CN104899141B - A kind of test cases selection and extending method of network-oriented application system - Google Patents
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Abstract
The present invention relates to a kind of test cases selection and extending method of network-oriented application system, by being parsed to test use cases, de-redundancyization processing, step is trained etc. to test data using machine learning method, finally using new test use cases of the testing standards of TTCN 3 generation with higher fault-finding efficiency.The problem of behavioral test and test data be tightly coupled in the problem of method of the present invention solves the problem of test case has bulk redundancy, Reuse of Test Cases among regression test, test case and test case is for lifting network application system performance capability deficiency.
Description
Technical field
The present invention relates to net application technology field, and in particular to a kind of test cases selection of network-oriented application system
With extending method.
Background technology
With continuing to develop for network application system, exist substantial amounts of be directed to lifting its feature, stably both at home and abroad
The research of the measuring technology of performance in terms of property, reliability.Have and testing script technique automatically generated by recording/replaying technology,
And model-driven testing technology.Wherein model-driven testing technology is increasingly becoming the main aspect of research, including：Using BPEL
Specification describes business process model, by extending the test case meta-model of U2TP specifications and TTCN-3 language definitions, in order to prop up
The conversion of two models is held, description service interaction and the business process meta-model of control logic are defined based on U2TP activity diagrams.
Operation flow test modeling platform is developed using Eclipse platform, support tester to operation flow and test case can
Depending on changing modeling, realize that business process model, to the automatic conversion of test case model, realizes the automation generation of test script.
In addition to based on UTP, test case can be also generated using UML extended capability extensible SQL.C.Crichton,
A.Cavarra and J.Davie are exactly in this way.They create two kinds of extensions, and one is by extension class figure, object
Scheme to describe the testing attribute of system under test (SUT) with state diagram.Another extension be by object diagram and state diagram be used for test is described
Target.
F.Bouquet et al. proposes model-based testing method, and this method is based on uml diagram, such as class figure, object diagram and shape
State figure, and OCL expression formulas automatically generate test case.
One in model above driving method of testing is mainly characterized by being based on system model, is built by defining test design
Mould language, carries out Design of Test System, and by certain test philosophy, generates test case.It is common among these methods
The subject matter of presence has：The test case of generation has diversity, the fault discovery lack of targeted for being tested test system,
The test case redundancy that the Space Explosion problem of test use cases is produced, the problems such as test data is insufficient.
The content of the invention
In view of above-mentioned analysis, the present invention is intended to provide test cases selection and the expansion of a kind of network-oriented application system
Method, the test case to solve to generate in the prior art has diversity, and test use cases have redundancy, for tested
The fault discovery lack of targeted of system, and test data it is insufficient the problems such as.
The purpose of the present invention is mainly achieved through the following technical solutions：
A kind of test cases selection and extending method of network-oriented application system, this method comprise the following steps：
Step 1, the test use cases data for reading from database tested network application system；
Step 2, the test use cases data in step 1 are sent in resolution server parsed, generation test system
Unite model, and be transferred to display device and presented in patterned form；Wherein, test system model includes：Behavioral test model,
Test data model and Test configurations model；
Step 3, the Behavioral test model in the test system model that generation is parsed in step 2 is sent to de-redundancy service
De-redundancy processing is carried out in device；
Step 4, the test data model in the test system model that generation is parsed in step 2 is sent to training server
In, test data acquisition is first carried out, then test data is trained using machine learning method, so as to generate new test
Data；
Step 5, the new survey that will be obtained in the Behavioral test model and step 4 after the de-redundancy obtained in step 3
Data are tried, with reference to the Test configurations model of the test system model of step 2, new test use cases generation server are sent collectively to
In, and then using new test use cases of the TTCN-3 testing standards generation with higher fault-finding efficiency.
Further, the test use cases described in step 1 are test script.
