CN105045710A - Method for automatically generating test data in cloud computing environment - Google Patents
Method for automatically generating test data in cloud computing environment Download PDFInfo
- Publication number
- CN105045710A CN105045710A CN201510373216.7A CN201510373216A CN105045710A CN 105045710 A CN105045710 A CN 105045710A CN 201510373216 A CN201510373216 A CN 201510373216A CN 105045710 A CN105045710 A CN 105045710A
- Authority
- CN
- China
- Prior art keywords
- test
- cloud
- data
- plan
- platform
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Landscapes
- Debugging And Monitoring (AREA)
Abstract
The invention relates to a method for automatically generating test data in a cloud computing environment, belonging to the technical field of performance tests. The method comprises the four steps of defining a test plan, uploading data to be tested to a cloud testing platform, executing a test and generating and analyzing a test report. According to the invention, too much manual intervention is unnecessary; the repetitive process can be effectively reduced, so that the time, the cost and the workload can be saved; and the method has the advantages of being rapid in data processing and testing speed, saved in memory space and the like.
Description
Technical field
The invention belongs to the technical field of performance test, the automatic test data creation method particularly under a kind of cloud computing environment.
Background technology
Software test ensures and improves the important means of software quality, and it is important step indispensable in software life-cycle.In software test procedure, the generation of test data is its key problem, is also key and the difficult point place of software test.Generating suitable test data is the basis of carrying out software test efficiently.Quantum leapfrog algorithm be software test data generate provide abundant Theories and methods, effectively can improve the efficiency of software test.
Any one test all be unable to do without manual test, based on test case, at the test initial stage, we need manual test, but manual test also has its very large limitation, first each paths can not be covered, also there is not repeated problem in unit testing, once arrive regression test, it is very large that the workload of test job will become, many and sequential, deadlock, resource contention, the mistake that multithreading etc. are relevant, be difficult to capture by manual test and carry out system load, during performance test, when needing the various application scenario such as simulation mass data or a large amount of concurrent users, this is also that manual test cannot be simulated.If the amount of test data of whole test process is huge, and data variation is frequent, (1 day) is at short notice needed to complete, only rely on tester manually test data, carry out inputting in test and management instrument, revise, the operation such as deletion, may accomplish hardly, and efficiency is low, easy test generation data are inconsistent, provide insecure test data so just to other tester, cause the inefficacy of test result.
JMeter is the testing tool based on java of Apache organization development, compares other HTTP testing tools, and the topmost feature of JMeter is that extendability is strong, has widely applied at present in the performance test process of each company.It providing one utilizes local ProxyServer (proxy server) to record the function generating test script, achieve powerful test function and can aggregated report be provided, when a build task, required task is searched in some tasks, generate HTML report (report) after end of run, and check the Output rusults of test.The report generated shows the result of each test run, comprise the time that test mode, time, data execution sequence and all tests spend, make user or test developer grasp integrated testability situation intuitively, check test report result.Meanwhile, Jenkins is an open source projects, provides a kind of wieldy continuous integration system, make developer from numerous and diverse integrated free, be absorbed in even more important service logic and realize.The mistake of the integrated middle existence of Jenkins energy implementing monitoring, provides detailed journal file and prompting function, can also show trend and the stability of project build by the form of chart visually simultaneously.It needs to define the lasting structure that some trigger conditions just can support task based access control, and there is oneself developing plug specification a set of, and have the performance plug-in unit DynamicParameters that increases income at present based on performance continuous integrating (continuous integrating).On this basis, build JMeter and Jenkins test platform, The platform provides the Test driver function library of Java programming language.The api provided with Jenkins notifies that Jenkins compiles engineering project, and the test result path of entry item information and triggering Jmeter plug-in unit needs loading automatically in engineering installation, write automatic test script, call Jmeter testing tool and project is tested, and generate test result.Facilitate software development test job person contrast test result at any time like this, from test result contrast, find out the defect of program code to improve the robustness of program code.
