pre-construction of the task execution network.
The test precision requirement refers to the test calling quantity of the service tasks of each service component, for example, the test precision requirement is 3, which indicates that as long as the test result of 3 service tasks in a plurality of service tasks of the service component is that the service tasks can be normally executed, all the service tasks of the service component can be normally executed, and the service component is free from abnormality.
The test user is interacted with the embodiment to obtain the test precision requirement input by the test user, the service task test quantity in the test precision requirement is further used as the granularity constraint, the granularity constraint is used as the call quantity constraint for carrying out service task random call on the task execution network subsequently, and the initialization of the task execution network is completed.
And inputting the K service functions for realizing the service functions one by one into the initialized task execution network traversal execution task matching to obtain K service task sets corresponding to the K service functions, further carrying out service task call of corresponding quantity from the K service task sets based on granularity constraint to obtain K random service task sets, wherein the obtained K random service task sets form the task set.
Meanwhile, it should be understood that the service to be tested in this embodiment is a low-coupling WEB service, the dependency relationship between the modules in the service is weak, and the modules are independent and decoupled, when the complexity of a service task is high, more modules may be required to cooperate to complete the task, in this case, the coupling is completely avoided, which may cause the system to be too dispersed and complicated, and difficult to manage and maintain, so that the coupling is acceptable to a certain extent when facing the complex task.
Thus, in this embodiment, each task in the task set carries a task level identifier, and the higher the task level, the higher the representative task complexity, and the higher the allowable coupling.
The embodiment realizes the technical effects of quickly matching and obtaining the task set for testing whether the service to be tested is abnormal or not by constructing the task execution network and setting granularity.
A300, configuring a test scheme library through big data, carrying out scheme matching of the test scheme library by using the task set, and establishing a test scheme set.
Specifically, it should be understood that the purpose of testing a service task is to determine whether the functions and performances of the service task meet expectations, and specifically, test cases (test schemes) are adopted for testing the service task, where the test cases are composed of test inputs, operation steps and expected outputs.
In this embodiment, test cases of all test tasks of all test task sets in the task execution network are obtained based on big data acquisition, mapping relations between a plurality of service tasks and the test cases are obtained, and the test scheme library is constructed and generated based on the mapping relations. And inputting each service task in the task set into a test scheme library, traversing and determining a corresponding test case, and constructing and obtaining a test scheme set mapped to the task set.
A400, configuring monitoring nodes of the service component based on the task set, and executing service test of the service to be tested through the test scheme set.
Specifically, the monitoring node is used for recording process data acquisition of the service components in the process of executing the service tasks based on the test scheme (test case), in this embodiment, the monitoring node is arranged for each service component according to the data characteristic of the test scheme, and the monitoring node is preferably used for data acquisition of the whole process of executing the test scheme.
After setting the monitoring nodes for the service components, a plurality of monitoring nodes corresponding to a plurality of service components in realizing the service function are obtained.
And executing service test on the service to be tested through the test scheme set to obtain a plurality of monitoring data sets of a plurality of monitoring nodes corresponding to the plurality of service components. It should be understood that the monitoring data set has a mapping relationship with the testing scheme set, and each monitoring node correspondingly records monitoring data in the executing process of each testing scheme.
A500, acquiring monitoring data of the monitoring node, wherein the monitoring data has a corresponding relation with the test scheme set.
In one embodiment, the method steps provided by the application further comprise:
A510, extracting the monitoring data and establishing a component function verification data set.
And A520, performing independent execution evaluation on service components in the service to be tested through the component function verification data set.
And A530, extracting common abnormal characteristics through independently executing the evaluation result, and completing the abnormal early warning management by using the common abnormal characteristic extraction result.
Specifically, in this embodiment, the monitoring node is configured to perform data acquisition on service function output of a service component, where the service function output obtained by specific acquisition is the component function verification data.
And extracting monitoring data from the monitoring nodes corresponding to the service components to obtain a plurality of component function verification data sets of the service components, wherein each component function data set comprises component function data of a task execution output result of a plurality of service tasks of the corresponding service components by adopting a corresponding test scheme (test case).
