CN107025172B - A kind of method for testing software based on probabilistic risk assessment - Google Patents
A kind of method for testing software based on probabilistic risk assessment Download PDFInfo
- Publication number
- CN107025172B CN107025172B CN201710173137.0A CN201710173137A CN107025172B CN 107025172 B CN107025172 B CN 107025172B CN 201710173137 A CN201710173137 A CN 201710173137A CN 107025172 B CN107025172 B CN 107025172B
- Authority
- CN
- China
- Prior art keywords
- risk assessment
- probabilistic risk
- software
- event
- probabilistic
- 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.)
- Active
Links
- 238000012502 risk assessment Methods 0.000 title claims abstract description 42
- 238000000034 method Methods 0.000 title claims abstract description 28
- 238000012360 testing method Methods 0.000 claims abstract description 46
- 238000005070 sampling Methods 0.000 claims abstract description 8
- 238000004088 simulation Methods 0.000 claims description 14
- 238000004458 analytical method Methods 0.000 claims description 8
- 230000008859 change Effects 0.000 claims description 6
- 238000012512 characterization method Methods 0.000 claims description 4
- 230000004044 response Effects 0.000 claims description 3
- 238000010200 validation analysis Methods 0.000 claims description 3
- 230000009471 action Effects 0.000 claims description 2
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 description 19
- 239000007788 liquid Substances 0.000 description 12
- 230000006870 function Effects 0.000 description 8
- 230000008569 process Effects 0.000 description 7
- 230000005856 abnormality Effects 0.000 description 4
- 238000007599 discharging Methods 0.000 description 4
- 230000007547 defect Effects 0.000 description 2
- 238000013461 design Methods 0.000 description 2
- 238000010586 diagram Methods 0.000 description 2
- 230000000694 effects Effects 0.000 description 2
- 238000005516 engineering process Methods 0.000 description 2
- 241000208340 Araliaceae Species 0.000 description 1
- 235000005035 Panax pseudoginseng ssp. pseudoginseng Nutrition 0.000 description 1
- 235000003140 Panax quinquefolius Nutrition 0.000 description 1
- 238000013459 approach Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 235000000332 black box Nutrition 0.000 description 1
- 238000012938 design process Methods 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 238000011990 functional testing Methods 0.000 description 1
- 235000008434 ginseng Nutrition 0.000 description 1
- 239000000463 material Substances 0.000 description 1
- 230000001105 regulatory effect Effects 0.000 description 1
- 230000009711 regulatory function Effects 0.000 description 1
- 238000011160 research Methods 0.000 description 1
- 230000003068 static effect Effects 0.000 description 1
- 239000000126 substance Substances 0.000 description 1
- 238000010998 test method Methods 0.000 description 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F11/00—Error detection; Error correction; Monitoring
- G06F11/36—Preventing errors by testing or debugging software
- G06F11/3668—Software testing
Landscapes
- Engineering & Computer Science (AREA)
- Theoretical Computer Science (AREA)
- Computer Hardware Design (AREA)
- Quality & Reliability (AREA)
- Physics & Mathematics (AREA)
- General Engineering & Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Stored Programmes (AREA)
Abstract
The present invention discloses a kind of method for testing software based on probabilistic risk assessment, comprises the following steps：S1, probabilistic risk assessment scene Recognition；S2, the description of operation profile feature；S3, operation profile generation sample；S4, the physical phantom for building system；S5, physical phantom produce test case；S6, perform test.The present invention is by using probabilistic risk assessment（PRA）Method is analyzed system, is obtained the feature description of system operation section, and stochastical sampling generation sample on this basis, is produced the test case for including probability nature, farthest tests whether system software function after risk case occurs reaches expected requirement.Can complete and accurate construction software operational profile, and the software reliability assessment based on risk-informed can be further used for.
Description
Technical field
The invention belongs to reliability testing technical field, specifically a kind of software test side based on probabilistic risk assessment
Method.
Background technology
Probabilistic risk assessment be with based on accident scene method analyze and research real system, it can clearly be retouched
The precarious position of system and the occurrence and development process of latent defect are stated, passes through a variety of safety analysis technologies of R. concomitans, mirror
Do not go out its consequence, and calculate various hazards to cause the probability of happening of accident, can effectively support the management of security risk
Decision-making, feasible and effective approach is provided for the qualitative assessment of risk, is applied to the fields such as nuclear energy, chemical industry, space flight.