JMeter can simulate the intensity that a large amount of user end to server sends request testing server, and the overall performance of Analysis server.Jmeter generates multiple thread when running and simulates multiple user and perform request, and each request all have recorded the information such as response time, request initiation time, request results of request, the xml formatted file of the destination file of generation to be suffix be .jtl.So this file has the characteristics such as file is large, performance continuous integrating test record number is many, meanwhile, friendly gui interface is user-friendly to, and increase income, be applicable to big-and-middle-sized Web system performance test, and freely, learning curve is low.But it is the same with other java application programs, needs to take a large amount of internal memory in implementation.
In order to dirigibility to greatest extent, under JMeter framework, adopt regular expression to create assert, by can return the result of expectation with proving program code with the script of asserting, achieve the functional test of application programs.Only need several simple command statements, just can complete a jmeter file to the control of a jar type file (yang, table).Meanwhile, jmeter file can carry out along with test, the application performance of software improves and file update, and real-time amendment code and more new data are to be more suitable for the requirement tested.But, when the data volume waiting in line to test is very large, then needs to consume the test that a large amount of time just can complete one-period, the demand that development and testing personnel check properties of product cannot be met, for test job brings many inconvenience; Meanwhile, if during overabundance of data in the file that to be tested (table) script, the reaction time being loaded into jmeter instrument is long, and operation is very blunt.Therefore, be just badly in need of a kind of can the method for script of fast processing mass data file, need server to clear up internal memory rubbish in time simultaneously, reduce taking of disk space, improve parsing and the reading efficiency of test result data.But, due to multiple user's shared drive, so just need to terminal to apply resource (i.e. internal memory), if the low memory be assigned with, test crash will be caused, and the memory source of system is very limited, the continuous demand of software development worker can not be met, and cloud computing software test can effectively utilize the vast resources of cloud platform dynamic scalable, saving the test duration and reduce testing cost, is a kind of test Solution preferably.But existing cloud computing software test platform and service need to collect the charges in use, channel floor solution is expensive, and, these cloud test platforms and solution are that namely commercial company or test serve (TestingasaService, TaaS) provider is proprietary, their bottom-layer design is externally nonopen, and outside research personnel are difficult to the further investigation carrying out relevant issues.
Summary of the invention
The technical problem to be solved in the present invention is: overcome the deficiency that prior art processing speed in software test is slow, memory headroom is in short supply, test is easily failed, to leapfrog algorithm and cloud computing technology based on quantum, the automatic test data creation method under a kind of cloud computing environment and system are provided.
Technical matters of the present invention can be achieved through the following technical solutions:
An automatic test data creation method under cloud computing environment, comprises test plan definition, data upload to be tested is generated to cloud test platform, test execution, test report and analyze 4 steps;
Described test plan definition is, when setting up a test plan, on the gui interface of JMeter, this test plan shows with tree structure, and the content of test plan is stored as the file of an xml form, and the file of described xml form is the formalized description to tree-like test plan; When testing execution module performs test plan, will judge in internal memory, set up which type of object to reflect the test plan that user sets up according to the description of the file of described xml form, and produce respective behavior according to different objects and treat test macro and conduct interviews;
Described by data upload to be tested to cloud test platform is, cloud test platform realizes adopt the quantum algorithm that leapfrogs to obtain optimum test data and carry out grouping and test to all testing datas, carry out the statistics of each module of software test, association analysis, then apply large data processing data; The application program that all tests are relevant, testing tool, test case, test environment are all first deployed on cloud test platform, test by cloud computing technology;
Described test execution is, the data uploading to cloud test platform are opened by JMeter the operation that multithreading simulates multi-user, and wherein each thread calls the element object in test plan and performs the operation of these objects definition;
Described test report generates and with analysis is, collection average response time, throughput of system real-time in measuring executing process, and result is shown to tester with the form of aggregated report, carries out analyzing and reference for it.
Cloud test platform of the present invention is specifically made up of four levels, i.e. cloud resource layer, cloud resource management layer, SML and user management layer.
