CN109902019A - A kind of automatic test stage division and system based on multidimensional weight - Google Patents

A kind of automatic test stage division and system based on multidimensional weight Download PDF

Info

Publication number
CN109902019A
CN109902019A CN201910182063.6A CN201910182063A CN109902019A CN 109902019 A CN109902019 A CN 109902019A CN 201910182063 A CN201910182063 A CN 201910182063A CN 109902019 A CN109902019 A CN 109902019A
Authority
CN
China
Prior art keywords
test
value
dimensional attribute
score value
case
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.)
Pending
Application number
CN201910182063.6A
Other languages
Chinese (zh)
Inventor
万书吉
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Beijing Urban Network Neighbor Information Technology Co Ltd
Beijing City Network Neighbor Technology Co Ltd
Original Assignee
Beijing City Network Neighbor Technology Co Ltd
Priority date (The priority date 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 date listed.)
Filing date
Publication date
Application filed by Beijing City Network Neighbor Technology Co Ltd filed Critical Beijing City Network Neighbor Technology Co Ltd
Priority to CN201910182063.6A priority Critical patent/CN109902019A/en
Publication of CN109902019A publication Critical patent/CN109902019A/en
Pending legal-status Critical Current

Links

Landscapes

  • Management, Administration, Business Operations System, And Electronic Commerce (AREA)

Abstract

The present invention provides a kind of automatic test stage division and system based on multidimensional weight, this includes: multiple dimensional attributes that selection influences each hierarchial test unit, configure the corresponding each score value index of the multiple dimensional attribute, periodically collect the corresponding each score value index of the multiple dimensional attribute, final calculate summarizes to obtain test case classification numerical value, automatic test is classified further according to test case classification numerical value, and then it realizes in automatic test course without manual configuration and change test case rank, automatically test case is classified, to greatly reduce the test deadline, and significantly improve the validity of test, greatly reduce maintenance cost;Further, by way of level weight calculation, the granularity of positioning is thinner, so that automatic test classification is more objective and efficient.