Software test is the committed step of software quality assurance, and its target is put into minimum human and material resources and time,
Foundation can be provided for software reliability analysis by excavating various mistakes and defect, test result present in software as much as possible.
In the basic process tested software, test design is to design testing scheme according to test plan, is write
The process of DCO script.The output of test design process is the test case that each test phase uses.With software systems
Increasingly huge, the test of software is just becoming complicated as software development.Traditional method of testing has a variety of classification, such as：Whitepack
Test is tested with Black-box Testing, functional test and structured testing, static test and dynamic.But the generating process of test case is most
Randomly generate, test process takes time and effort, and can not comprehensive simulated software practical operation scene, and construct complete and accurate
Operation profile.
The content of the invention
The present invention provides a kind of method for testing software based on probabilistic risk assessment to solve the above problems.
A kind of method for testing software based on probabilistic risk assessment of the present invention, comprises the following steps：
S1, probabilistic risk assessment scene Recognition：System is obtained by conventional probability risk assessment analysis method accordingly to cause
Each event cut set of top event, and fault Tree is established according to each event cut set, then analyze software after each cut set event occurs
The control action risen, the probabilistic risk assessment scene of high-level of the identification comprising software adjustment function；
S2, operation profile characterize description：With reference to the initial conditions of system and the probabilistic risk assessment scene of high-level
Probability failure model, i.e. system physical situation related each event cut set and its probability, and system caused by each event cut set become
Change, form operation profile, then characterization description is carried out to operation profile, truly trace system state and variability；
S3, operation profile generation sample：Stochastical sampling generates sample from operation profile, and sample size is determined by testing requirement
It is fixed；
S4, the physical phantom for building system：With reference to the physical phantom of simulation software constructing system；
S5, physical phantom produce test case：By the physical phantom of sample input system, physical phantom
Operation emulation obtains including the simulation result of probability nature, and is used as test case；
S6, perform test：Test case input system under test (SUT) is tested.
Further, in S2, system change is characterized with the probability distribution of different type parameter.
Further, in S2, the probability distribution of different type parameter can obtain during operation profile characterizes description
Arrive.
Further, in S3, sample content includes：System initial conditions, the probability distribution of system initial conditions, high-level
Probabilistic risk assessment scene in an event cut set and event cut set in each failure event probability failure model.
Further, in S5, the simulation result as test case includes physical parameter numerical value.
Further, in S5, physical parameter numerical value includes but is not limited to sensor signal numerical value.
Further, in S6, in addition to real response and software requirement with reference to software test, whether analysis software operation
Rationally, whether validation test result is correct.
The beneficial effects of the invention are as follows：
The present invention is by using probabilistic risk assessment（PRA）Method is analyzed system, obtains system on this basis
The feature description of operation profile, and stochastical sampling generation sample, produce the test case for including risk information, farthest survey
Whether system software function can reach expected requirement after examination risk case occurs.Can complete and accurate construction software operational profile,
And the software reliability assessment based on risk-informed can be further used for.
Brief description of the drawings
Fig. 1 is the software test procedure flow chart of the present invention；
Fig. 2 is the tank level control system model of the present embodiment；
Fig. 3 is the tank level control system control program software flow pattern of the present embodiment；
Fig. 4 is the tank level control system model PRA scene Recognitions of the present embodiment；
Fig. 5 is the simulation model block diagram of the present embodiment；
Fig. 6 is the part sample file of the present embodiment.
Embodiment
To further illustrate each embodiment, the present invention is provided with accompanying drawing.These accompanying drawings are the invention discloses the one of content
Point, it can coordinate the associated description of specification to explain the operation principles of embodiment mainly to illustrate embodiment.Coordinate ginseng
These contents are examined, those of ordinary skill in the art will be understood that other possible embodiments and advantages of the present invention.In figure
Component be not necessarily to scale, and similar element numbers are conventionally used to indicate similar component.