The present invention is intended to Jmeter automated test tool and Jenkins continuous integrating software for substrate, construct a cloud computing software test platform framework, to solve the phenomenon that in test process, internal memory is in short supply, adopt a large Data buffer, the test record of performance continuous integrating is loaded into by each performance continuous integrating test request in the buffer queue of internal memory, cloud platform realizes test, with quantum leapfrog algorithm obtain optimum test data carry out grouping test, carry out the statistics of each data of software test, association analysis, then cloud computing technology process data are applied, final quickening data processing test speed, save memory headroom.
The present invention has following beneficial effect:
1, the present invention uses any one link in continuous integrating automatically to complete, without the need to too many manual intervention, be conducive to reducing repetitive process to save time, expense and workload.
2, the present invention uses Jmeter automated test tool and Jenkins continuous integrating software, automatic test result can be solved preferably preserve and continuous integrating energy continuous presentation automatic test result, realize can facilitating contrast test result at any time, from test result contrast, find out the defect of program code and improve Procedure Haleness, achieving automatic test result continuous integrating and integrate.
3, the present invention adopts regular expression establishment to assert under JMeter framework, by can return the result of expectation with proving program code with the script of asserting, test command statement is simplified, achieves the functional test of application programs, improve test code dirigibility simultaneously.
4, cloud testing service platform of the present invention can improve the testing efficiency of developer, and test does not take the computational resource of developer, and can automatically carry out as far as possible.
5, cloud testing service platform of the present invention improves the security of test, even if test crash, whole system also can not be caused to collapse.
6, cloud testing service platform of the present invention makes test flexibly can change test environment, namely changes the resource distribution of test.
Accompanying drawing explanation
Fig. 1 is overall architecture of the present invention and functional part schematic diagram.
Fig. 2 is that quantum of the present invention leapfrogs the process flow diagram of Algorithm for Solving optimal data generation method.
Embodiment
Embodiment 1 general structure of the present invention
Automatic test data creation method under a kind of cloud computing environment of the present invention, comprises test plan definition, data upload to be tested is generated to cloud test platform, test execution, test report and analyze 4 steps;
Described test plan definition is, when setting up a test plan, on the gui interface of JMeter, this test plan is with tree structure display, and the storage format of its content is xml form, and the script that this xml form stores is the formalized description to tree-like test plan.When testing execution module performs test plan, will judge in internal memory, set up which type of object to reflect the test plan that user sets up according to the description of xml file, and produce respective behavior according to different objects and treat test macro and conduct interviews;
Described by data upload to be tested to cloud test platform is, cloud platform realizes to all testing datas adopt a kind of quantum leapfrog algorithm obtain optimum test data carry out grouping test, carry out the statistics of each table of software test, association analysis, then large data processing data is applied, accelerate data processing test speed, save memory headroom.And cloud test platform is made up of four levels, i.e. cloud resource layer, cloud resource management layer, SML, user management layer.These four layers together constitute cloud test platform, and the application such as application program, testing tool, test case, test environment that all tests are relevant all must first be deployed on cloud test platform, by cloud computing technology, improves the efficiency of test.The vast resources of cloud platform dynamic scalable can be effectively utilized, save the test duration and reduce testing cost.
Described test execution is, when test execution, the data uploading to cloud test platform are opened by JMeter the operation that multithreading simulates multi-user, and wherein each thread can call the element object in test plan and perform the operation of these objects definition;
Described test report generates and with analysis is, the performance index value such as collection average response time, throughput of system real-time in measuring executing process, and result is shown to tester with the form of aggregated report, carries out analyzing and reference for it.
The software configuration automatic generation of test data of embodiment 2 algorithm that leapfrogs based on quantum of the present invention
The work that automatic calculation effectively can reduce tester is carried out to software test data Generating Problems, improves Efficiency of Software Testing, save software development cost.Software Test Data Generation Method of the present invention is that quantum leapfrogs algorithm.The method selects input data randomly from the program input space (input domain), then input data are used for performing tested program, again according to input data execution result in a program, incorporating quantum leapfrog algorithm generate new input data, continuation runs and test procedure is soundd out, until find optimum solution.