Further, the resolving described in step 2 is mainly realized by following three step：
(1) data are extracted：The metadata of source file is obtained by analysis either statically or dynamically；
(2) model is built：The metadata of extraction is classified and stored, metadata is carried out using predefined model
Restructuring, the structure of implementation model；
(3) information is showed：After the model built is obtained, model information is carried out at abstract by meta-model technology
Reason, and showed with patterned form.
Further, step 3 is specially：According to the test system and test behavior model parsed, using Similarity Measure
Formula, the similarity between difference contrastive test behavior；Using genetic search algorithm, whole Behavioral test model is optimized
Search, so that the minimum Behavioral test model set of test target can be reached by drawing.
Further, the calculation formula of the similarity is as follows：
SimilarityFunction (i, j)=nit/avg (| i |, | j |)
Wherein, nit represents the identical operand between two behavioral tests, avg (| i |, | j |) represent that two tests are used
The average operation number length of example.
Further, the utilization machine learning method described in step 4 is trained specially to test data：Obtaining
After test data, by the test thinking of simulation test personnel, original test data is trained, learn and adjusted, from
And generate new test data.
Further, step 5 is specially：By setting up between test system model and TTCN-3 test system models
Mapping, realizes test system model to the conversion of TTCN-3 abstract test cases, and then generates the executable test cases of TTCN-3
Script, by TTCN-3 test execution platforms, realizes the automatic test to network application system.
The present invention has the beneficial effect that：
The invention provides a kind of test cases selection and extending method of network-oriented application system, by using test
Example collection is parsed, de-redundancyization is handled, test data is trained using machine learning method and surveyed using TTCN-3
The technological means such as new test use cases of the test-object quasi- generation with higher fault-finding efficiency, solve following technical problem：
1st, the problem of test case has bulk redundancy is solved；
2nd, the problem of solving the Reuse of Test Cases among regression test；
3rd, behavioral test and the tightly coupled problem of test data in test case are solved；
4th, the problem of test case is for lifting network application system performance capability deficiency is solved.
Other features and advantages of the present invention will be illustrated in the following description, also, the partial change from specification
Obtain it is clear that or being understood by implementing the present invention.The purpose of the present invention and other advantages can be by the explanations write
Specifically noted structure is realized and obtained in book, claims and accompanying drawing.
Brief description of the drawings
Accompanying drawing is only used for showing the purpose of specific embodiment, and is not considered as limitation of the present invention, in whole accompanying drawing
In, identical reference symbol represents identical part.
Fig. 1 is flow chart of the method for the present invention；
Fig. 2 is test data model schematic of the invention；
Fig. 3 is Test configurations model schematic diagram of the invention；
Fig. 4 is Behavioral test model schematic diagram of the invention；
Fig. 5 is test data model analyzing flow chart of the invention；
Fig. 6 generates Optimizing Flow figure for the test data self study of the present invention.
Embodiment
The preferred embodiments of the present invention are specifically described below in conjunction with the accompanying drawings, wherein, accompanying drawing constitutes the application part, and
It is used for the principle for explaining the present invention together with embodiments of the present invention.
A kind of test cases selection and extending method of network-oriented application system, this method comprise the following steps：
Step 1, the test use cases for reading from database tested network application system.
Wherein, the test use cases are test script.Test script comprising system operatio Perform sequence, operating parameter with
And system configuration information etc..
Step 2, the test use cases in step 1 are sent in resolution server parsed, generate test system mould
Type, and presented in patterned form；Wherein, test system model includes：Behavioral test model, test data model and test
Allocation models.
According to test correlation theory and network application system test feature, test system model is set up, for from input
Test case, which is concentrated, obtains test key message, and test system is modeled.
(1) test data model
One group of concept of test data model definition to describe test data, mainly including data pool (DataPool),
Data divide the various complicated data structure definitions such as (DataPartition), data instance (DataInstance).