The method for testing software of the present invention, by using probabilistic risk assessment（PRA）Method is analyzed system, herein
On the basis of obtain system operation section feature description, and stochastical sampling generation sample, produce comprising probability nature test use
Example, farthest tests whether system software function after risk case occurs reaches expected requirement.
In conjunction with the drawings and specific embodiments, the present invention is further described.
Embodiment：
As shown in Figures 1 to 6, as a specific embodiment, the present invention is by building a single water tank liquid level control
System model processed, according to flow shown in Fig. 1, illustrate the specific implementation of the method for testing software of the invention based on probabilistic risk assessment
Process.
It is illustrated in figure 2 a kind of tank level control system model, including valve pipe, water tank and corresponding control system.It is controlled
Software flow figure processed, as shown in figure 3, including liquid level regulatory function and water level abnormality defencive function.
Step 1：Probabilistic risk assessment scene Recognition：System can obtain by conventional probability risk assessment analysis method and cause phase
Each event cut set of top event is answered, and establishes fault Tree, then analyzes the control that software rises after each cut set event occurs and makees
With, be identified as comprising software adjustment function high-level probabilistic risk assessment scene.Specifically, by conventional probability risk assessment
Analysis method obtains corresponding event cut set, with reference to soft by the definition of model assembly fault mode and impact analysis to structure
Part acts on, and gained high-level probabilistic risk assessment scene is as shown in Figure 4.Top event is liquid level control system water level abnormality, i.e. water covers
Water tank is dry, is undesired event.Cause top event there are 3 one-level reason events, and finally identify 8 things
Part cut set, from system performance, 8 elementary events are minimal cut set, i.e. the generation of any one elementary event can all be led
Cause liquid level control system water level abnormality.In this probabilistic risk assessment scene, comprising effect software adjustment function to system.Example
Such as, relative to two kinds of fault modes of feed-water valve：Failure closes and failure standard-sized sheet, water discharging valve only have a kind of fault mode,
That is water discharging valve failure standard-sized sheet, reason are that Control System Software can be carried out to feed-water valve when water discharging valve failure closes
Corresponding control, will not cause water level abnormality top event to occur.This fault tree for considering software impact can recognize that as more high-level
Probabilistic risk assessment scene, i.e., the probabilistic risk assessment scene of the high-level comprising software adjustment function.
Step 2, operation profile feature describes：With reference to the initial conditions of system and the probabilistic risk assessment scene of high-level
Probability failure model, i.e. system physical situation related each event cut set and its probability, and system caused by each event cut set become
Change, form operation profile, then characterization description is carried out to operation profile, truly trace system state and variability.
By liquid level control system initial conditions probability distribution situation, 3 kinds of initial conditions are defined：
L- liquid levels are in low water level, and system is in adjustment state
M- liquid levels are in given liquid level, and system is in stable state
H- liquid levels are in high water level, and system is in adjustment state
Each event cut set formed with reference to above-mentioned 8 elementary events as minimal cut set, i.e.,：
X1- cut events；
X2- controllers fail；
X3- feed-water valves failure closes；
X4- feed-water valve failure standard-sized sheets；
X5- water discharging valve failure standard-sized sheets；
X6- sensors are without output；
The output of X7- sensors keeps the instantaneous value before failure；
X8- sensors export maximum；
And its respective probability, and system change caused by each event cut set, liquid level control system operation profile can be described, then it is right
Operation profile carries out characterization description, truly trace system state and variability.System change different type parameter
Probability distribution is characterized, and the probability distribution of different type parameter is determined by system operation section, and can be in the physical simulation mould of step 5
Embodied in type operation simulation process.
Step 3, operation profile generation sample：Stochastical sampling generates several samples from operation profile.Sample content bag
Include：The probability distribution of system initial conditions, the system initial conditions of selection；Chosen from the probabilistic risk assessment scene of high-level
An event cut set；The probability failure model of each failure event in event cut set（Failure mould including each failure event
Formula and failure probability）.
According to high-level probabilistic risk assessment scene, stochastical sampling event cut set is carried out according to event occurrence rate, wherein
Comprising probability failure model, the part sample file of acquisition is as shown in Figure 6.