Description

A kind of automatic test stage division and system based on multidimensional weight
Technical field
The present invention relates to computer testing field more particularly to a kind of automatic test classification sides based on multidimensional weight Method and system.
Background technique
At present when carrying out automatic test based on test environment, automatic test hierarchy plan is in test code Identify test case rank, test grading operation is carried out by way of manual configuration, in this way each test case update or When person's test scope changes, it can all be related to the change of test case rank, need to identify or configure again, lead to maintenance cost It is relatively high.
In addition, the configuration of test case rank and mark are generally fixed and invariable, but the emphasis base of automatic test It is that can generate variation at any time in demand, environmental factor and test result, therefore, the operation other test case of fix level is very Difficulty covers the test zone of new change.Further, automatic test usually persistently carries out, and when test case product In sufficiently long situation of tired time, much stablize, is outmoded, or the test case not updated for a long time occupies largely The automatic test time and cost, be difficult to navigate to effective test case, and the only test case of effective operation, these Situation has all eventually led to the not high problem of automatic test actual efficiency.
Summary of the invention
This specification is proposed in order to provide a kind of base for overcoming the above problem or at least being partially solved the above problem In the automatic test stage division and system of multidimensional weight.
In a first aspect, the present invention provides a kind of automatic test stage division based on multidimensional weight,
Include: multiple dimensional attributes that selection influences each hierarchial test unit, it is right respectively to configure the multiple dimensional attribute The each score value index answered;Periodically collect the corresponding each score value index of the multiple dimensional attribute;Based on each score value Index calculates the corresponding weighted value of each hierarchial test unit;The corresponding weighted value of each hierarchial test unit is defined, is based on The weighted value of the definition and the corresponding weighted value of calculated each hierarchial test unit, summarize each level out The test case that test cell determines jointly is classified numerical value;Numerical value is classified according to the test case to carry out automatic test Classification.
Second aspect, the present invention provide a kind of automatic test hierarchy system based on multidimensional weight, comprising: configuration mould It is corresponding each to configure the multiple dimensional attribute for selecting to influence multiple dimensional attributes of each hierarchial test unit for block A score value index;Regular collection module, for periodically collecting the corresponding each score value index of the multiple dimensional attribute;Level Weighted calculation module calculates the corresponding weighted value of each hierarchial test unit for being based on each score value index;Point Value of series summarizing module, for defining the corresponding weighted value of each hierarchial test unit, based on the weighted value of the definition, and The corresponding weighted value of the calculated each hierarchial test unit, summarizes the survey that each hierarchial test unit determines jointly out Example on probation is classified numerical value;Test grading module divides automatic test for being classified numerical value according to the test case Grade.
The third aspect, the present invention provide a kind of server, including processor and memory: the memory is for storing Execute the program of the above method;The processor is configured to for executing the program stored in the memory.
Fourth aspect, the present invention provide a kind of computer readable storage medium, are stored with computer program, feature The step of being, preceding claim method realized when which is executed by processor.
Above scheme according to the present invention influences multiple dimensional attributes of each hierarchial test unit by selection, configures institute The corresponding each score value index of multiple dimensional attributes is stated, the corresponding each score value of the multiple dimensional attribute is periodically collected Index, final calculate summarizes to obtain test case classification numerical value, further according to test case classification numerical value to automatic test It is classified, and then is realized without manual configuration and change test case rank in automatic test course, automatically to survey Example on probation is classified, to greatly reduce the test deadline, and is significantly improved the validity of test, is greatly reduced Maintenance cost;Further, by way of level weight calculation, the granularity of positioning is thinner, so that automation is surveyed Examination classification is more objective and efficient.
The above description is only an overview of the technical scheme of the present invention, in order to better understand the technical means of the present invention, And can be implemented in accordance with the contents of the specification, the following is a detailed description of the preferred embodiments of the present invention and the accompanying drawings.
Detailed description of the invention
The attached drawing for constituting a part of the invention is used to provide further understanding of the present invention, and of the invention is schematic Examples and descriptions thereof are used to explain the present invention, does not constitute improper limitations of the present invention.In the accompanying drawings:
Fig. 1 shows the process of the automatic test stage division according to an embodiment of the invention based on multidimensional weight Figure.
Fig. 2 shows the structures of the automatic test hierarchy system according to an embodiment of the invention based on multidimensional weight Schematic diagram.
Specific embodiment
This specification technical solution is described in detail below by attached drawing and specific embodiment, it should be understood that this Specific features in specification embodiment and embodiment are the detailed description to this specification technical solution, rather than right The restriction of this specification technical solution, in the absence of conflict, the technical characteristic in this specification embodiment and embodiment It can be combined with each other.
The terms "and/or", only a kind of incidence relation for describing affiliated partner, indicates may exist three kinds Relationship, for example, A and/or B, can indicate: individualism A exists simultaneously A and B, these three situations of individualism B.In addition, Character "/" herein, typicallys represent the relationship that forward-backward correlation object is a kind of "or".
Embodiment
Referring to FIG. 1, the present invention is based on one embodiment of the automatic test stage division of multidimensional weight, comprising:
Step S110, selection influence multiple dimensional attributes of each hierarchial test unit, configure the multiple dimensional attribute point Not corresponding each score value index.
Wherein, each hierarchial test unit may include: test item, test class and/or test case.Further Ground, test item may include test class, and test class may include test case, therefore each hierarchial test unit is layer-by-layer Cover, in this way for each hierarchial test unit can all have an impact its own multiple dimensional attributes it is corresponding, different levels survey Trying the corresponding dimensional attribute of unit can be independent each other, but can also share identical dimensional attribute.According to test cell Level divide after, the weight summarized to subsequent totality is weighted, and the granularity of weighted calculation is thinner.
In one embodiment, selection is on the influential multiple dimensions of test item, test class and test case difference After attribute, the corresponding corresponding score value index for influencing each dimensional attribute that test item, test class and test case are divided of configuration. Each dimensional attribute has the numerical value of itself to be characterized, and in addition configures the score value index of corresponding dimensional attribute.Furthermore it is possible to shape At in dimensional attribute allocation list deposit database.Optional dimensional attribute citing may include: test percent of pass, test execution frequency Degree, test code update frequency, newest execution time etc..
Further, the score value index of the corresponding configuration of dimensional attribute be characterize significance level that this influences test cell with The correlation metric of data trend illustrates such in a way for example, test percent of pass is lower for testing percent of pass The degree that test needs to pay close attention to is higher, and the probability for needing to be performed is higher, so according to how much configuration score values of test percent of pass Index is exemplified as, and the configuration score value that the configuration score value index that percent of pass own value is 0-50% is 100,50%-80% refers to The configuration score value index for being designated as 70,80%-100% is 30.The value that score value index allocation is not fixed, can be according to business needs It is adjusted.
Step S120 periodically collects the corresponding each score value index of the multiple dimensional attribute.
Wherein, the multiple dimensional attribute own value variation is periodically collected, if there is dimensional attribute own value occurs The corresponding score value index of the dimensional attribute is then accordingly dynamically modified in variation.
Further, it can periodically set as unit of day, Huo Zheyue, year are unit, are set by testing requirement. Furthermore it is possible to specific timed task is configured, as the information for periodically collecting each dimensional attribute itself, such as operation daily Timed task is collected, and checks whether each dimensional attribute own value changes after the completion of collecting, so that dynamic is modified The corresponding score value index of changed dimensional attribute.(the percent of pass own value 0- for testing percent of pass dimensional attribute 50% be set as 100,50%-80% be set as being set as 30.) for 70,80%-100%, daily timed collection passes through Rate own value keeps the score value index of corresponding percent of pass constant if percent of pass own value does not change;If Last percent of pass is 30%, and it is 100 that dimensional attribute, which corresponds to score value index, but newest percent of pass own value becomes 90%, changed, it is therefore desirable to which the score value index of percent of pass is updated to 30.It can be seen that the score value of dimensional attribute refers to Mark is dynamically generated, and embodiment is situation after newest test execution.
Step S130 is based on each score value index, calculates the corresponding weighted value of each hierarchial test unit.
Further, the corresponding dimension weight of each score value index is set, respectively in connection with each score value index, is obtained To each dimension weighted value;According to the corresponding each dimensional attribute of test cells at different levels, it is corresponding to summarize test cells at different levels respectively Each dimension weighted value, to obtain the corresponding weighted value of test cells at different levels.
Wherein, dimension weight can need to be defined according to specific business.For example predict the percent of pass dimension of a certain test It is larger to spend properties affect, then the numerical value for the percent of pass weight setting being correspondingly arranged just should be bigger, dimensional attribute may include but It is not limited to, test percent of pass, test execution frequency, test code update frequency, newest execution time etc., these dimensions power The numerical value setting of weight can need to define and add according to business, for example the dimension weight of test percent of pass is 100, test The dimension weight for executing frequency is set as 80 etc..
It in one embodiment, can be according to test item, test class and the corresponding each dimension of test case Attribute calculates separately to obtain test item, test class and the corresponding weighted value of test case.
Further, the calculating can be according to following formula:
Weighted value x=k1*p1+k2*p2+ ... kn*pn,
Wherein, k1, k2 ..., kn are the score value indexs of each dimensional attribute, and p1, p2 ..., pn is each dimensional attribute pair The dimension weight answered.
After calculating based on above-mentioned formula, each hierarchial test unit corresponding weighted value x1, x2 ..., xn are obtained.With three For the test cell of level, it is divided into test item, test class and test case.By it is above-mentioned summarize calculating after, respectively To test item weighted value, test case weighted value in the weighted value and test class of test class in test item.
Step S140 defines the corresponding weighted value of each hierarchial test unit, based on the weighted value of the definition, Yi Jisuo The corresponding weighted value of calculated each hierarchial test unit is stated, the test that each hierarchial test unit determines jointly out is summarized Use-case is classified numerical value.
Wherein, weighted value and calculated each hierarchial test unit based on the definition it is corresponding plus Weight summarizes the test case classification numerical value that each hierarchial test unit determines jointly out.It is needed to define weighted value according to business, For example, if current test item be it is most important in all items, what be can be set is very high, such as 100, if project is not It is important to can be set 10.
Specifically, defining test item, test class and test case respectively influences the power of size on integrated testability use-case Weight values finally obtain the test case point determined jointly by the test item, test class and test case after further summarizing Value of series.
Further summarizing test case classification numerical value herein can calculate according to following formula:
Y=x1*w1+x2*w2+ ... xn*wn, wherein x1, x2 ..., xn are the weighted value of each hierarchial test unit, such as The weighted value of test item, test class and test case, w1, w2 ..., wn are the power of each hierarchial test unit defined respectively Weight values, y are that test case is classified numerical value.
Thus the totality being calculated summarizes to be weighted to obtain by the weight of each hierarchial test unit, so that last survey The granularity of example classification numerical value on probation is thinner.
Step S150 is classified numerical value according to the test case and is classified to automatic test.
Wherein, score value sequence is carried out to test case classification numerical value, it is high to choose classification numerical value by preset threshold Test case, to be classified to automatic test.
Further, the high multiple test cases of classification numerical value are chosen by preset threshold and forms use-case set to be tested; The use-case set to be tested is set as high priority and carries out automatic test.
Specifically, score value sequence is carried out after obtaining test case classification numerical value, after sequence, passes through the threshold pre-defined Value chooses the high formation use-case set to be tested of classification numerical value.For example, choosing 60% test case forms set of uses case to be tested It closes, tester can need to adjust at any time according to business the size of threshold value.
As an embodiment, after being classified numerical value according to the test case and being classified to automatic test, Further include: it generates in test report deposit database, the New Set occurred in statistical test, the dimension alternative as test case Spend attribute.
Use-case to be tested all in the use-case set to be tested is executed, the survey of this corresponding automatic test is generated Examination report, while test report is carried out to be convenient for later data Macro or mass analysis in statistics deposit database.When statistical test report It, can also be using new index as the dimensional attribute of the spare selection of test case when accusing now new index.
Referring to FIG. 2, the present invention is based on one embodiment of the automatic test hierarchy system of multidimensional weight, comprising:
Configuration module 210 configures the multiple dimension for selecting to influence multiple dimensional attributes of each hierarchial test unit Spend the corresponding each score value index of attribute;Regular collection module 220, for periodically collecting the multiple dimensional attribute pair The each score value index answered;Level weighted calculation module 230 calculates each hierarchial test for being based on each score value index The corresponding weighted value of unit;It is classified numerical value summarizing module 240, for defining the corresponding weighted value of each hierarchial test unit, Weighted value based on the definition and the corresponding weighted value of calculated each hierarchial test unit, summarize each out The test case that hierarchial test unit determines jointly is classified numerical value;Test grading module 250, for according to the test case Classification numerical value is classified automatic test.
Wherein, each hierarchial test unit includes: test item, test class and/or test case.Further, it surveys Examination project may include test class, and test class may include test case, therefore each hierarchial test unit is successively to cover , in this way for each hierarchial test unit can all have an impact its own multiple dimensional attributes it is corresponding, different levels test is single The corresponding dimensional attribute of member can be independent each other, but can also share identical dimensional attribute.According to the layer of test cell After grade divides, the weight summarized to subsequent totality is weighted, and the granularity of weighted calculation is thinner.
Further, the configuration module 210 is also used to select to have test item, test class and test case respectively The multiple dimensional attributes influenced, corresponding configuration correspond to each dimensional attribute of influence test item, test class and test case point Score value index.Each dimensional attribute has the numerical value of itself to be characterized, and in addition configures the score value index of corresponding dimensional attribute. Furthermore it is possible to be formed in dimensional attribute allocation list deposit database.The citing of optional dimensional attribute may include: test percent of pass, Test execution frequency, test code update frequency, newest execution time etc..
Further, the score value index of the corresponding configuration of dimensional attribute be characterize significance level that this influences test cell with The correlation metric of data trend illustrates such in a way for example, test percent of pass is lower for testing percent of pass The degree that test needs to pay close attention to is higher, and the probability for needing to be performed is higher, so according to how much configuration score values of test percent of pass Index is exemplified as, and the configuration score value that the configuration score value index that percent of pass own value is 0-50% is 100,50%-80% refers to The configuration score value index for being designated as 70,80%-100% is 30.The value that score value index allocation is not fixed, can be according to business needs It is adjusted.
Wherein, the regular collection module 220, is further used for, and periodically collects the multiple dimensional attribute own value Variation then accordingly dynamically modifies the corresponding score value index of the dimensional attribute if there is dimensional attribute own value changes.
Further, it can periodically set as unit of day, Huo Zheyue, year are unit, are set by testing requirement. Furthermore it is possible to specific timed task is configured, as the information for periodically collecting each dimensional attribute itself, such as operation daily Timed task is collected, and checks whether each dimensional attribute own value changes after the completion of collecting, so that dynamic is modified The corresponding score value index of changed dimensional attribute.(the percent of pass own value 0- for testing percent of pass dimensional attribute 50% be set as 100,50%-80% be set as being set as 30.) for 70,80%-100%, daily timed collection passes through Rate own value keeps the score value index of corresponding percent of pass constant if percent of pass own value does not change;If Last percent of pass is 30%, and it is 100 that dimensional attribute, which corresponds to score value index, but newest percent of pass own value becomes 90%, changed, it is therefore desirable to which the score value index of percent of pass is updated to 30.It can be seen that the score value of dimensional attribute refers to Mark is dynamically generated, and embodiment is situation after newest test execution.
Wherein, the level weighted calculation module 230, is further used for, and sets the corresponding dimension power of each score value index Weight, respectively in connection with each score value index, obtains each dimension weighted value;According to the corresponding each dimension of test cells at different levels Spend attribute, summarize the corresponding each dimension weighted value of test cells at different levels respectively, thus obtain test cells at different levels it is corresponding plus Weight.
