CN109242363A - Full life cycle test management platform based on multiple quality control models - Google Patents
Full life cycle test management platform based on multiple quality control models Download PDFInfo
- Publication number
- CN109242363A CN109242363A CN201811297446.XA CN201811297446A CN109242363A CN 109242363 A CN109242363 A CN 109242363A CN 201811297446 A CN201811297446 A CN 201811297446A CN 109242363 A CN109242363 A CN 109242363A
- Authority
- CN
- China
- Prior art keywords
- test
- module
- parameter
- defect
- round
- 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
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0639—Performance analysis of employees; Performance analysis of enterprise or organisation operations
- G06Q10/06395—Quality analysis or management
Abstract
The invention provides a full life cycle test management platform based on multiple quality control models, which at least comprises: the system comprises an electronic review management module, a test evaluation module, a test plan module, a test requirement module, a test design module and a test execution module, wherein the test evaluation module is used for analyzing and evaluating the scale/function and the complexity of a tested system and calculating the workload according to a set experience value, the test plan module is used for planning the addition, deletion and modification of a test according to the evaluation result of the test evaluation module, the test requirement module is used for analyzing the test requirement, the test design module is used for manually/automatically designing a test case, and the test execution module is used for executing the test case designed by the test design module. The invention effectively improves the efficiency of compiling and executing the test cases, and is a full life cycle test management solution based on various quality control models. The invention establishes a software testing system architecture for securities futures industry companies. Meanwhile, an automatic, effective and convenient test design method is provided, and a multi-dimensional full-quality monitoring analysis and prediction model can be realized.
Description
Technical field
The present invention relates to the period measuring technical fields of quality control, specifically, more particularly to a kind of based on a variety of matter
The full lifecycle testing for measuring Controlling model manages platform.
Background technique
At present have on the market there are two types of manage platform: HP Quality Center and buddhist road Project Management Software.
HP Quality Center is the test and management tool based on web access mode, and QC is pseudo- B/S structure
Software --- ActiveX technology, actually Client/Server are inserted in browser, only appearance is B/S.It supports
Test and management process comprises determining that demand-> scenario test-> executes test-> tracking defect (exploitation test case).
Buddhist road Project Management Software is domestic open source projects management software, built-in demand management, task management, bug pipe
The functions such as reason, defect management, case management, plan publication.The development language that buddhist road software uses is PHP, and database is
MySQL, front end use jQuery as JS frame and some third-party front end extensions.It abdicates road and is absorbed in development project pipe
Reason, but it is not fine enough to test and management.
Therefore current supervision test software, can not be from test assessment, test plan, testing requirement analysis, test design, survey
Try the entire Life Cycle of executions, the coverage tests such as defect management, especially test design module, integrate or realize test case certainly
Dynamic design, rather than just hand-designed use-case.
Summary of the invention
According to technical problem set forth above, and provide a kind of full lifecycle testing based on a variety of Quality Control Models
Manage platform.The present invention relates to a kind of, and the full lifecycle testing based on a variety of Quality Control Models manages platform, includes at least:
The management of appraising module of electronization evaluation is analyzed according to the scale, function and complexity of system under test (SUT) and is assessed, root
Be calculated the test evaluation module of workload, according to the assessment result of the test evaluation module according to the empirical value of setting
Scenario test it is newly-increased, delete, the test plan module of modification, the testing requirement module for analyzing testing requirement, manual/auto set
Count test case test design module, execute it is described test design module design after example on probation testing execution module,
Defect is generated when the testing execution module executes and optimizes the defect management module of defect, based on Compertz mould
The failure prediction module of the bug prediction model of type, the testing journal sheet's module and project pipe that testing journal sheet is exported after being finished
Manage module.