Step 4, system physical simulation model is built：Liquid level control system simulation model is built by emulation tool, its block diagram
As shown in Figure 5.Model uses closed-loop control system, and tank level control system part has been included among model, i.e. water tank, ratio
Integral differential（PID）Controller, liquid level sensor, motor regulated valve etc., and add change-over switch and be used to introduce failure event.
Gained model can be used for analogue system steady state operating condition, and after failure event introducing, the event of realistic simulation sample is cut
The failure effect of collection.
Step 5, physical phantom produces test case：The physical phantom of sample input system will be sampled, obtained
The simulation result of probability nature is included corresponding to each sample.Simulation result is as test case corresponding to each sample.As
The simulation result of test case contains the physical parameter numerical value of representative sensor signal etc..
Step 6, test and analysis result are performed：Simulation result contains the physical parameter number of representative sensor signal etc.
Value, this signal will be used as test case input system software.In the present embodiment, by test case input control system, with reference to
Software real response and software requirement, whether analysis software operation is reasonable, and whether validation test result is correct.
A kind of method for testing software based on probabilistic risk assessment of the present invention, by using probabilistic risk assessment（PRA）Side
Method is analyzed system, is obtained the feature description of system operation section, and stochastical sampling generation sample on this basis, is produced
Test case comprising risk information, whether system software function reaches expected and wants after farthest test risk case occurs
Ask.Can complete and accurate construction software operational profile, and the software reliability assessment based on risk-informed can be further used for.
Although specifically showing and describing the present invention with reference to preferred embodiment, those skilled in the art should be bright
In vain, do not departing from the spirit and scope of the present invention that appended claims are limited, in the form and details can be right
The present invention makes a variety of changes, and is protection scope of the present invention.
Claims (7)
- A kind of 1. method for testing software based on probabilistic risk assessment, it is characterised in that：Comprise the following steps：S1, probabilistic risk assessment scene Recognition：By conventional probability risk assessment analysis method obtain system cause accordingly it is useful Each event cut set of part, and fault Tree is established according to each event cut set, then analyze software after each cut set event occurs and rise Control action, identification comprising software adjustment function high-level probabilistic risk assessment scene；S2, operation profile characterize description：With reference to system initial conditions and high-level probabilistic risk assessment scene probability Failure model, i.e. system physical situation related each event cut set and its probability, and system change caused by each event cut set, structure Characterization description is carried out into operation profile, then to operation profile, truly trace system state and variability；S3, operation profile generation sample：Stochastical sampling generates sample from operation profile；S4, the physical phantom for building system：The physical phantom of constructing system；S5, physical phantom produce test case：By the physical phantom of sample input system, physical phantom operation Emulation obtains including the simulation result of probability nature, and is used as test case；S6, perform test：Test case input system under test (SUT) is tested.
- A kind of 2. method for testing software based on probabilistic risk assessment as claimed in claim 1, it is characterised in that：In S2, it is Variability of uniting is characterized with the probability distribution of different type parameter.
- A kind of 3. method for testing software based on probabilistic risk assessment as claimed in claim 2, it is characterised in that：In S2, no The probability distribution of similar shape parameter can obtain during operation profile characterizes description.
- A kind of 4. method for testing software based on probabilistic risk assessment as claimed in claim 1, it is characterised in that：In S3, sample This content includes：One in system initial conditions, the probability distribution of system initial conditions, the probabilistic risk assessment scene of high-level The probability failure model of each failure event in individual event cut set and event cut set.
- A kind of 5. method for testing software based on probabilistic risk assessment as claimed in claim 1, it is characterised in that：In S5, make Include physical parameter numerical value for the simulation result of test case.
- A kind of 6. method for testing software based on probabilistic risk assessment as claimed in claim 5, it is characterised in that：In S5, thing Reason parameter values include sensor signal numerical value.