Specifically, dimension weight can need to be defined according to specific business.For example predict the percent of pass of a certain test Dimensional attribute is affected, then the numerical value for the percent of pass weight setting being correspondingly arranged just should be bigger, and dimensional attribute may include But it is not limited to, test percent of pass, test execution frequency, test code update frequency, newest execution time etc., these dimensions The numerical value setting of weight can need to define and add according to business, for example the dimension weight of test percent of pass is 100, is surveyed The dimension weight that examination executes frequency is set as 80 etc..
The level weighted calculation module 230, is further used for, according to test item, test class and test case difference Corresponding each dimensional attribute summarizes to obtain test item, test class and the corresponding weighted value of test case respectively.
Further, the calculating can be according to following formula:
Weighted value x=k1*p1+k2*p2+ ... kn*pn,
Wherein, k1, k2 ..., kn are the score value indexs of each dimensional attribute, and p1, p2 ..., pn is each dimensional attribute pair The dimension weight answered.
After calculating based on above-mentioned formula, each hierarchial test unit corresponding weighted value x1, x2 ..., xn are obtained.With three For the test cell of level, it is divided into test item, test class and test case.By it is above-mentioned summarize calculating after, respectively To test item weighted value, test case weighted value in the weighted value and test class of test class in test item.
Wherein, the classification numerical value summarizing module 240, is further used for, based on the weighted value of the definition, Yi Jisuo The corresponding weighted value of calculated each hierarchial test unit is stated, the test that each hierarchial test unit determines jointly out is summarized Use-case is classified numerical value.It is needed to define weighted value according to business, for example, if current test item is most important in all items , what be can be set is very high, such as 100, if project is inessential to can be set 10.
Specifically, defining test item, test class and test case respectively influences the power of size on integrated testability use-case Weight values finally obtain the test case point determined jointly by the test item, test class and test case after further summarizing Value of series.
Further summarizing test case classification numerical value herein can calculate according to following formula:
Y=x1*w1+x2*w2+ ... xn*wn, wherein x1, x2 ..., xn are the weighted value of each hierarchial test unit, such as The weighted value of test item, test class and test case, w1, w2 ..., wn are the power of each hierarchial test unit defined respectively Weight values, y are that test case is classified numerical value.
Thus the totality being calculated summarizes to be weighted to obtain by the weight of each hierarchial test unit, so that last survey The granularity of example classification numerical value on probation is thinner.
Wherein, the diversity module 250, is further used for, and carries out score value sequence to test case classification numerical value, The high test case of classification numerical value is chosen by preset threshold, to be classified to automatic test.
Further, the diversity module 250, is also used to, and chooses the high multiple tests of classification numerical value by preset threshold Use-case forms use-case set to be tested;The use-case set to be tested is set as high priority and carries out automatic test.
Specifically, score value sequence is carried out after obtaining test case classification numerical value, after sequence, passes through the threshold pre-defined Value chooses the high formation use-case set to be tested of classification numerical value.For example, choosing 60% test case forms set of uses case to be tested It closes, tester can need to adjust at any time according to business the size of threshold value.
As an embodiment, the system also includes: report statistical module 260, for generating test report deposit In database, the New Set occurred in statistical test, the dimensional attribute alternative as test case.
Use-case to be tested all in the use-case set to be tested is executed, the survey of this corresponding automatic test is generated Examination report, while test report is carried out to be convenient for later data Macro or mass analysis in statistics deposit database.When statistical test report It, can also be using new index as the dimensional attribute of the spare selection of test case when accusing now new index.
Based on this understanding, server relevant to present invention realization one embodiment of the above method comprising processing Device and memory, memory are configured to store the processing routine of each step of an embodiment of the above method, and processor is then matched It sets for executing the program stored in the memory.
Based on this understanding, the present invention realizes all or part of the process in an embodiment of the above method, can also be with Relevant hardware is instructed to complete by computer program, the computer program can be stored in one and computer-readable deposit In storage media, the computer program is when being executed by processor, it can be achieved that the step of above-mentioned each embodiment of the method.Wherein, institute Stating computer program includes computer program code, and the computer program code can be source code form, object identification code shape Formula, executable file or certain intermediate forms etc..The computer-readable medium may include: that can carry the computer Any entity or device of program code, medium, USB flash disk, mobile hard disk, magnetic disk, CD, computer storage, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), electric carrier signal, Telecommunication signal and software distribution medium etc..It should be noted that the content that the computer-readable medium includes can basis Legislation and the requirement of patent practice carry out increase and decrease appropriate in jurisdiction, such as in certain jurisdictions, according to legislation And patent practice, computer-readable medium do not include electric carrier signal and telecommunication signal.
Although preferred embodiments of the present invention have been described, once a person skilled in the art knows basic wounds The property made concept, then additional changes and modifications may be made to these embodiments.It is wrapped so the following claims are intended to be interpreted as It includes preferred embodiment and falls into all change and modification of this specification range.Obviously, those skilled in the art can be right The present invention carries out various modification and variations without departing from the spirit and scope of the present invention.If in this way, these modifications of the invention Within the scope of the claims of the present invention and its equivalent technology with modification, then the present invention be also intended to encompass these change and Including modification.