Further, the test evaluation module amount of calculation includes at least following steps:
S11: standard is calculated according to current block/function system type/functional characteristics and function type and executes round；
If system type/the functional characteristics is unmodified, the standard executes round=1；Otherwise standard executes round=2；
S12: setting plan executes round and is equal to standard execution round；
S13: test system is obtained from default assessment parameter according to the genealogical classification of the current block/function and complexity
Number；
S14: system is obtained from the default assessment parameter according to the genealogical classification of the current block/function and complexity
Number 1；
S15: round is executed according to the genealogical classification of the current block/function and the plan and obtains coefficient 2；
If the plan executes round ≠ 1 and genealogical classification ≠ A class, the coefficient 2=of test execution ((hold 1+ by plan
Row round -1) * 0.75), plan to hold described in round=1 and genealogical classification=A, the coefficient 2=of test execution if plan executes
Row round；The A class is transaction and infrastructure component class；
S16: when executing round=1, test design efforts would=estimate with number of cases/test design coefficient is estimated；When
When executing round > 1, test execution workload=coefficient 1* coefficient 2 is estimated；
The workload=demand analysis+estimates workload+data configuration workload+test execution of estimating and works
Amount.
Further, the Automated Design use-case input parameter mainly includes the input parameter and parameter of test function point
Enumerated value；The parameter enumerated value includes: positive value and reverse value；
The Automated Design use-case at least also comprises the steps of:
S21: carrying out parameter number conjunction by cartesian product mode, handles the parameter value of complete combination, obtains new parameter；
S22: the combining parameter values of the new parameter and the complete combination remove according to preset constraint condition and do not meet
Then remaining each parameter is grouped by the data of the constraint condition according to combination parameter N；
S23: repeated data is removed by multilayer circulation, obtains combining parameter values.
Further, the failure prediction module of the bug prediction model based on Compertz model include at least with
Lower step:
S31: residual defects rate target is preset in the management platform；
S32: collecting from database and the defective data quantity of statistical item；
The defective data includes: effective defect and invalid defect；Effective defect is except other of cancellation and refusal
The defect of state；
S33: according to the defective data quantity call Compertz model algorithm, the overall defect number K of the prediction of estimation, when
The initial value a and gradient b of Y carries out project data failure prediction analysis when t=0, and described is forecast analysis are as follows:
K* (1- residual defects rate target %)=project expected defect sum.
Further, the Compertz model algorithm are as follows:
Linear transformation obtains:
log yt=log K+btlog a；
Wherein, t indicates that testing time, K indicate the overall defect number of prediction, K=ymax, the initial value of Ka expression y as t=0
Predict the starting point of defect, b indicates gradient.
Compared with the prior art, the invention has the following advantages that
The present invention effectively improves the efficiency that test case is write and executed, and is a based on a variety of Quality Control Models
Life cycle test and management solution.The present invention is that stock futures industry company establishes Software Testing System framework.
Automation is provided simultaneously, effectively easily test design method being capable of various dimensions, total quality monitoring analysis and prediction model.
Detailed description of the invention
In order to more clearly explain the embodiment of the invention or the technical proposal in the existing technology, to embodiment or will show below
There is attached drawing needed in technical description to do simply to introduce, it should be apparent that, the accompanying drawings in the following description is this hair
Bright some embodiments for those of ordinary skill in the art without any creative labor, can be with
It obtains other drawings based on these drawings.
Fig. 1 is overall structure of the present invention.
Fig. 2 is schematic diagram of the embodiment of the present invention.
Specific embodiment
In order to enable those skilled in the art to better understand the solution of the present invention, below in conjunction in the embodiment of the present invention
Attached drawing, technical scheme in the embodiment of the invention is clearly and completely described, it is clear that described embodiment is only
The embodiment of a part of the invention, instead of all the embodiments.Based on the embodiments of the present invention, ordinary skill people
The model that the present invention protects all should belong in member's every other embodiment obtained without making creative work
It encloses.