- A kind of 7. method for testing software based on probabilistic risk assessment as claimed in claim 1, it is characterised in that：In S6, also Real response and software requirement including combining software test, whether analysis software operation is reasonable, and just whether validation test result Really.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710173137.0A CN107025172B (en) | 2017-03-22 | 2017-03-22 | A kind of method for testing software based on probabilistic risk assessment |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710173137.0A CN107025172B (en) | 2017-03-22 | 2017-03-22 | A kind of method for testing software based on probabilistic risk assessment |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN107025172A CN107025172A (en) | 2017-08-08 |
| CN107025172B true CN107025172B (en) | 2018-01-05 |
Family
ID=59526169
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201710173137.0A Active CN107025172B (en) | 2017-03-22 | 2017-03-22 | A kind of method for testing software based on probabilistic risk assessment |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN107025172B (en) |
Families Citing this family (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107480069A (en) * | 2017-08-23 | 2017-12-15 | 厦门大学 | A kind of Ration Assessing Software Dependability method under low demand operator scheme |
| CN110688152B (en) * | 2019-09-27 | 2021-01-01 | 厦门大学 | Software reliability quantitative evaluation method combining software development quality information |
| CN110795351B (en) * | 2019-10-29 | 2023-02-28 | 中国科学院微小卫星创新研究院 | Reliability increase testing and evaluating method for component-based star software |
| CN111413951A (en) * | 2020-04-01 | 2020-07-14 | 浙江中控技术股份有限公司 | Control system test signal generation method and device and test platform |
| CN111461239B (en) * | 2020-04-03 | 2023-05-09 | 成都考拉悠然科技有限公司 | CTC scene character recognition model optimization method based on white-box attack |
| CN114741284B (en) * | 2022-03-30 | 2023-02-07 | 中国电子产品可靠性与环境试验研究所（（工业和信息化部电子第五研究所）（中国赛宝实验室）） | Task reliability evaluation method and device, computer equipment and storage medium |
| CN114817078B (en) * | 2022-06-29 | 2022-11-29 | 荣耀终端有限公司 | Automatic testing method and device and storage medium |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103150481A (en) * | 2013-03-14 | 2013-06-12 | 安凯 | Computer-based realization method of cut set non-intersection in fault tree analysis |
| CN104239687A (en) * | 2014-08-13 | 2014-12-24 | 中国航天标准化研究所 | Reliability modeling and evaluation method based on aerospace product signal transmission path |
| CN106168797A (en) * | 2016-05-25 | 2016-11-30 | 哈尔滨工程大学 | A kind of modularity obtains the method for nuclear power station fault tree useful item failure probability |
| CN106226055A (en) * | 2016-08-04 | 2016-12-14 | 哈尔滨工程大学 | The monitoring reliability method that a kind of nuclear power plant based on fault tree valve body lost efficacy |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP4326731B2 (en) * | 2001-08-27 | 2009-09-09 | 株式会社東芝 | Process management system having risk monitor and process management method having risk display function |
-
2017
- 2017-03-22 CN CN201710173137.0A patent/CN107025172B/en active Active
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103150481A (en) * | 2013-03-14 | 2013-06-12 | 安凯 | Computer-based realization method of cut set non-intersection in fault tree analysis |
| CN104239687A (en) * | 2014-08-13 | 2014-12-24 | 中国航天标准化研究所 | Reliability modeling and evaluation method based on aerospace product signal transmission path |
| CN106168797A (en) * | 2016-05-25 | 2016-11-30 | 哈尔滨工程大学 | A kind of modularity obtains the method for nuclear power station fault tree useful item failure probability |
| CN106226055A (en) * | 2016-08-04 | 2016-12-14 | 哈尔滨工程大学 | The monitoring reliability method that a kind of nuclear power plant based on fault tree valve body lost efficacy |
Non-Patent Citations (2)
| Title |
|---|
| 反应堆FPGA 保护子***开发与验证;水璇璇 等;《核电子学与探测技术》;20151031;第35卷(第10期);全文 * |
| 基于故障树分析的软件安全性测试研究;赵跃华 等;《计算机应用研究》;20130630;第30卷(第6期);全文 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN107025172A (en) | 2017-08-08 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN107025172B (en) | A kind of method for testing software based on probabilistic risk assessment | |
| CN107608335B (en) | Data driving method for fault detection and fault separation of unmanned aerial vehicle flight control system | |
| CN105893256A (en) | Software failure positioning method based on machine learning algorithm | |
| Buehler et al. | Evolutionary functional testing of an automated parking system | |