In test data model, UML basic data type (SimpleType) is introduced, enumeration type is further comprises
And record type (Record), and ordered set (RecordOf) and unordered set (SetOf) (Enum).The one of record type
Individual domain (field) one data type of correspondence, can be set by association class (Attribute) ignore this domain (omit) and
Optional (optional) two attributes.The example of data type (DataType) is data instance (DataInstance), fixed
Justice one record type or simple data type or the example of set.Data pool (DataPool) is real comprising multiple data
Example, there is the equivalence class partition (DataPartition) of data template on data pool.Referring specifically to Fig. 2.
(2) Test configurations model
Test configurations model is used for the structure and configuration for describing test suite and system under test (SUT) in testing.Test configurations mould
Type is the description to test system static state composition structure.Test configurations model mainly includes：Test suite
(TestComponent), the connection between test interface (TestInterface), test system
(TestInterfaceConnection), system under test (SUT) (SUT).Add test interface type (TestInterfaceType)
The data type that test interface input and output allow is defined, a test interface type can be quoted by multiple test interfaces.
Timer (Timer) can be defined in test suite, timer can be cited at test scene (TestScenario).Tool
Body is referring to Fig. 3.
(3) Behavioral test model
Behavioral test model is used to describe the various actions in test case.Behavioral test model definition includes timer
Action (Start Timer Action and Stop Timer Action), massage stimulus (StimuliAction), message response
And test result classification (Verdict) etc., in addition to do action (WhileAction (ResponseEvaluateAction)
And ForAction) and if action (IfAction and ForAction) and branch operation (AltAction), these elements
Inherited from movable block (ActionBlock), movable block is inherited from abstract action (Action).Test case (TestCase) after
Hold self-test scene (TestScenario).The input data needed wherein defined in massage stimulus and message response and expection
Response data type and name information.Referring specifically to Fig. 4.
By test system model, field one by one is carried out to test case and is parsed, test mould is extracted from test case
Type, is stored as test data model, Behavioral test model and Test configurations model respectively.
The resolving can be divided into three parts, and Part I is to identify associated components, Part II to component it
Between dependence analyzed, Part III is the abstract expression form for setting up system same level or more high-level.Mainly
Realized by following three step：
(1) data are extracted：Data now are undressed, and the member of source file is obtained by analysis either statically or dynamically
Data；Wherein described metadata is contained in the data such as system operatio Perform sequence, operating parameter and system configuration information.
(2) model is built：The metadata of extraction is classified and stored, metadata is carried out using predefined model
Restructuring, the structure of implementation model；
(3) information is showed：After the model built is obtained, model information is carried out at abstract by meta-model technology
Reason, and showed with patterned form.Meta-model is the one kind " abstract language " defined for descriptive model, is that model is entered
One step is abstract.Meta-model technology is that the relation by the basic constitution element to things, and between element is defined, and is provided
It indicates a kind of technology being modeled to reach to things.
Step 3, the Behavioral test model in the test system model that generation is parsed in step 2 is sent to de-redundancy service
De-redundancy processing is carried out in device.
Further, according to the test system and test behavior model parsed, using calculating formula of similarity, compare respectively
Similarity between behavioral test；Using genetic search algorithm, search is optimized to whole Behavioral test model, so as to draw
The minimum Behavioral test model set of test target can be reached.
The calculation formula of the similarity is as follows：
SimilarityFunction (i, j)=nit/avg (| i |, | j |)
Wherein, nit represents the identical operand between two behavioral tests, avg (| i |, | j |) represent that two tests are used
The average operation number length of example.
By step 3, the redundancy testing use-case among test use cases is eliminated, reduces what is produced by redundancy testing
Test cost, greatlys save testing cost.
Step 4, the test data model in the test system model that generation is parsed in step 2 is sent to training server
Middle progress test data acquisition, and test data is trained using machine learning method, so as to generate new test data.
By parsing test data model file, dtd--data type definition information is obtained, so as to be set up before data storage
The tables of data of corresponding types.As shown in figure 5, the specific step of test data model analyzing is as follows：
First, it is determined that whether selected test system model is test data model, if it is not, then terminating parsed
Journey.