It should be noted that description and claims of this specification and term " first " in above-mentioned attached drawing, "
Two " etc. be to be used to distinguish similar objects, without being used to describe a particular order or precedence order.It should be understood that using in this way
Data be interchangeable under appropriate circumstances, so as to the embodiment of the present invention described herein can in addition to illustrating herein or
Sequence other than those of description is implemented.In addition, term " includes " and " having " and their any deformation, it is intended that cover
Cover it is non-exclusive include, for example, the process, method, system, product or equipment for containing a series of steps or units are not necessarily limited to
Step or unit those of is clearly listed, but may include be not clearly listed or for these process, methods, product
Or other step or units that equipment is intrinsic.
As shown in Figure 1, the present invention provides a kind of full lifecycle testing management based on a variety of Quality Control Models to put down
Platform includes at least:
The management of appraising module of electronization evaluation is analyzed according to the scale, function and complexity of system under test (SUT) and is assessed, root
Be calculated the test evaluation module of workload, according to the assessment result plan of test evaluation module according to the empirical value of setting
The newly-increased of test, deletion, the test plan module of modification, the testing requirement module for analyzing testing requirement, manual/auto design are surveyed
The test design module of example on probation, the testing execution module for executing the example on probation after test design module design, test execution mould
Defect is generated when block executes and optimizes the defect management module of defect, the defect of bug prediction model based on Compertz model
Prediction module, the testing journal sheet's module and project management module that testing journal sheet is exported after being finished.
As preferred embodiment, the present invention is based on B/S framework, the EasyUI frame by JQuery that front end uses
Frame, report show that through ECharts, by SpringMVC frame, front and back end carries out the transmitting of data, number by JSON for rear end
MyBatis frame is used according to persistent layer, database uses Mysql.It can be understood as in other embodiments, can also adopt
It is realized with other frameworks, as long as can satisfy can be calculated data and obtain corresponding data.
As preferred embodiment, tests evaluation module amount of calculation and include at least following steps: step S11: root
Standard, which is calculated, according to current block/function system type/functional characteristics and function type executes round；If system type/
Functional characteristics is unmodified, then standard executes round=1；Otherwise standard executes round=2；Step S12: setting plan executes round
Round is executed equal to standard；Step S13: according to the genealogical classification of current block/function and complexity from default assessment parameter
Obtain test coefficient；Step S14: it is obtained from default assessment parameter according to the genealogical classification of current block/function and complexity
Coefficient 1；Step S15: round is executed according to the genealogical classification of current block/function and plan and obtains coefficient 2；If plan executes
Round ≠ 1 and genealogical classification ≠ A class, then the coefficient 2=(1+ (plan execute round -1) * 0.75 of test execution), if plan is held
Row round=1 and genealogical classification=A, then the coefficient 2=plan of test execution executes round；A class is transaction and infrastructure component class；
Step S16: when executing round=1, test design efforts would=estimate with number of cases/test design coefficient is estimated；Work as execution
When round > 1, test execution workload=coefficient 1* coefficient 2 is estimated；Workload=demand analysis+estimates workload+data structure
Make workload+estimate test execution workload.
As a kind of embodiment of the application, as shown in Fig. 2, parameter 1 (A1, A2) combines shape with parameter 2 (B1, B2) first
At a new parameter ([A1, B1] [A1, A2] [A2, B1] [A2, B2])；New parameter is that parameter 3, parameter 4 are combined entirely, raw
At an interim findings, constraint condition is checked for, due to not having constraint condition, then enters directly into and is grouped
{ [A1B1] C1D1 } is split as { [A1B1] C1 } { [A1B1] D1 } { C1D1 }, and { [A1B1] C1D2 } is split as { [A1B1] C1 }
{ [A1B1] D2 } { C1D2 }, { [A1B1] C1D3 } are split as { [A1B1] C1 } { [A1B1] D3 } { C1D3 } ... ... and then remove divisor
According to { [A1B1] C1 } is repeated in parameter in interim findings, it is only necessary to retain one group of data ..., by constantly recycling
Repeated data obtains final result { A1B1C1D3 }, { A1B1C2D2 }, { A1B2C1D1 }, { A1B2C3D1 }, { A1B2C3D2 },
{ A2B1C1D2 }, { A2B1C3D3 }, { A2B2C2D1 }, { A2B2C2D3 }.The test case generated according to algorithm is as a result, particular field
It needs further to adjust under scape, platform provides the analysis classes adjustment to input parameter, is adjusted to test according to parameter characteristic
Step or test condition, test premise preparation etc..