Based on the test scheme (test case) corresponding to each service function, the implementation comprises test input, operation steps and expected output, and judges whether the service function is abnormal or not according to whether the expected input is consistent with the actual output of the service function.
And carrying out actual output calling of the service function based on a plurality of component function verification data sets of the plurality of service components to obtain a plurality of service function outputs of each service component, and further carrying out consistency comparison on the plurality of service function outputs of each service component and the expected outputs of the corresponding test schemes.
And if and only if the actual output and the expected output of the plurality of service functions of the service component are consistent, the service component is considered to have normal functions, and based on the method, the service component in the service to be tested is independently executed and evaluated through the component function verification data set, whether each service component has abnormal independent evaluation is obtained, and a plurality of independent execution evaluation results of the plurality of service components of the service to be tested are obtained.
And calling the M abnormal service components from the independent execution evaluation results, and further interactively obtaining the calling condition of the function modules in the service to be tested in the execution service of the M service components to obtain M groups of function modules.
And (3) acquiring one or more general functional modules by aggregating the M groups of functional modules, taking the general functional modules as the extracted common abnormal characteristics, and finishing abnormal early warning management according to the extraction result of the common abnormal characteristics to prompt the operation and maintenance processing of the functional modules with abnormal functions in the service to be tested.
According to the embodiment, the service component is subjected to the abnormality early warning treatment, so that the preposed judgment of whether the test case is abnormal or not is carried out before the coupling analysis of the service to be tested is carried out, and the technical effect of low reliability of the coupling evaluation result caused by the coupling evaluation carried out when the test case is in a fault abnormal state is avoided.
A600, carrying out coupling automation test evaluation by using the monitoring data, the task grade identification and the task execution data to generate a test evaluation result.
In one embodiment, the method steps provided by the application further comprise:
A611, establishing a task monitoring edge node, wherein the task monitoring edge node is constructed based on a test scheme set.
And A612, in the service test process of executing the test scheme set, activating the corresponding task monitoring edge node through the called test scheme.
And A613, executing task data acquisition by the task monitoring edge node to generate the task execution data.
In one embodiment, the method steps provided by the application further comprise:
And A621, inputting the monitoring data and the task grade identification into a first processing sub-network, and carrying out data alignment processing on the monitoring data and the task grade identification before inputting the monitoring data and the task grade identification into the first processing sub-network.
And A622, after the first processing sub-network receives the task grade identification and the monitoring data, configuring and matching evaluation parameters according to the task grade identification.
A623, performing frequency evaluation on the monitoring data through the matching evaluation parameters, and generating a first evaluation result.
And A624, completing coupling automation test evaluation through the first evaluation result and the task execution data.
In one embodiment, the method steps provided by the application further comprise:
And A631, inputting the task grade identification and the task execution data into a second processing sub-network, wherein before the task execution data and the task grade identification are input into the second processing sub-network, the task execution data and the task grade identification are subjected to data alignment processing.
And A632, performing the completion state evaluation of the task execution data at the current task level mark through the second processing sub-network, and generating a second evaluation result.
And A633, performing dependency influence analysis on the first evaluation result and the second evaluation result, and completing coupling automation test evaluation through all the dependency influence analysis results.
In one embodiment, the method steps provided by the application further comprise:
and A641, extracting execution time data of the task execution data through a time sequence channel, wherein the time sequence channel is an inclusion channel of the second processing sub-network.
And A642, evaluating the execution time of the execution time data and the task grade identification by the time sequence channel to generate auxiliary data.
And A643, compensating the second evaluation result through the auxiliary data to obtain a third evaluation result.
And A644, carrying out dependence influence analysis by using the third evaluation result and the first evaluation result, and completing coupling automation test evaluation by using all dependence influence analysis results.
Specifically, in this embodiment, the monitoring node is configured to perform data acquisition and recording on service function output of the service component, to obtain component function data; the task monitoring edge node is used for carrying out data acquisition record of a task execution process on a plurality of service tasks of the service component by adopting a corresponding test scheme (test case) to obtain task execution data.