1, the structure of adaptive value function
Adaptive value function is that quantum leapfrogs algorithm application in the optimization aim of Solve problems, and its structure directly affects the efficiency of PSO in particular problem.The present invention adopts " branch function method of superposition " to construct adaptive value function.Branch function is a real-valued function, it be branch's predicate to real-valued mapping, under can being described in the driving of test data quantitatively, the actual execution route of unit under test is to the level of coverage in selected path.
If path to be measured there be m take-off point, n parameter, then m branch function is respectively: f
1=f
1(x
1, x
2..., x
n), f
2=f
2(x
1, x
2..., x
n) ..., f
m=f
m(x
1, x
2..., x
n); And the branch function in this path is
F＝MAX-(F(f
1)+F(f
2)+…+F(f
m))
Wherein,
MAX is a comparatively big integer.
2, Test data generation algorithm
Leapfrog based on quantum the software configuration automatic generation of test data of algorithm, using the element of test data as frog population vector x.First stochastic generation test data, the test data of the algorithm search the best that then leapfrogs with quantum, makes the value of adaptive value function reach maximum.With reference to shown in Fig. 2, its step is as follows:
(1) tested program is analyzed.According to Test coverage strategy, tested program determination adaptive value function, and to tested program plug-in mounting;
(2) selected frog number m, adaptive value threshold epsilon, maximum permission iterations, group's number, the quantum position of initialization frog and position;
(3) iterative steps t=0; F
g=0; F
p=(0,0 ..., 0);
(4) when meeting F
g≤ ε and t<Maxiteration condition time, the program after using each frog in frog population P to perform piling; Result after running according to frog, calculates its fitness;
(5) quantum position and speed and the position of frog group is upgraded;
(6) until reach final iterations, obtain optimal data and generate result.
Below may be used for the matlab program that embodiment 2 carries out solving:
。
Claims (2)
1. the automatic test data creation method under cloud computing environment, comprises test plan definition, data upload to be tested is generated to cloud test platform, test execution, test report and analyze 4 steps;
Described test plan definition is, when setting up a test plan, on the gui interface of JMeter, this test plan shows with tree structure, and the content of test plan is stored as the file of an xml form, and the file of described xml form is the formalized description to tree-like test plan; When testing execution module performs test plan, will judge in internal memory, set up which type of object to reflect the test plan that user sets up according to the description of the file of described xml form, and produce respective behavior according to different objects and treat test macro and conduct interviews;
Described by data upload to be tested to cloud test platform is, cloud test platform realizes adopt the quantum algorithm that leapfrogs to obtain optimum test data and carry out grouping and test to all testing datas, carry out the statistics of each module of software test, association analysis, then apply large data processing data; The application program that all tests are relevant, testing tool, test case, test environment are all first deployed on cloud test platform, test by cloud computing technology;
Described test execution is, the data uploading to cloud test platform are opened by JMeter the operation that multithreading simulates multi-user, and wherein each thread calls the element object in test plan and performs the operation of these objects definition;
Described test report generates and with analysis is, collection average response time, throughput of system real-time in measuring executing process, and result is shown to tester with the form of aggregated report, carries out analyzing and reference for it.
