CN107967218A - Boundary value test method in industrial software on-the-spot test based on user's history data - Google Patents
Boundary value test method in industrial software on-the-spot test based on user's history data Download PDFInfo
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Abstract
The invention discloses boundary value test method in a kind of industrial software on-the-spot test based on user's history data, belong to software test field.The on-the-spot test of industrial software is possible to bring serious loss to user's produced on-site, just valid data near boundary value and just invalid data easily causes production accident.Pass through the excavation to user production scene historical data, find the nearest invalid data near boundary value and nearest valid data, and according to corresponding historical process data come production status information caused by analyzing these data, assessing related data could be as the input data of border value testing, and the comparison foundation of output can be tested using the alignment processing process data of old software in historical data as tested new Software thread.The method of the present invention is based on obtaining border value testing data to the data processing of particular user production history, and closer to the actual conditions of user, testing efficiency and adequacy can be improved on the premise of effective accident prevention risk.
Description
Technical field
The invention belongs to industrial software technical field of measurement and test, and in particular to a kind of industrial software based on user's history data
Boundary value test method in on-the-spot test.
Background technology
Industrial software correlation technique develops constantly, and the online software of commercial plant is also updating, many old
Process industrial process units there is ongoing need for long-term normal operation, and the online software system of these devices may also need more
Newly.But wherein also there is phenomenon of the new software system in the failure of industrial installation scene trial operation, for example petrochemical iy produced high temperature is high
Pressure, inflammable and explosive, risk is too big, and user one has found that new software has bug, stops trial operation at once, dare not continue to take a risk.Its is tangible
Software supplier has also carried out conscientious non-at-scene test as possible before the live trial operation of these failures, in experimental provision very
It has been successfully tested to other similar process units, but still in this specific production scene operation failure, summary practice religion
Instruction, a main problem are exactly：Lack a degree of on-the-spot test before the trial operation of user production scene.
Under non-genuine on-the-spot test environment, may and true production scene have a various tiny different deviations, but this
A little deviations are likely to result in test result and the operation result under real scene environment is not quite identical, can produce the test of mistake
Conclusion, on-the-spot test of the software under real goal site environment cannot be substituted completely by non-at-scene test environment.Experience have shown that
The probability higher that new industrial software boundary value nearby malfunctions, with greater need for implementation border value testing.
In practice, the on-the-spot test of industrial software has many difficulties, and the method for on-the-spot test will be subject to user is actual to give birth to
The various constraints of industry business.Passive Test be frequently with method, but Passive Test more problems：It is difficult to active control test mesh
Mark and process, not design test case, testing efficiency it is universal it is relatively low, coverage rate is low etc..Tester with active it is of course desirable that surveyed
Method for testing, but actively test may produce the risk that causes the accident to user at scene, even sometimes legal input data also has
It may cause the appearance of accident, it is possible to serious loss is brought to produced on-site.Border during especially test is put into practice at the scene
The problem of being worth test method is even more serious, just valid data near boundary value and just invalid data easily causes production thing
Therefore.
The content of the invention
The present invention provides boundary value test method in a kind of industrial software on-the-spot test based on user's history data, is used for
The practical problems of existing boundary value test method at the scene in implementation process are solved, overcome each of common live Passive Test
Kind shortcoming, is such as difficult to active control test target and process, not design test case, and testing efficiency is generally relatively low, coverage rate is low
Deng having taken precautions against the just valid data in actively testing near boundary value and just invalid data easily cause the skills such as production accident
Art problem.
In order to solve the above technical problems, the technical solution adopted in the present invention is as follows：
Boundary value test method in a kind of industrial software on-the-spot test based on user's history data, step are as follows：
S1, obtains the historical production data storehouse of user.
S2, for some service parameter handled by tested software, sets the search criterion of invalid data, is produced from history
Continuous invalid data section is searched in database, the continuous invalid data section means that invalid data is not single isolated
Data point, number at least three of continuous invalid data, and the number lower limit set value of continuous data can be according to industry number
Increased according to experience adjustments.
S3, if can not find continuous invalid data section, goes to step S7.
S4, using first group of data of each continuous invalid data section found as initial point, in chronological order to going through
The data record of history Production database toward being pushed forward, finds valid data one by one, because industrial production is usually nominal situation,
Valid data can be generally pushed forward, if having found continuous valid data section, then by this continuous valid data section most
Later group data are as nearest valid data.