It should be understood that the specific module calling conditions and module calling sequences in the service to be tested are different when the same service component executes different service tasks, so that the task monitoring edge nodes corresponding to the service tasks are distributed and positioned according to the test schemes, a plurality of task monitoring edge nodes corresponding to all the test schemes in the test scheme set are obtained, and test data covering the execution process of all the test schemes in the test scheme set are obtained.
And in the service test process of executing the test scheme set, activating the corresponding task monitoring edge node to execute task data acquisition through the called test scheme, and generating the task execution data of each service task execution process.
In this embodiment, the monitoring data, the task level identifier, and the task execution data are used to perform coupling automation test and evaluation, and the test and evaluation result representing the module coupling degree of the service to be tested is generated.
The monitoring node is used for acquiring service task output results and acquiring component function data, and is also used for acquiring and recording inter-module data calling conditions of modules used in the service task processing process. The monitoring data thus includes, in addition to the component functionality data set, a plurality of module call records for each service component as it performs a plurality of service tasks.
When a certain service task of a certain service component is tested based on a test scheme, a module call record of the service task is obtained based on a module call condition record of a test scheme execution process performed by a monitoring node, if a module is A, B, C, the module call record may be that A calls B and C, B does not call other modules, and C calls B.
In this embodiment, the first processing sub-network for performing module coupling degree analysis in the WEB service based on the monitoring data is pre-constructed, and the construction process of the first processing sub-network is as follows:
And performing task level aggregation based on the task level identifiers of all service tasks to obtain a plurality of task levels, setting a plurality of task processing weights for the plurality of task levels, and setting the addition result of the plurality of task weights to be 1.
And carrying out weighted calculation on the product of the number of module calls and the number of times of call among the total modules and task processing weights to serve as standard evaluation parameters, further combining the standard evaluation parameters and the task processing weights to obtain a plurality of groups of task grade-matching evaluation parameters, and constructing and obtaining the first processing sub-network based on the plurality of groups of task grade-grade evaluation parameters.
And constructing a mapping relation between the monitoring data and the task grade identification based on the service task, and completing data alignment processing of the monitoring data and the task grade identification to obtain a plurality of groups of monitoring data-task grade identifications of a plurality of service tasks. And further, extracting module calling records from the plurality of groups of monitoring data-task grade identifiers to obtain a plurality of groups of module calling records-task grade identifiers.
And obtaining a first group of module call records based on the random call of the multi-group module call records and the task grade identification, inputting the first group of module call records and the task grade identification into a first processing sub-network, and configuring and matching evaluation parameters in the first processing sub-network according to the task grade identification.
And carrying out module calling quantity and total calling frequency multiplication calculation of the first module calling record through the matching evaluation parameters, and combining task processing weights to calculate to obtain a first service evaluation result, thereby completing the frequency evaluation of the first group of module calling record-task grade identification.
And similarly, the same method is adopted to evaluate the frequency of the multi-group monitoring data-task grade identification of the plurality of service tasks, a plurality of service evaluation results of the plurality of service tasks are obtained, the first evaluation result is formed, and it is understood that the first evaluation result evaluates the coupling degree of the service to be tested from the module calling number and the inter-module data calling frequency dimension of the service task executing process.
Further, in this embodiment, detection and evaluation are performed on task execution data, and it is determined whether there is a data loss damage in the service task execution process, where the second processing sub-network includes a state evaluation channel and a timing channel, and an output end of the state evaluation channel is connected to an input end of the timing channel.
The state evaluation channel is constructed based on the prior art, and can determine the data loss rate of the service task execution process by checking log records, error codes or abnormal stack tracking in the task execution data. And setting a plurality of task processing weights for a plurality of task levels in the first processing sub-network, and directly transferring the task processing weights to the state evaluation channel.
In this embodiment, a mapping relationship between the task execution data and the task class identifier is constructed based on a service task, and data alignment processing is completed, so as to obtain multiple sets of task class identifier-task execution data corresponding to multiple service tasks.