| Wang et al. | An exploratory study of autopilot software bugs in unmanned aerial vehicles | |
| CN110991036B (en) | Spacecraft attitude and orbit control system fault case library construction system and construction method | |
| CN109470946B (en) | Power generation equipment fault detection method and system | |
| CN105138770B (en) | Space product Reliablility simulation appraisal procedure based on indirect characteristic quantities | |
| CN105629958A (en) | Intermittence process fault diagnosis method based on sub-period MPCA-SVM | |
| US7373550B2 (en) | Generation of a computer program to test for correct operation of a data processing apparatus | |
| Kuhn et al. | Input space coverage matters | |
| CN110059010A (en) | The buffer overflow detection method with fuzz testing is executed based on dynamic symbol | |
| US20070180411A1 (en) | Method and apparatus for comparing semiconductor-related technical systems characterized by statistical data | |
| CN105512372B (en) | The data processing onboard emulation test method of modelling | |
| Ossmann et al. | Detection and identification of loss of efficiency faults of flight actuators | |
| US20090319830A1 (en) | System and Method for Automatically Testing a Model | |
| Liu et al. | A data‐driven combined deterministic‐stochastic subspace identification method for condition assessment of roof structures subjected to strong winds | |
| Ozdagli et al. | Model-based damage detection through physics guided learning | |
| Niculita et al. | Design for diagnostics and prognostics: A physical-functional approach | |
| CN112849429B (en) | Tracing method for civil aircraft system measurement parameters | |
| CN106444695B (en) | A kind of intelligence Aircraft Steering Engine method for rapidly testing and device | |
| CN105068529B (en) | A kind of fault separating method and system compared based on weighted residual component | |
| Marcos | Application of H-infinity fault diagnosis to ADDSAFE benchmark: the control surface jamming case | |
| CN109635480A (en) | A kind of control logic verifying and adjustment method based on graphics software | |
| CN107957269B (en) | Inertial navigation system fault characteristic judgment and testability prediction method |
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 | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant | ||
| EE01 | Entry into force of recordation of patent licensing contract | ||
| EE01 | Entry into force of recordation of patent licensing contract |
Application publication date: 20170808 Assignee: Xiamen Mengjia Network Technology Co.,Ltd. Assignor: XIAMEN University Contract record no.: X2023350000134 Denomination of invention: A Software Testing Method Based on Probabilistic Risk Assessment Granted publication date: 20180105 License type: Common License Record date: 20230324 |
|
| EE01 | Entry into force of recordation of patent licensing contract |
Application publication date: 20170808 Assignee: Xiamen Douya Software Technology Co.,Ltd. Assignor: XIAMEN University Contract record no.: X2023350000166 Denomination of invention: A Software Testing Method Based on Probabilistic Risk Assessment Granted publication date: 20180105 License type: Common License Record date: 20230404 |
|
| EE01 | Entry into force of recordation of patent licensing contract | ||
| EE01 | Entry into force of recordation of patent licensing contract |
Application publication date: 20170808 Assignee: Xiamen Yunzai Technology Co.,Ltd. Assignor: XIAMEN University Contract record no.: X2023350000184 Denomination of invention: A Software Testing Method Based on Probabilistic Risk Assessment Granted publication date: 20180105 License type: Common License Record date: 20230412 Application publication date: 20170808 Assignee: Xiamen Zoyouxing Environmental Protection Technology Co.,Ltd. Assignor: XIAMEN University Contract record no.: X2023350000183 Denomination of invention: A Software Testing Method Based on Probabilistic Risk Assessment Granted publication date: 20180105 License type: Common License Record date: 20230412 |
|
| EE01 | Entry into force of recordation of patent licensing contract | ||
| EE01 | Entry into force of recordation of patent licensing contract |
Application publication date: 20170808 Assignee: ISTRONG TECHNOLOGY Co.,Ltd. Assignor: XIAMEN University Contract record no.: X2023350000316 Denomination of invention: A Software Testing Method Based on Probabilistic Risk Assessment Granted publication date: 20180105 License type: Common License Record date: 20230718 |
|
| EE01 | Entry into force of recordation of patent licensing contract |