2. the automatic test data creation method under a kind of cloud computing environment according to claim 1, is characterized in that, described cloud test platform is made up of four levels, i.e. cloud resource layer, cloud resource management layer, SML and user management layer.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201510373216.7A CN105045710B (en) | 2015-06-30 | 2015-06-30 | A kind of automatic test data creation method under cloud computing environment |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201510373216.7A CN105045710B (en) | 2015-06-30 | 2015-06-30 | A kind of automatic test data creation method under cloud computing environment |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN105045710A true CN105045710A (en) | 2015-11-11 |
| CN105045710B CN105045710B (en) | 2017-11-10 |
Family
ID=54452273
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201510373216.7A Expired - Fee Related CN105045710B (en) | 2015-06-30 | 2015-06-30 | A kind of automatic test data creation method under cloud computing environment |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN105045710B (en) |
Cited By (21)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105022635A (en) * | 2015-07-23 | 2015-11-04 | 北京中油瑞飞信息技术有限责任公司 | Algorithm file generating method and apparatus based on cloud platform and cloud platform |
| CN105320599A (en) * | 2015-11-26 | 2016-02-10 | 上海斐讯数据通信技术有限公司 | System and method for web automatic tests |
| CN105955749A (en) * | 2016-05-10 | 2016-09-21 | 北京启明星辰信息安全技术有限公司 | Continuous software project integration method and device |
| CN106210013A (en) * | 2016-07-04 | 2016-12-07 | 上海华岭集成电路技术股份有限公司 | A kind of integrated circuit testing information integration based on high in the clouds analyzes system and method |
| CN106850321A (en) * | 2017-04-05 | 2017-06-13 | 无锡华云数据技术服务有限公司 | A kind of simulated testing system of cluster server |
| CN106991039A (en) * | 2016-01-20 | 2017-07-28 | 滴滴（中国）科技有限公司 | Method of testing and device for platform adaptive automotive engine system |
| CN107092559A (en) * | 2017-04-18 | 2017-08-25 | 携程旅游信息技术（上海）有限公司 | Test platform middleware, test system and method based on Jmeter |
| CN107153601A (en) * | 2016-03-02 | 2017-09-12 | 阿里巴巴集团控股有限公司 | Unit performance method of testing and equipment |
| WO2017211042A1 (en) * | 2016-06-07 | 2017-12-14 | 中兴通讯股份有限公司 | Task automation testing method and system for big data |
| CN107491386A (en) * | 2016-06-13 | 2017-12-19 | 富士通株式会社 | The method and apparatus for recording test script |
| CN107608901A (en) * | 2017-10-20 | 2018-01-19 | 北京京东金融科技控股有限公司 | Method of testing and device based on Jmteter, storage medium, electronic equipment |
| CN108334443A (en) * | 2017-12-22 | 2018-07-27 | 海尔优家智能科技（北京）有限公司 | Generate method, apparatus, equipment and the computer readable storage medium of test case |
| CN108572919A (en) * | 2018-05-30 | 2018-09-25 | 平安普惠企业管理有限公司 | Automated testing method, device, computer equipment and storage medium |
| CN109460367A (en) * | 2018-11-16 | 2019-03-12 | 四川长虹电器股份有限公司 | Method based on the sustainable integrated automation performance test of Jmeter |
| CN110196812A (en) * | 2019-06-06 | 2019-09-03 | 四川长虹电器股份有限公司 | Based on the Web application iteration tests method recorded and reset |
| WO2020000726A1 (en) * | 2018-06-29 | 2020-01-02 | 平安科技（深圳）有限公司 | Performance test report generating method, electronic device, and readable storage medium |
| CN110750458A (en) * | 2019-10-22 | 2020-02-04 | 恩亿科(北京)数据科技有限公司 | Big data platform testing method and device, readable storage medium and electronic equipment |
| CN111290934A (en) * | 2018-12-06 | 2020-06-16 | 中车株洲电力机车研究所有限公司 | Jenkins-based vehicle-mounted network product cloud testing method and system |
| CN112256595A (en) * | 2020-12-22 | 2021-01-22 | 成都新希望金融信息有限公司 | Heterogeneous system testing method and device and electronic equipment |