Claims (12)

1. a kind of automatic test stage division based on multidimensional weight characterized by comprising
Selection influences multiple dimensional attributes of each hierarchial test unit, and it is each point corresponding to configure the multiple dimensional attribute It is worth index;
Periodically collect the corresponding each score value index of the multiple dimensional attribute;
Based on each score value index, the corresponding weighted value of each hierarchial test unit is calculated;
The corresponding weighted value of each hierarchial test unit is defined, weighted value and calculated each layer based on the definition The corresponding weighted value of grade test cell summarizes the test case classification numerical value that each hierarchial test unit determines jointly out;
Numerical value is classified according to the test case to be classified automatic test.
2. the method as described in claim 1, which is characterized in that described periodically to collect the multiple dimensional attribute corresponding each Score value index further comprises:
The variation of the multiple dimensional attribute own value is periodically collected, if there is dimensional attribute own value changes, then phase The corresponding score value index of the dimensional attribute should dynamically be modified.
3. the method according to claim 1, which is characterized in that be based on each score value index, calculate at different levels The corresponding weighted value of test cell further comprises:
The corresponding dimension weight of each score value index is set, respectively in connection with each score value index, obtains each dimension weighting Value;
According to the corresponding each dimensional attribute of test cells at different levels, summarize the corresponding each dimension weighting of test cells at different levels respectively Value, to obtain the corresponding weighted value of test cells at different levels.
4. the method as described in claim 1, which is characterized in that according to the test case be classified numerical value to automatic test into Row classification further comprises:
Score value sequence is carried out to test case classification numerical value, the high test case of classification numerical value is chosen by preset threshold, To be classified to automatic test, wherein
The high multiple test cases of classification numerical value, which are chosen, by preset threshold forms use-case set to be tested;
The use-case set to be tested is set as high priority and carries out automatic test.
5. method as claimed in claim 4, which is characterized in that according to the test case be classified numerical value to automatic test into After row classification, further comprise:
It generates in test report deposit database, the New Set occurred in statistical test, the dimension category alternative as test case Property.
6. a kind of automatic test hierarchy system based on multidimensional weight characterized by comprising
Configuration module configures the multiple dimensional attribute point for selecting to influence multiple dimensional attributes of each hierarchial test unit Not corresponding each score value index;
Regular collection module, for periodically collecting the corresponding each score value index of the multiple dimensional attribute;
Level weighted calculation module, for calculating based on each score value index, each hierarchial test unit is corresponding to be added Weight;
It is classified numerical value summarizing module, for defining the corresponding weighted value of each hierarchial test unit, based on the weighted value of the definition, And the corresponding weighted value of the calculated each hierarchial test unit, summarize what each hierarchial test unit out determined jointly Test case is classified numerical value;
Test grading module is classified automatic test for being classified numerical value according to the test case.
7. system as claimed in claim 6, which is characterized in that the regular collection module is further used for,
The variation of the multiple dimensional attribute own value is periodically collected, if there is dimensional attribute own value changes, then phase The corresponding score value index of the dimensional attribute should dynamically be modified.
8. such as the described in any item systems of claim 6-7, which is characterized in that the level weighted calculation module is further used In,
The corresponding dimension weight of each score value index is set, respectively in connection with each score value index, obtains each dimension weighting Value;
According to the corresponding each dimensional attribute of test cells at different levels, summarize the corresponding each dimension weighting of test cells at different levels respectively Value, to obtain the corresponding weighted value of test cells at different levels.
9. system as claimed in claim 6, which is characterized in that the diversity module is further used for,
Score value sequence is carried out to test case classification numerical value,
The high multiple test cases of classification numerical value, which are chosen, by preset threshold forms use-case set to be tested, it will be described to be measured on probation Example set is set as high priority and carries out automatic test.
10. system as claimed in claim 9, which is characterized in that further include:
Report statistical module, for generating in test report deposit database, the New Set occurred in statistical test, as test The alternative dimensional attribute of use-case.
11. a kind of server, which is characterized in that including processor and memory:
The memory is used to store the program that perform claim requires any one of 1 to 5 the method;
The processor is configured to for executing the program stored in the memory.
12. a kind of computer readable storage medium, is stored with computer program, which is characterized in that the program is held by processor The step of any one of claims 1 to 5 the method is realized when row.
CN201910182063.6A 2019-03-11 2019-03-11 A kind of automatic test stage division and system based on multidimensional weight Pending CN109902019A (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN201910182063.6A CN109902019A (en) 2019-03-11 2019-03-11 A kind of automatic test stage division and system based on multidimensional weight