Assuming that findnA continuous invalid data section, for thei（I=1,2 ...,n) a continuous invalid data section carries out
Following processing：
It is concretely comprised the following steps：
S4.1, obtains the corresponding historical data of i-th of continuous invalid data section；
S4.2, using first group of invalid data point of i-th of continuous invalid data section as starting point, according to process time toward being pushed forward, is looked for
To continuous valid data section, and using last group of data in continuous valid data section as i-th of nearest valid data.
S5, using first group of data of each first continuous invalid data section behind valid data recently as non-recently
Method data.
The invalid data recently is that customer service scene is in history for some service parameter handled by tested software
Once closest to the invalid data of boundary value in the continuous invalid data section occurred；Continuous invalid data section refers to invalid data not
It is single isolated data point, number at least three of continuous invalid data, the number lower limit set value of continuous data can basis
Industry data experience adjustments increase；The valid data recently is for some service parameter handled by tested software, user
Closest to the data of boundary value in the continuous valid data section that business scene once occurred in history；Continuous valid data section refers to
Valid data is not single isolated data point, number at least three of continuous valid data, and the number lower limit of continuous data is set
Definite value can be increased according to industry data experience adjustments.
S6, selects the input data as border value testing from the nearest invalid data and nearest valid data obtained
Alternate data.The selection of alternate data is first to obtain to produce with nearest invalid data and the corresponding history of nearest valid data
Process data, the production status reflected according to relevant history production process data, analysis production status produce user
Whether influence degree and caused accident process are controllable, and choose nearest valid data and nearest invalid data risk is controllable
Alternate data of the part as the input data of on-the-spot test, and go to step S8.
S7, the historical data maximum and minimum value of statistical correlation parameter, using the maximum of historical data, minimum value as
The alternative input data of the border value testing of on-the-spot test.
S8, lists all nearest valid datas, nearest invalid data and step as on-the-spot test input data
The obtained input datas of S7, as the alternate data of the input data of live border value testing, and offer Subscriber Unit examination ＆ approval.
S9, for identified each group of test input data, finds these input datas from historical production data storehouse
Corresponding response process data, the comparison foundation as the test output data of tested software system（Or as desired output
Design considerations）.
The shortcomings that testing the present invention overcomes classical Passive Test and actively：Passive Test is normally produced dependent on user
Data, on-the-spot test efficiency is low, and test process is uncontrollable, it is difficult to carry out border value testing；Border in classical active test
Risk caused by value test method is possible is difficult to control, and is easy to cause accident, loss is brought to user.This new industrial software
Boundary value test method in on-the-spot test can control test target and test process on the premise of averting risks, existing
Field is implemented efficient, and the test output of tested new software system and the corresponding historical data of legacy system can be carried out
Compare（With the quality of the new software of exact evaluation）.In fact, the history big data of the produced on-site of industrial user is largely
The characteristics of personality of particular user business datum is reflected, boundary value obtained from the processing based on particular user production history data
Data, a portion are exactly exactly the data easily occurred, closer to the truth of user from the point of view of experience.
Brief description of the drawings
In order to illustrate more clearly about the embodiment of the present invention or technical scheme of the prior art, below will be to embodiment or existing
There is attached drawing needed in technology description to be briefly described, it should be apparent that, drawings in the following description are only this
Some embodiments of invention, for those of ordinary skill in the art, without creative efforts, can be with
Other attached drawings are obtained according to these attached drawings.
Fig. 1 is the simple flow chart of steps of the present invention.
Fig. 2 is the specific steps flow chart of the present invention.
Embodiment
Below in conjunction with the attached drawing in the embodiment of the present invention, the technical solution in the embodiment of the present invention is carried out clear, complete
Site preparation describes, it is clear that described embodiment is only part of the embodiment of the present invention, instead of all the embodiments.It is based on
Embodiment in the present invention, those of ordinary skill in the art are obtained all other under the premise of not making the creative labor
Embodiment, belongs to the scope of protection of the invention.
As shown in Figure 1, boundary value test method in a kind of industrial software on-the-spot test based on user's history data, step
It is as follows：
S1, obtains the historical production data storehouse of user.
S2, for some service parameter handled by tested software, sets the search criterion of invalid data, is produced from history
Continuous invalid data section is searched in database, the continuous invalid data section means that invalid data is not single isolated
Data point, number at least three of continuous invalid data, and the number lower limit set value of continuous data can be according to industry number
Increased according to experience adjustments.
S3, if can not find continuous invalid data section, goes to step S7.