| CN112765014A (en) * | 2021-01-04 | 2021-05-07 | 光大兴陇信托有限责任公司 | Automatic test system for multi-user simultaneous operation and working method |
| CN116909932A (en) * | 2023-09-12 | 2023-10-20 | 吉孚汽车技术(苏州)有限公司 | Continuous integrated automatic software testing system and method based on VT system |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103136101A (en) * | 2012-12-31 | 2013-06-05 | 博彦科技（上海）有限公司 | Software automated testing unified operation platform |
| CN104378252A (en) * | 2014-08-26 | 2015-02-25 | 国家电网公司 | Cloud testing service platform |
-
2015
- 2015-06-30 CN CN201510373216.7A patent/CN105045710B/en not_active Expired - Fee Related
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103136101A (en) * | 2012-12-31 | 2013-06-05 | 博彦科技（上海）有限公司 | Software automated testing unified operation platform |
| CN104378252A (en) * | 2014-08-26 | 2015-02-25 | 国家电网公司 | Cloud testing service platform |
Non-Patent Citations (3)
| Title |
|---|
| 孟祥超: ""云计算环境下的软件测试服务研究"", 《中国优秀硕士学位论文全文数据库 信息科技辑》 * |
| 布里泰恩: "《Tomcat权威指南(第二版)》", 30 September 2009, 中国电力出版社 * |
| 胥枫: ""软件自动化测试技术的研究"", 《中国优秀硕士学位论文全文数据库 信息科技辑》 * |
Cited By (27)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105022635A (en) * | 2015-07-23 | 2015-11-04 | 北京中油瑞飞信息技术有限责任公司 | Algorithm file generating method and apparatus based on cloud platform and cloud platform |
| CN105320599A (en) * | 2015-11-26 | 2016-02-10 | 上海斐讯数据通信技术有限公司 | System and method for web automatic tests |
| CN106991039A (en) * | 2016-01-20 | 2017-07-28 | 滴滴（中国）科技有限公司 | Method of testing and device for platform adaptive automotive engine system |
| CN107153601A (en) * | 2016-03-02 | 2017-09-12 | 阿里巴巴集团控股有限公司 | Unit performance method of testing and equipment |
| CN105955749A (en) * | 2016-05-10 | 2016-09-21 | 北京启明星辰信息安全技术有限公司 | Continuous software project integration method and device |
| WO2017211042A1 (en) * | 2016-06-07 | 2017-12-14 | 中兴通讯股份有限公司 | Task automation testing method and system for big data |
| CN107491386A (en) * | 2016-06-13 | 2017-12-19 | 富士通株式会社 | The method and apparatus for recording test script |
| CN106210013A (en) * | 2016-07-04 | 2016-12-07 | 上海华岭集成电路技术股份有限公司 | A kind of integrated circuit testing information integration based on high in the clouds analyzes system and method |
| CN106210013B (en) * | 2016-07-04 | 2019-12-20 | 上海华岭集成电路技术股份有限公司 | Integrated circuit test information integration analysis system and method based on cloud |
| CN106850321A (en) * | 2017-04-05 | 2017-06-13 | 无锡华云数据技术服务有限公司 | A kind of simulated testing system of cluster server |
| CN107092559A (en) * | 2017-04-18 | 2017-08-25 | 携程旅游信息技术（上海）有限公司 | Test platform middleware, test system and method based on Jmeter |
| CN107608901A (en) * | 2017-10-20 | 2018-01-19 | 北京京东金融科技控股有限公司 | Method of testing and device based on Jmteter, storage medium, electronic equipment |
| CN107608901B (en) * | 2017-10-20 | 2019-12-31 | 京东数字科技控股有限公司 | Jmeter-based testing method and device, storage medium and electronic equipment |
| CN108334443A (en) * | 2017-12-22 | 2018-07-27 | 海尔优家智能科技（北京）有限公司 | Generate method, apparatus, equipment and the computer readable storage medium of test case |
| CN108572919A (en) * | 2018-05-30 | 2018-09-25 | 平安普惠企业管理有限公司 | Automated testing method, device, computer equipment and storage medium |
| WO2020000726A1 (en) * | 2018-06-29 | 2020-01-02 | 平安科技（深圳）有限公司 | Performance test report generating method, electronic device, and readable storage medium |
| CN109460367A (en) * | 2018-11-16 | 2019-03-12 | 四川长虹电器股份有限公司 | Method based on the sustainable integrated automation performance test of Jmeter |
| CN111290934A (en) * | 2018-12-06 | 2020-06-16 | 中车株洲电力机车研究所有限公司 | Jenkins-based vehicle-mounted network product cloud testing method and system |
| CN110196812A (en) * | 2019-06-06 | 2019-09-03 | 四川长虹电器股份有限公司 | Based on the Web application iteration tests method recorded and reset |
| CN110196812B (en) * | 2019-06-06 | 2022-02-01 | 四川长虹电器股份有限公司 | Web application iteration test method based on recording and playback |