Next, if it is, locking and acquiring domain model files, and circulate acquisition and judge each test data type
Definition：(1) if type definition is basic data type, its relevant information is not preserved, because in the tables of data set up
All basic data types through having pre-defined；(2) if type definition is complex data type, according to the number of its definition
The basic data type included according to structure and the type, sets up Service Data Object model, preserves the dtd--data type definition information.
So circulation preserves the complex data type each defined, until all data types are all with the shape of Service Data Object model
Formula is preserved, for setting up tables of data in database.
After parsing test data model and obtaining the definition information of data type, by test data according to data type
Tables of data is built up in definition, and is stored in database.The each tables of data set up in database corresponds to test data model
Defined in some data type.In order to handle in a uniform manner in Various types of data, the data of the invention based on service object
Be situated between the visit of service (Data Mediator Service) connection and operating database SDO data agents service offer to data source
Ask.Data agent service creates datagram by reading data from back-end data source, is also based on what datagram was done
Change and update the data source.Data agent service can occur with size in a variety of manners, but also can include to XML data
XML intermediaries that source is written and read, the relation intermediary being written and read to the data source based on JDBC, the entity mould according to application definition
Type, even receives XML query and reads and writes the intermediary in various XML and non-XML data source.The number that data agent service support disconnects
According to chart rack structure.
Data access service (Data Access Service, DAS) is used to load a number from a data storage
It is saved according to figure, or by a datagram in a data storage.Function such as an XML DAS is from XML file loading
One datagram is saved into XML file, and a JDBC DAS is then to load or preserve data from relational database
Figure.
Described training step is specially：It is right by the test thinking of simulation test personnel after test data is obtained
Original test data is trained, learns and adjusted, so as to generate new test data.As shown in Figure 6.The training step includes
Two aspects, correspond respectively to two class behaviors of manual testing：
First, the Test data generation algorithm of given cover up rule is met, test of the manual testing according to established rule is corresponded to
Design data behavior.
2nd, the study and adjustment according to test feedback to Test coverage rule, so that new test case is produced, correspondence
Adjustment behavior in manual testing according to test effect to Test data generation rule.
By step 4, the automation generation of test data is realized, Test data generation cost is reduced, and pass through height
The data training of level and learning method, generate the data test of fault-finding higher level, improve testing efficiency.
The new test obtained in Behavioral test model and step 4 after step 5, the de-redundancy for obtaining step 3
Data, with reference to the Test configurations model of the test system model of step 2, are sent to new test use cases generation server in the lump
In, and then using new test use cases of the TTCN-3 testing standards generation with higher fault-finding efficiency.
By setting up the mapping between test system model and TTCN-3 test system models, test system model is realized
To the conversion of TTCN-3 abstract test cases, and then the executable test case scripts of TTCN-3 are generated, held by TTCN-3 tests
Row platform, realizes the automatic test to network application system.
By step 5, the expansion to test use cases is realized, executable test use cases are generated, survey is realized
The automation of examination, has reached the purpose for saving testing cost.
In summary, the embodiments of the invention provide a kind of test cases selection of network-oriented application system and expansion side
Method, by being parsed to test use cases, de-redundancyization processing, is trained using machine learning method to test data
Step, finally using new test use cases of the TTCN-3 testing standards generation with higher fault-finding efficiency.The side of the present invention
The problem of method solves the problem of test case has bulk redundancy, Reuse of Test Cases among regression test, test are used
Behavioral test and the tightly coupled problem of test data and test case are for lifting network application system performance capability not in example
Sufficient the problem of.
It will be understood by those skilled in the art that realizing all or part of flow of above-described embodiment method, meter can be passed through
Calculation machine program instructs the hardware of correlation to complete, and described program can be stored in computer-readable recording medium.Wherein, institute
It is disk, CD, read-only memory or random access memory etc. to state computer-readable recording medium.
The foregoing is only a preferred embodiment of the present invention, but protection scope of the present invention be not limited thereto,
Any one skilled in the art the invention discloses technical scope in, the change or replacement that can be readily occurred in,
It should all be included within the scope of the present invention.