S4, using first group of data of each continuous invalid data section found as initial point, in chronological order to going through
The data record of history Production database toward being pushed forward, finds valid data one by one, because industrial production is usually nominal situation,
Valid data can be generally pushed forward, if having found continuous valid data section, then by this continuous valid data section most
Later group data are as nearest valid data.
Assuming that findnA invalid data section, for i-th（I=1,2 ...,n) a continuous invalid data section carry out it is as follows
Processing：
It is concretely comprised the following steps：
S4.1, obtains the corresponding historical data of i-th of continuous invalid data section；
S4.2, using first group of invalid data point of i-th of continuous invalid data section as starting point, according to process time toward being pushed forward, is looked for
To continuous valid data section, and using last group of data in continuous valid data section as i-th group of nearest valid data.
S5, using first group of data of each first continuous invalid data section behind valid data recently as non-recently
Method data.
The invalid data recently is that customer service scene is in history for some service parameter handled by tested software
Once closest to the invalid data of boundary value in the continuous invalid data section occurred；Continuous invalid data section refers to invalid data not
It is single isolated data point, number at least three of continuous invalid data, the number lower limit set value of continuous data can basis
Industry data experience adjustments increase；The valid data recently is for some service parameter handled by tested software, user
Closest to the data of boundary value in the continuous valid data section that business scene once occurred in history；Continuous valid data section refers to
Valid data is not single isolated data point, number at least three of continuous valid data, and the number lower limit of continuous data is set
Definite value can be increased according to industry data experience adjustments.
S6, selects the input data as border value testing from the nearest invalid data and nearest valid data obtained
Alternate data.The selection of alternate data is first to obtain to produce with nearest invalid data and the corresponding history of nearest valid data
Process data, the production status reflected according to relevant history production process data, analysis production status produce user
Whether influence degree and caused accident process are controllable, and choose nearest valid data and nearest invalid data risk is controllable
Alternate data of the part as the input data of on-the-spot test, and go to step S8.
S7, the historical data maximum and minimum value of statistical correlation parameter, using the maximum of historical data, minimum value as
The alternative input data of the border value testing of on-the-spot test.
S8, lists all nearest valid datas, nearest invalid data and step as on-the-spot test input data
The obtained input datas of S7, the alternate data as the input data of live border value testing（Subscriber Unit is needed to examine in practice
Batch）.
S9, for identified each group of test input data, finds these input datas from historical production data storehouse
Corresponding response process data, the comparison foundation as the test output data of tested software system（Or as desired output
Design considerations）.
The key technology step of specific implementation is explained as follows, as shown in Figure 2：
(1) step 1：Find as far as possible in historical data near the data of boundary value.If boundary value search criterion is excessively harsh,
Qualified data can be reduced；Condition is relaxed, and qualified data may be excessive.When initial, search criterion, which is set, to use up
Amount is loose, makes that condition and range is progressively harsh, approaches boundary value in step 3.The setting of this certain boundary value querying condition is also
Consider the measurement error of hardware device.
(2) step 2：The data occurred in the historical data of actual device production near boundary value are uncertain, to be arranged
Except distortion data.Single invalid data may have a lot of reasons generation（Noise, distortion etc.）, so continuous data segment is needed,
Consecutive numbers is more difficult to look for more greatly, but cannot be too small（Continuous invalid data number lower limit is at least 3, rule of thumb, continuous data
Number lower limit set value can be increased according to industry data experience adjustments）.
(3) step 3：If the continuous invalid data section found is excessive, condition can be changed harsher so that data
Outcome quality higher.
(4) step 4：For each invalid data section, excavating all continuous process with this invalid data section has
The historical data of pass, the data of local time's section are as far as possible abundant, and data collection cycle is as far as possible short.The history number of process industrial production
According in storehouse include for many years can automatic data collection, can automatic data collection collection period be usually the second level, classification etc., in real time
Database is main source, needed in practice inspection data whether distortion（Measuring apparatus failure, noise jamming etc. cause）, but very
May without it is integrated it is relevant can not automatic data collection, can not automatic data collection（Such as artificial analysis data）Collection period
Time is generally longer, can be from Subscriber Unit in this case, it is necessary to find the corresponding relevant manually historical data base such as chemical examination
Go to excavate in the various data archivals of multiple departments, relevant information storehouse etc., the method that disparate databases preserve is different, need to be to original
The production history database of beginning is processed, and carries out targetedly cutting, integrated association process.