And randomly calling based on a plurality of groups of task grade identifiers-task execution data to obtain a first group of task grade identifiers-task execution data, inputting the first group of task grade identifiers-task execution data into a state evaluation channel of a second processing sub-network, calculating to obtain a data damage rate, further carrying out product calculation on task processing weight calling and the data damage rate according to the first task grade identifiers, and taking the calculation result as a monitoring evaluation result of the first group of task grade identifiers-task execution data.
And so on, obtaining a plurality of monitoring evaluation results of a plurality of groups of task grade identification-task execution data, wherein the plurality of execution evaluation results form the second evaluation result.
The present embodiment further describes the construction and application of a timing channel for extracting execution time data of the task execution data, where the present embodiment sets a plurality of task execution time constraints for a plurality of task classes in addition to a plurality of task processing weights.
Synchronizing the execution time constraints of a plurality of tasks to a plurality of execution time deviation calculation sub-channels of the time sequence channel to complete the construction of the time sequence channel, wherein the data processing process of the time sequence channel is as follows:
And performing execution time data call from the task execution data of the service tasks through the time sequence channel to obtain a plurality of execution time data-task grade identifiers.
Synchronizing the execution time data to the corresponding execution time deviation calculating sub-channel based on the task grade identification, and calculating the execution time deviation as a plurality of auxiliary data of a plurality of service tasks in combination with task execution time constraint in the sub-channel.
And carrying out association storage on the second evaluation result and the auxiliary data based on the service tasks to obtain a plurality of groups of auxiliary data-execution evaluation results mapped to a plurality of service tasks, multiplying the auxiliary data in the groups by the execution evaluation results, and finishing compensation of the second evaluation result by the auxiliary data to obtain the third evaluation result formed by a plurality of compensation evaluation results of the plurality of service tasks.
And carrying out associated storage on the third evaluation result and the first evaluation result based on the service tasks to obtain a plurality of groups of compensation evaluation result-monitoring evaluation results of a plurality of service tasks, presetting a first weight and a second weight, and carrying out weighted calculation on the plurality of groups of compensation evaluation result-monitoring evaluation results based on the first weight and the second weight to serve as a service coupling degree index of one service task.
And combining the service coupling indexes of the service tasks according to the corresponding service components based on the characteristic that the service tasks are executed by one service component, so as to obtain a plurality of groups of service coupling indexes of the service components of the service to be tested.
And carrying out average value calculation on a plurality of groups of service coupling degree indexes to obtain component coupling degree indexes of a plurality of service components, carrying out serialization processing on the component coupling degree indexes to obtain the maximum component coupling degree index as an evaluation result of coupling automation test evaluation on the service to be tested, wherein the value reflects the module coupling degree of the whole service to be tested, and can provide guidance and support for subsequent system iteration and upgrading.
The embodiment achieves the technical effect of obtaining the coupling degree of the unspecified WEB service with high reliability, and indirectly achieves the technical effect of providing guidance and support reference for system design optimization iteration and module reconstruction.
Example two
Based on the same inventive concept as the low-coupling WEB service automation test method in the foregoing embodiment, as shown in fig. 3, the present application provides a low-coupling WEB service automation test system, where the system includes:
The service data integration unit 1 is used for establishing service communication with the service to be tested, completing data interaction with the service communication, and establishing a service data set according to a data interaction result, wherein the service data set comprises a service component and a service function corresponding to the service component.
And the task matching execution unit 2 is used for inputting the service realization function into a task execution network, executing task matching of the service realization function and establishing a task set, wherein each task in the task set is provided with a task grade identifier.
And the test scheme establishing unit 3 is used for configuring a test scheme library through big data, carrying out scheme matching of the test scheme library by the task set, and establishing a test scheme set.
And the service test execution unit 4 is used for configuring the monitoring node of the service component based on the task set and executing the service test of the service to be tested through the test scheme set.
And the monitoring data calling unit 5 is used for acquiring the monitoring data of the monitoring node, wherein the monitoring data has a corresponding relation with the testing scheme set.
And the test evaluation execution unit 6 is used for carrying out coupling automation test evaluation by the monitoring data, the task grade identification and the task execution data to generate a test evaluation result.