As preferred embodiment, Automated Design use-case input parameter mainly include the input parameter of test function point with
And parameter enumerated value；Parameter enumerated value includes: positive value and reverse value.Automated Design use-case at least also comprises the steps of:
Step S21: carrying out parameter number conjunction by cartesian product mode, handles the parameter value of complete combination, obtains new ginseng
Number；
Step S22: the combining parameter values of new parameter and complete combination remove according to preset constraint condition and do not meet constraint
Then remaining each parameter is grouped by the data of condition according to combination parameter N；
Step S23: repeated data is removed by multilayer circulation, obtains combining parameter values.
In the present embodiment, the failure prediction module of the bug prediction model based on Compertz model include at least with
Lower step:
S31: residual defects rate target is preset in management platform；
S32: collecting from database and the defective data quantity of statistical item；
Defective data includes: effective defect and invalid defect；Effective defect is lacking except other states cancelled and refused
It falls into；
S33: Compertz model algorithm is called according to defective data quantity, the overall defect number K of the prediction of estimation, works as t=0
When Y initial value a and gradient b carry out project data failure prediction analysis, be forecast analysis are as follows: K* (1- residual defects rate mesh
Mark %)=project expected defect sum.
As preferred embodiment, Compertz model algorithm are as follows:
Linear transformation obtains:
log yt=log K+btlog a；
Wherein, t indicates that testing time, K indicate the overall defect number of prediction, K=ymax, the initial value of Ka expression y as t=0
Predict the starting point of defect, b indicates gradient, and b is bigger, and representative needs the testing time more, and the time for reaching K is longer, the smaller need of b
Want the testing time fewer.
The serial number of the above embodiments of the invention is only for description, does not represent the advantages or disadvantages of the embodiments.
In the above embodiment of the invention, it all emphasizes particularly on different fields to the description of each embodiment, does not have in some embodiment
The part of detailed description, reference can be made to the related descriptions of other embodiments.
In several embodiments provided herein, it should be understood that disclosed technology contents can pass through others
Mode is realized.Wherein, the apparatus embodiments described above are merely exemplary, such as the division of the unit, Ke Yiwei
A kind of logical function partition, there may be another division manner in actual implementation, for example, multiple units or components can combine or
Person is desirably integrated into another system, or some features can be ignored or not executed.Another point, shown or discussed is mutual
Between coupling, direct-coupling or communication connection can be through some interfaces, the INDIRECT COUPLING or communication link of unit or module
It connects, can be electrical or other forms.
The unit as illustrated by the separation member may or may not be physically separated, aobvious as unit
The component shown may or may not be physical unit, it can and it is in one place, or may be distributed over multiple
On unit.It can some or all of the units may be selected to achieve the purpose of the solution of this embodiment according to the actual needs.
It, can also be in addition, the functional units in various embodiments of the present invention may be integrated into one processing unit
It is that each unit physically exists alone, can also be integrated in one unit with two or more units.Above-mentioned integrated list
Member both can take the form of hardware realization, can also realize in the form of software functional units.
If the integrated unit is realized in the form of SFU software functional unit and sells or use as independent product
When, it can store in a computer readable storage medium.Based on this understanding, technical solution of the present invention is substantially
The all or part of the part that contributes to existing technology or the technical solution can be in the form of software products in other words
It embodies, which is stored in a storage medium, including some instructions are used so that a computer
Equipment (can for personal computer, server or network equipment etc.) execute each embodiment the method for the present invention whole or
Part steps.And storage medium above-mentioned includes: that USB flash disk, read-only memory (ROM, Read-Only Memory), arbitrary access are deposited
Reservoir (RAM, Random Access Memory), mobile hard disk, magnetic or disk etc. be various to can store program code
Medium.
Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present invention., rather than its limitations；To the greatest extent
Pipe present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that: its according to
So be possible to modify the technical solutions described in the foregoing embodiments, or to some or all of the technical features into
Row equivalent replacement；And these are modified or replaceed, various embodiments of the present invention technology that it does not separate the essence of the corresponding technical solution
The range of scheme.
Claims (5)
1. a kind of full lifecycle testing based on a variety of Quality Control Models manages platform, which is characterized in that include at least:
The management of appraising module of electronization evaluation is analyzed assessment basis according to the scale/function and complexity of system under test (SUT) and is set
Fixed empirical value be calculated the test evaluation module of workload, according to the assessment result plan of the test evaluation module
The newly-increased of test, deletion, the test plan module of modification, the testing requirement module for analyzing testing requirement, manual/auto design are surveyed
The test design module of example on probation, the testing execution module for executing the example on probation after the test design module design；
Defect is generated when the testing execution module executes and optimizes the defect management module of defect, based on Compertz model
The failure prediction module of bug prediction model, the testing journal sheet's module and project management mould that testing journal sheet is exported after being finished
Block.
2. a kind of full lifecycle testing based on a variety of Quality Control Models according to claim 1 manages platform,
It is further characterized in that:
The test evaluation module amount of calculation includes at least following steps:
S11: standard is calculated according to current block/function system type/functional characteristics and function type and executes round；If
System type/the functional characteristics is unmodified, then the standard executes round=1；Otherwise standard executes round=2；
S12: setting plan executes round and is equal to standard execution round；
S13: test coefficient is obtained from default assessment parameter according to the genealogical classification of the current block/function and complexity；
S14: coefficient 1 is obtained from the default assessment parameter according to the genealogical classification of the current block/function and complexity；
S15: round is executed according to the genealogical classification of the current block/function and the plan and obtains coefficient 2；
If the plan executes round ≠ 1 and genealogical classification ≠ A class, ((plan executes wheel to 1+ to the coefficient 2=of test execution
Secondary -1) * 0.75), if plan executes plan described in round=1 and genealogical classification=A, the coefficient 2=of test execution and executes wheel
It is secondary；The A class is transaction and infrastructure component class；
S16: when executing round=1, test design efforts would=estimate with number of cases/test design coefficient is estimated；Work as execution
When round > 1, test execution workload=coefficient 1* coefficient 2 is estimated；
The workload=demand analysis+estimates workload+data configuration workload+described and estimates test execution workload.
3. a kind of full lifecycle testing based on a variety of Quality Control Models according to claim 1 manages platform,
It is further characterized in that:
The Automated Design use-case input parameter mainly includes the input parameter and parameter enumerated value of test function point；The ginseng
Number enumerated value includes: positive value and reverse value；
The Automated Design use-case at least also comprises the steps of:
S21: carrying out parameter number conjunction by cartesian product mode, handles the parameter value of complete combination, obtains new parameter；
S22: the combining parameter values of the new parameter and the complete combination remove according to preset constraint condition described in not meeting
Then remaining each parameter is grouped by the data of constraint condition according to combination parameter N；
S23: repeated data is removed by multilayer circulation, obtains combining parameter values.
4. a kind of full lifecycle testing based on a variety of Quality Control Models according to claim 1 manages platform,
It is further characterized in that:
The failure prediction module of the bug prediction model based on Compertz model includes at least following steps:
S31: residual defects rate target is preset in the management platform；
S32: collecting from database and the defective data quantity of statistical item；
The defective data includes: effective defect and invalid defect；Effective defect is except other states cancelled and refused
Defect；
S33: Compertz model algorithm is called according to the defective data quantity, the overall defect number K of the prediction of estimation, works as t=0
When Y initial value a and gradient b carry out project data failure prediction analysis, it is described be forecast analysis are as follows:
K* (1- residual defects rate target %)=project expected defect sum.