(5) step 5：From this invalid data section（It was likely to be accident condition at that time）Data are past one by one in chronological order
It is pushed forward, finds valid data（Because device production is usually nominal situation, valid data can be generally pushed forward）, but instantaneously
Valid data cannot function as nominal situation data, so the continuous process data before judging this valid data point whether
Legal, if continuous valid data section, last group of data therein are as nearest valid data.
(6) step 6：First group of data of the continuous invalid data section behind nearest valid data section can be used as non-recently
Method data.
(7) step 7：Under normal circumstances, the accident process data that process industry production scene occurs are generally seldom, but
These data are but very precious for on-the-spot test.Data mining cost may be higher, invalid data that can be as needed
Detail pointedly excavate, to reduce excavating cost and excavate as far as possible abundant.Here especially remind：Accident conditions,
Go into operation, stop work, process program handoff procedure is medium easily includes invalid data.
(8) step 8：Many commercial plant long-time stable normal operations, invalid data is seldom, if from existing whole
It can not find the invalid data of needs in production history database, then the historical data of manufacturing parameter can be counted in this case
Maximum and minimum value, these maximums, minimum values also largely reflect the number of this commercial plant actual production in fact
According to scope and business characteristic, can using the maximum and minimum value of historical data as the input data of border value testing design according to
According to.
(9) step 9：Can maximum, the corresponding historical process data of minimum value and corresponding work information, judgement be excavated make
To test input data.
(10) step 10：For each " nearest valid data " and " nearest invalid data "：Excavate corresponding history life
Process data is produced, according to the production status of relevant history production process data reflection, analyzes the influence degree to user's production
And whether caused accident process is controllable, judgement could be as the input data of on-the-spot test（In practice, user's production technology is needed
Expert participate in this step work, and need to by user's production safety department examine after can be as the input data of on-the-spot test）.Generally
In the case of, choose the input data of nearest valid data and the controllable nearest invalid data in part of risk as on-the-spot test.
(11) step 11：For the input data of fixed border value testing, this is found from production history database
Response process data corresponding to a little input datas, the comparison foundation as the test output data of new tested software system
（Or the design considerations as desired output）, so can carry out corresponding to comparison with the process data of old software processing, for phase
Same input data can more clearly quantify the Quality advance degree of the relatively old software of the new tested software system of comparative evaluation.
The foregoing is merely illustrative of the preferred embodiments of the present invention, is not intended to limit the invention, all essences in the present invention
With within principle, any modification, equivalent replacement, improvement and so on, should all be included in the protection scope of the present invention god.
Claims (4)
- A kind of 1. boundary value test method in industrial software on-the-spot test based on user's history data, it is characterised in that step It is as follows：S1, obtains the historical production data storehouse of user；S2, for some service parameter handled by tested software, sets the search criterion of invalid data, from historical production data Continuous invalid data section is searched in storehouse；S3, if can not find continuous invalid data section, goes to step S7；S4, using first group of data of each continuous invalid data section found as initial point, in chronological order gives birth to history The data record of database is produced one by one toward being pushed forward, valid data is searched, if having found continuous valid data section, then by this Last group of data of a continuous valid data section are as nearest valid data；S5, using first group of data of first group of continuous invalid data section behind nearest valid data time point as illegal recently Data；S6, for obtained each group of nearest valid data and nearest invalid data, excavates corresponding history production process number According to the production status reflected according to relevant history production process data, whether accident process is controllable caused by analysis, judges Could be as the input data of on-the-spot test, and go to step S8；S7, the historical data maximum and minimum value of statistical correlation parameter, using the maximum of historical data, minimum value as scene The input data of the border value testing of test；S8, is listed obtained by all nearest valid datas, nearest invalid data and step S7 as on-the-spot test input data The input data arrived, as the alternate data of the input data of live border value testing, submits a report asking for user's examination ＆ approval；S9, for identified each group of test input data, finds these input datas correspondence from historical production data storehouse Response process data, the comparison foundation as the test output data of tested software system.
- 2. boundary value test method in the industrial software on-the-spot test according to claim 1 based on user's history data, It is characterized in that, in step s 4, concretely comprise the following steps：Assuming that findnA continuous invalid data section, it is continuous illegal for the Data segment is handled as follows, wherein i=1, and 2 ...,n：S4.1, obtains the corresponding history production process data of i-th of continuous invalid data section；S4.2, using first group of invalid data point of i-th of continuous invalid data section as starting point, according to process time toward being pushed forward, is looked for To continuous valid data section, and using last group of data in continuous valid data section as i-th of nearest valid data.