In one embodiment, the test evaluation execution unit 6 further includes:
And establishing a task monitoring edge node, wherein the task monitoring edge node is constructed based on the test scheme set.
And in the service test process of executing the test scheme set, activating the corresponding task monitoring edge node through the called test scheme.
And executing task data acquisition by the task monitoring edge node to generate the task execution data.
In one embodiment, the test evaluation execution unit 6 further includes:
And inputting the monitoring data and the task grade identification into a first processing sub-network, wherein before the monitoring data and the task grade identification are input into the first processing sub-network, the monitoring data and the task grade identification are subjected to data alignment processing.
And after the first processing sub-network receives the task grade identification and the monitoring data, configuring matching evaluation parameters according to the task grade identification.
And performing frequency evaluation on the monitoring data through the matching evaluation parameters to generate a first evaluation result.
And completing coupling automation test evaluation through the first evaluation result and the task execution data.
In one embodiment, the test evaluation execution unit 6 further includes:
and inputting the task grade identification and the task execution data into a second processing sub-network, wherein before the task execution data and the task grade identification are input into the second processing sub-network, the task execution data and the task grade identification are subjected to data alignment processing.
And executing the completion state evaluation of the task execution data at the current task level mark through the second processing sub-network, and generating a second evaluation result.
And carrying out dependence influence analysis on the first evaluation result and the second evaluation result, and completing coupling automation test evaluation through all dependence influence analysis results.
In one embodiment, the test evaluation execution unit 6 further includes:
and extracting execution time data of the task execution data through a time sequence channel, wherein the time sequence channel is an included channel of the second processing sub-network.
And evaluating the execution time of the execution time data and the task grade identification by the time sequence channel to generate auxiliary data.
And compensating the second evaluation result through the auxiliary data to obtain a third evaluation result.
And carrying out dependence influence analysis by using the third evaluation result and the first evaluation result, and completing coupling automation test evaluation by using all dependence influence analysis results.
In one embodiment, the monitoring data calling unit 5 further comprises:
and extracting the monitoring data and establishing a component function verification data set.
And performing independent execution evaluation on the service components in the service to be tested through the component function verification data set.
And carrying out common abnormal feature extraction through independently executing the evaluation result, and completing abnormal early warning management by using the common abnormal feature extraction result.
In one embodiment, the task matching execution unit 2 further includes:
and acquiring a test precision requirement, and configuring granularity constraint by the test precision requirement.
And initializing network parameters of the task execution network through the granularity constraint.
And the task execution network after the initialization of the input parameters of the service function is realized, so that task matching is completed.
Any of the methods or steps described above may be stored as computer instructions or programs in various non-limiting types of computer memories, and identified by various non-limiting types of computer processors, thereby implementing any of the methods or steps described above.
Based on the above-mentioned embodiments of the present invention, any improvements and modifications to the present invention without departing from the principles of the present invention should fall within the scope of the present invention.
Claims (6)
1. An automated testing method for low-coupling WEB services, the method comprising:
Establishing service communication with a service to be tested, completing data interaction by the service communication, and establishing a service data set according to a data interaction result, wherein the service data set comprises a service component and a service function corresponding to the service component;
Inputting the realization service function into a task execution network, executing task matching of the realization service function, and establishing a task set, wherein each task in the task set is provided with a task grade identification;
configuring a test scheme library through big data, carrying out scheme matching of the test scheme library by using the task set, and establishing a test scheme set;
Configuring a monitoring node of a service component based on the task set, and executing service test of the service to be tested through the test scheme set;
Acquiring monitoring data of a monitoring node, wherein the monitoring data has a corresponding relation with a testing scheme set;
performing coupling automatic test evaluation by using the task execution data, the monitoring data and the task grade identification to generate a test evaluation result;
The generating of the task execution data comprises the following steps:
establishing a task monitoring edge node, wherein the task monitoring edge node is constructed based on a test scheme set;
in the service test process of executing the test scheme set, activating a corresponding task monitoring edge node through the called test scheme;
executing task data acquisition by using a task monitoring edge node to generate task execution data;
The coupling automation test evaluation comprises the following steps:
Inputting the monitoring data and the task grade identification into a first processing sub-network, and carrying out data alignment processing on the monitoring data and the task grade identification before inputting the monitoring data and the task grade identification into the first processing sub-network;
after the first processing sub-network receives the task grade identification and the monitoring data, matching evaluation parameters are configured according to the task grade identification;
Performing frequency evaluation on the monitoring data through the matching evaluation parameters to generate a first evaluation result;
And completing coupling automation test evaluation through the first evaluation result and the task execution data.