5. a kind of full lifecycle testing based on a variety of Quality Control Models according to claim 1 manages platform,
It is further characterized in that:
The Compertz model algorithm are as follows:
K > 0, a < 1,0 <b < 1；
Linear transformation obtains:
logyt=logK+btloga；
Wherein, t indicates that testing time, K indicate the overall defect number of prediction, K=ymax, the initial value prediction of Ka expression y as t=0
The starting point of defect, b indicate gradient.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201811297446.XA CN109242363B (en) | 2018-11-01 | 2018-11-01 | Full life cycle test management platform based on multiple quality control models |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201811297446.XA CN109242363B (en) | 2018-11-01 | 2018-11-01 | Full life cycle test management platform based on multiple quality control models |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN109242363A true CN109242363A (en) | 2019-01-18 |
| CN109242363B CN109242363B (en) | 2022-05-13 |
Family
ID=65080305
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201811297446.XA Active CN109242363B (en) | 2018-11-01 | 2018-11-01 | Full life cycle test management platform based on multiple quality control models |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN109242363B (en) |
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109857663A (en) * | 2019-01-26 | 2019-06-07 | 北京工业大学 | Automatic test platform of the crucial word drive in conjunction with image similarity |
| CN111143222A (en) * | 2019-12-30 | 2020-05-12 | 军事科学院系统工程研究院系统总体研究所 | Software evaluation method based on defect prediction |
| US11256608B2 (en) | 2019-08-06 | 2022-02-22 | Red Hat, Inc. | Generating test plans for testing computer products based on product usage data |
| CN117634932A (en) * | 2024-01-25 | 2024-03-01 | 深圳市微克科技股份有限公司 | Management system of platform for production test of intelligent watch |
| CN117634932B (en) * | 2024-01-25 | 2024-04-30 | 深圳市微克科技股份有限公司 | Management system of platform for production test of intelligent watch |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102521697A (en) * | 2011-12-13 | 2012-06-27 | 广东电网公司信息中心 | Power grid informatization evaluating lab management system |
| CN103246947A (en) * | 2012-02-10 | 2013-08-14 | 广州博纳信息技术有限公司 | Management system for software assessment lab |
| CN103257917A (en) * | 2012-02-16 | 2013-08-21 | 广州博纳信息技术有限公司 | Management method for software evaluation system |
| CN104407971A (en) * | 2014-11-18 | 2015-03-11 | 中国电子科技集团公司第十研究所 | Method for automatically testing embedded software |
| US20150078182A1 (en) * | 2011-09-10 | 2015-03-19 | Arnab Das | Methods systems, and devices for robustness improvement in a mobile ad hoc network using reputation-based routing |
-
2018
- 2018-11-01 CN CN201811297446.XA patent/CN109242363B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20150078182A1 (en) * | 2011-09-10 | 2015-03-19 | Arnab Das | Methods systems, and devices for robustness improvement in a mobile ad hoc network using reputation-based routing |
| CN102521697A (en) * | 2011-12-13 | 2012-06-27 | 广东电网公司信息中心 | Power grid informatization evaluating lab management system |
| CN103246947A (en) * | 2012-02-10 | 2013-08-14 | 广州博纳信息技术有限公司 | Management system for software assessment lab |
| CN103257917A (en) * | 2012-02-16 | 2013-08-21 | 广州博纳信息技术有限公司 | Management method for software evaluation system |
| CN104407971A (en) * | 2014-11-18 | 2015-03-11 | 中国电子科技集团公司第十研究所 | Method for automatically testing embedded software |
Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109857663A (en) * | 2019-01-26 | 2019-06-07 | 北京工业大学 | Automatic test platform of the crucial word drive in conjunction with image similarity |
| CN109857663B (en) * | 2019-01-26 | 2022-04-12 | 北京工业大学 | Keyword driving and image similarity combined automatic test platform |
| US11256608B2 (en) | 2019-08-06 | 2022-02-22 | Red Hat, Inc. | Generating test plans for testing computer products based on product usage data |