- 3. boundary value test method in the industrial software on-the-spot test according to claim 1 based on user's history data, It is characterized in that, in step s 4, the invalid data recently is for some service parameter handled by tested software, user Closest to the invalid data of boundary value in the continuous invalid data section that business scene once occurred in history；Continuous invalid data section refers to Be that invalid data is not single isolated data point, number at least three of continuous invalid data, under the number of continuous data Limit setting value can be increased according to industry data experience adjustments；The valid data recently is for some handled by tested software Service parameter, closest to the data of boundary value in the continuous valid data section that customer service scene once occurred in history；It is continuous to close Method data segment refers to that valid data is not single isolated data point, number at least three of continuous valid data, consecutive numbers According to number lower limit set value can be increased according to industry data experience adjustments.
- 4. boundary value test method in the industrial software on-the-spot test according to claim 1 based on user's history data, It is characterized in that, in step s 6, the selection of alternate data is that first acquisition is opposite with nearest invalid data and nearest valid data The history production process data answered, the production status reflected according to relevant history production process data, analyzes production status It is whether controllable to the influence degree and caused accident process of user's production, and choose nearest valid data and nearest invalid data Alternate data of the controllable part of risk as the input data of on-the-spot test.
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Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108959102A (en) * | 2018-07-27 | 2018-12-07 | 百度在线网络技术（北京）有限公司 | Method and apparatus for generating test data, test application to be tested |
| CN109885504A (en) * | 2019-03-15 | 2019-06-14 | 网易（杭州）网络有限公司 | Test method, device, medium and the electronic equipment of recommender system |
| CN110334308A (en) * | 2019-04-23 | 2019-10-15 | 中国电子科技集团公司第二十四研究所 | A kind of calculation method optimizing bias condition in voltage sweep parameter testing |
| CN112180886A (en) * | 2020-10-29 | 2021-01-05 | 中原工学院 | Method for determining critical value of process parameter of specific production device in process industry |
| CN112566128A (en) * | 2021-03-01 | 2021-03-26 | 深圳市乙辰科技股份有限公司 | Wireless router management and control method based on mac address |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103034209A (en) * | 2012-12-18 | 2013-04-10 | 湖南大唐先一科技有限公司 | Discrimination method for on-line measured data accuracy |
| CN103914380A (en) * | 2014-03-26 | 2014-07-09 | 北京邮电大学 | Boundary value testing method and system in structure tests |
| CN105843743A (en) * | 2016-04-11 | 2016-08-10 | 南京邮电大学 | Method for verifying correctness of actual output result of special automatic test case |
-
2017
- 2017-12-26 CN CN201711430855.8A patent/CN107967218B/en active Active
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103034209A (en) * | 2012-12-18 | 2013-04-10 | 湖南大唐先一科技有限公司 | Discrimination method for on-line measured data accuracy |
| CN103914380A (en) * | 2014-03-26 | 2014-07-09 | 北京邮电大学 | Boundary value testing method and system in structure tests |
| CN105843743A (en) * | 2016-04-11 | 2016-08-10 | 南京邮电大学 | Method for verifying correctness of actual output result of special automatic test case |
Non-Patent Citations (1)
| Title |
|---|
| 赵一丁 等: "工业软件现场测试中的拆分及其测试数据设计", 《计算机工程与科学》 * |
Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108959102A (en) * | 2018-07-27 | 2018-12-07 | 百度在线网络技术（北京）有限公司 | Method and apparatus for generating test data, test application to be tested |
| CN109885504A (en) * | 2019-03-15 | 2019-06-14 | 网易（杭州）网络有限公司 | Test method, device, medium and the electronic equipment of recommender system |
| CN110334308A (en) * | 2019-04-23 | 2019-10-15 | 中国电子科技集团公司第二十四研究所 | A kind of calculation method optimizing bias condition in voltage sweep parameter testing |
| CN110334308B (en) * | 2019-04-23 | 2022-10-25 | 中国电子科技集团公司第二十四研究所 | Calculation method for optimizing bias condition in power supply scanning parameter test |
| CN112180886A (en) * | 2020-10-29 | 2021-01-05 | 中原工学院 | Method for determining critical value of process parameter of specific production device in process industry |
| CN112566128A (en) * | 2021-03-01 | 2021-03-26 | 深圳市乙辰科技股份有限公司 | Wireless router management and control method based on mac address |
| CN112566128B (en) * | 2021-03-01 | 2021-05-11 | 深圳市乙辰科技股份有限公司 | Wireless router management and control method based on mac address |
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