2. The method of claim 1, wherein the method further comprises:
Inputting the task grade identification and task execution data into a second processing sub-network, and before inputting the task grade identification and the task execution data into the second processing sub-network, carrying out data alignment processing on the task execution data and the task grade identification;
executing the completion state evaluation of the task execution data at the current task level mark through the second processing sub-network to generate a second evaluation result;
and carrying out dependence influence analysis on the first evaluation result and the second evaluation result, and completing coupling automation test evaluation through all dependence influence analysis results.
3. The method of claim 2, wherein the method further comprises:
Extracting execution time data of the task execution data through a time sequence channel, wherein the time sequence channel is an included channel of the second processing sub-network;
Performing execution time evaluation on the execution time data and the task grade identification by using the time sequence channel to generate auxiliary data;
compensating the second evaluation result through the auxiliary data to obtain a third evaluation result;
And carrying out dependence influence analysis by using the third evaluation result and the first evaluation result, and completing coupling automation test evaluation by using all dependence influence analysis results.
4. The method of claim 1, wherein the method further comprises:
Extracting the monitoring data and establishing a component function verification data set;
performing independent execution evaluation on service components in the service to be tested through the component function verification data set;
and carrying out common abnormal feature extraction through independently executing the evaluation result, and completing abnormal early warning management by using the common abnormal feature extraction result.
5. The method of claim 1, wherein inputting the implementation service function into a task execution network, performing task matching of the implementation service function, and establishing a task set, further comprises:
acquiring a test precision requirement, and configuring granularity constraint according to the test precision requirement;
initializing network parameters of a task execution network through the granularity constraint;
And the task execution network after the initialization of the input parameters of the service function is realized, so that task matching is completed.
6. A low-coupling WEB services automated testing system, the system comprising:
The service data integration unit is used for establishing service communication with the service to be tested, completing data interaction by the service communication, and establishing a service data set according to a data interaction result, wherein the service data set comprises a service component and a service function corresponding to the service component;
The task matching execution unit is used for inputting the service realization function into a task execution network, executing task matching of the service realization function and establishing a task set, wherein each task in the task set is provided with a task grade identifier;
the test scheme establishing unit is used for configuring a test scheme library through big data, carrying out scheme matching of the test scheme library by the task set, and establishing a test scheme set;
The service test execution unit is used for configuring the monitoring node of the service component based on the task set and executing the service test of the service to be tested through the test scheme set;
the monitoring data calling unit is used for acquiring monitoring data of the monitoring node, wherein the monitoring data has a corresponding relation with the testing scheme set;
The test evaluation execution unit is used for carrying out coupling automation test evaluation by using the task execution data, the monitoring data and the task grade identification to generate a test evaluation result;
the test evaluation execution unit includes:
establishing a task monitoring edge node, wherein the task monitoring edge node is constructed based on a test scheme set;
in the service test process of executing the test scheme set, activating a corresponding task monitoring edge node through the called test scheme;
executing task data acquisition by using a task monitoring edge node to generate task execution data;
the test evaluation execution unit includes:
Inputting the monitoring data and the task grade identification into a first processing sub-network, and carrying out data alignment processing on the monitoring data and the task grade identification before inputting the monitoring data and the task grade identification into the first processing sub-network;
after the first processing sub-network receives the task grade identification and the monitoring data, matching evaluation parameters are configured according to the task grade identification;
Performing frequency evaluation on the monitoring data through the matching evaluation parameters to generate a first evaluation result;
And completing coupling automation test evaluation through the first evaluation result and the task execution data.
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