Claims (7)
1. a kind of test cases selection and extending method of network-oriented application system, it is characterised in that this method includes as follows
Step：
Step 1, the test use cases data for reading from database tested network application system；
Step 2, the test use cases data in step 1 are sent in resolution server parsed, generate test system mould
Type, and be transferred to display device and presented in patterned form；Wherein, test system model includes：Behavioral test model, test
Data model and Test configurations model；
Step 3, the Behavioral test model in the test system model that generation is parsed in step 2 is sent in de-redundancy server
Carry out de-redundancy processing；
Step 4, the test data model in the test system model that generation is parsed in step 2 is sent in training server,
Test data acquisition is first carried out, then test data is trained using machine learning method, so as to generate new test number
According to；
Step 5, by the new test number obtained in the Behavioral test model and step 4 after the de-redundancy obtained in step 3
According to, with reference to the Test configurations model of the test system model of step 2, it is sent collectively in new test use cases generation server,
And then using new test use cases of the TTCN-3 testing standards generation with higher fault-finding efficiency.
2. the method as described in claim 1, it is characterised in that the test use cases described in step 1 are test script.
3. the method as described in claim 1, it is characterised in that the resolving described in step 2 mainly passes through following three
Step is realized：
(1) data are extracted：The metadata of source file is obtained by analysis either statically or dynamically；
(2) model is built：The metadata of extraction is classified and stored, metadata is weighed using predefined model
Group, the structure of implementation model；
(3) information is showed：After the model built is obtained, abstract processing is carried out to model information by meta-model technology, and
Showed with patterned form, meta-model technology is that the relation by the basic constitution element to things, and between element is determined
Justice, and provide a kind of technology that its sign is modeled to reach to things.
4. the method as described in claim 1, it is characterised in that step 3 is specially：According in the test system model parsed
Behavioral test model, using calculating formula of similarity, the similarity between contrastive test behavior respectively；Calculated using genetic search
Method, search is optimized to whole Behavioral test model, so that the minimum Behavioral test model of test target can be reached by drawing
Set.
5. method as claimed in claim 4, it is characterised in that the calculation formula of the similarity is as follows：
SimilarityFunction (i, j)=nit/avg (| i |, | j |)
Wherein, nit represents the identical operand between two behavioral tests, avg (| i |, | j |) represent two test cases
Average operation number length.
6. the method as any one of claim 1-5, it is characterised in that the utilization machine learning side described in step 4
Method is trained specially to test data：After test data is obtained, by the test thinking of simulation test personnel, to original
Beginning test data is trained, learns and adjusted, so as to generate new test data.
7. the method as any one of claim 1-5, it is characterised in that step 5 is specially：By setting up test system
Mapping between model and TTCN-3 test system models, realizes test system model turning to TTCN-3 abstract test cases
Change, and then generate TTCN-3 and can perform test case script, by TTCN-3 test execution platforms, realize to network application system
Automatic test.
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| CN107885656B (en) * | 2017-09-13 | 2021-02-09 | 平安科技（深圳）有限公司 | Automatic product algorithm testing method and application server |
| CN107808004B (en) * | 2017-11-15 | 2021-02-26 | 北京百度网讯科技有限公司 | Model training method and system, server and storage medium |
| CN110737726B (en) * | 2018-07-03 | 2024-04-05 | 北京京东尚科信息技术有限公司 | Method and device for determining test data of interface to be tested |
| CN110058922B (en) * | 2019-03-19 | 2021-08-20 | 华为技术有限公司 | Method and device for extracting metadata of machine learning task |
| CN110008121B (en) * | 2019-03-19 | 2022-07-12 | 合肥中科类脑智能技术有限公司 | Personalized test system and test method thereof |
| US11295242B2 (en) | 2019-11-13 | 2022-04-05 | International Business Machines Corporation | Automated data and label creation for supervised machine learning regression testing |
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