| CN110750458A (en) * | 2019-10-22 | 2020-02-04 | 恩亿科(北京)数据科技有限公司 | Big data platform testing method and device, readable storage medium and electronic equipment |
| CN112256595A (en) * | 2020-12-22 | 2021-01-22 | 成都新希望金融信息有限公司 | Heterogeneous system testing method and device and electronic equipment |
| CN112256595B (en) * | 2020-12-22 | 2021-03-12 | 成都新希望金融信息有限公司 | Heterogeneous system testing method and device and electronic equipment |
| CN112765014A (en) * | 2021-01-04 | 2021-05-07 | 光大兴陇信托有限责任公司 | Automatic test system for multi-user simultaneous operation and working method |
| CN112765014B (en) * | 2021-01-04 | 2024-02-20 | 光大兴陇信托有限责任公司 | Automatic test system for multi-user simultaneous operation and working method |
| CN116909932A (en) * | 2023-09-12 | 2023-10-20 | 吉孚汽车技术(苏州)有限公司 | Continuous integrated automatic software testing system and method based on VT system |
| CN116909932B (en) * | 2023-09-12 | 2023-12-05 | 吉孚汽车技术(苏州)有限公司 | Continuous integrated automatic software testing system and method based on VT system |
Also Published As
| Publication number | Publication date |
|---|---|
| CN105045710B (en) | 2017-11-10 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN105045710A (en) | Method for automatically generating test data in cloud computing environment | |
| CN110245067A (en) | Security critical software automates need-based test case and generates system and method | |
| EP2572294B1 (en) | System and method for sql performance assurance services | |
| Bernardino et al. | Canopus: A domain-specific language for modeling performance testing | |
| US9311345B2 (en) | Template based database analyzer | |
| US9552202B2 (en) | Automated and heuristically managed solution to quantify CPU and path length cost of instructions added, changed or removed by a service team | |
| Ehlers et al. | A self-adaptive monitoring framework for component-based software systems | |
| Remenska et al. | Using model checking to analyze the system behavior of the LHC production grid | |
| Li et al. | A scenario-based approach to predicting software defects using compressed C4. 5 model | |
| Wang et al. | A model-based framework for cloud API testing | |
| CN110109816A (en) | Test cases selection method and apparatus | |
| Sottile et al. | Semi-automatic extraction of software skeletons for benchmarking large-scale parallel applications | |
| US9983965B1 (en) | Method and system for implementing virtual users for automated test and retest procedures | |
| Belli et al. | Event-oriented, model-based GUI testing and reliability assessment—approach and case study | |
| US8850407B2 (en) | Test script generation | |
| Cleland-Huang et al. | Goal-centric traceability: Using virtual plumblines to maintain critical systemic qualities | |
| Augusto et al. | RETORCH: an approach for resource-aware orchestration of end-to-end test cases | |
| Calotoiu et al. | Extrapeak: Advanced automatic performance modeling for HPC applications | |
| CN114647568A (en) | Automatic testing method and device, electronic equipment and readable storage medium | |
| Hewage et al. | CloudSim express: A novel framework for rapid low code simulation of cloud computing environments | |
| Endo et al. | An industrial experience on using models to test web service-oriented applications | |
| Ahmad et al. | Scenario based functional regression testing using Petri net models | |
| Khan et al. | A literature review on software testing techniques for smartphone applications | |
| Müller et al. | Collaborative software performance engineering for enterprise applications | |
| Irfan et al. | Key role of value-oriented requirements to develop real-time database systems |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant | ||
| CF01 | Termination of patent right due to non-payment of annual fee |
Granted publication date: 20171110 Termination date: 20210630 |
|
| CF01 | Termination of patent right due to non-payment of annual fee |