| CN111143222A (en) * | 2019-12-30 | 2020-05-12 | 军事科学院系统工程研究院系统总体研究所 | Software evaluation method based on defect prediction |
| CN117634932A (en) * | 2024-01-25 | 2024-03-01 | 深圳市微克科技股份有限公司 | Management system of platform for production test of intelligent watch |
| CN117634932B (en) * | 2024-01-25 | 2024-04-30 | 深圳市微克科技股份有限公司 | Management system of platform for production test of intelligent watch |
Also Published As
| Publication number | Publication date |
|---|---|
| CN109242363B (en) | 2022-05-13 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Namdar et al. | Business continuity-inspired resilient supply chain network design | |
| Fu et al. | Impact propagation and risk assessment of requirement changes for software development projects based on design structure matrix | |
| US20150120263A1 (en) | Computer-Implemented Systems and Methods for Testing Large Scale Automatic Forecast Combinations | |
| US8027859B2 (en) | Analysis of a model of a complex system, based on two models of the system, wherein the two models represent the system with different degrees of detail | |
| US20130024167A1 (en) | Computer-Implemented Systems And Methods For Large Scale Automatic Forecast Combinations | |
| CN109242363A (en) | Full life cycle test management platform based on multiple quality control models | |
| CN101620691A (en) | Automatic data mining platform in telecommunications industry | |
| US7941301B2 (en) | Modelling a complex system | |
| Thapar et al. | Quantifying reusability of software components using hybrid fuzzy analytical hierarchy process (FAHP)-Metrics approach | |
| KR20180106533A (en) | Data Value evaluation system through detailed analysis of data governance data | |
| CN111242430A (en) | Power equipment supplier evaluation method and device | |
| CN113139687A (en) | Method and device for predicting default of credit card user | |
| Avritzer et al. | A multivariate characterization and detection of software performance antipatterns | |
| US20050278301A1 (en) | System and method for determining an optimized process configuration | |
| Truong et al. | Modeling non-compensatory preferences in environmental valuation | |
| CN112785057B (en) | Method, device, equipment and storage medium for predicting quantity of parts based on exponential smoothing | |
| Lozano et al. | Developing flexible management strategies in infrastructure: The sequential expansion problem for infrastructure analysis (SEPIA) | |
| Jiang et al. | An examination of the factors influencing software development effort | |
| Schroeder et al. | Predicting and evaluating software model growth in the automotive industry | |
| Li et al. | Challenges in developing a computational platform to integrate data analytics with simulation-based optimization | |
| CN111849545B (en) | Hydrocracking product quality prediction method, device and memory | |
| Lee et al. | Software reliability prediction for open source software adoption systems based on early lifecycle measurements | |
| Tiihonen et al. | Coping with Inconsistent Models of Requirements. | |
| Esposito et al. | Misspecification analysis of gamma‐and inverse Gaussian‐based perturbed degradation processes | |
| De Sousa Coelho et al. | System dynamics model for simulation of the software inspection process |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| TA01 | Transfer of patent application right | ||
| TA01 | Transfer of patent application right |
Effective date of registration: 20210315 Address after: No. 178, Huanghai Avenue, Dalian Economic and Technological Development Zone, Liaoning, 116600 Applicant after: Dashangsuo Feitai Testing Technology Co.,Ltd. Address before: Room 2607-07, 26 / F, 541 Huangpu Road, high tech park, Dalian, Liaoning 116000 Applicant before: DALIAN FUTURES INFORMATION TECHNOLOGY Co.,Ltd. |
|
| GR01 | Patent grant | ||
| GR01 | Patent grant |