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN201910182063.6A CN109902019A (en) 2019-03-11 2019-03-11 A kind of automatic test stage division and system based on multidimensional weight

Publications (1)

Publication Number Publication Date
CN109902019A true CN109902019A (en) 2019-06-18

Family

ID=66946998

Family Applications (1)

Application Number Title Priority Date Filing Date
CN201910182063.6A Pending CN109902019A (en) 2019-03-11 2019-03-11 A kind of automatic test stage division and system based on multidimensional weight

Country Status (1)

Country Link
CN (1) CN109902019A (en)

Cited By (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN110597729A (en) * 2019-09-20 2019-12-20 中国银行股份有限公司 Dimension-based pressure testing method, device and system
CN111047150A (en) * 2019-11-22 2020-04-21 浙江蓝卓工业互联网信息技术有限公司 Method, device and system for calculating stability rate of process industrial device
CN111209208A (en) * 2020-01-14 2020-05-29 网易(杭州)网络有限公司 Test scheme generation method, device, equipment and storage medium
CN112580887A (en) * 2020-12-25 2021-03-30 百果园技术(新加坡)有限公司 Weight determination method, device and equipment for multi-target fusion evaluation and storage medium
CN114185810A (en) * 2021-12-30 2022-03-15 北京网太科技发展有限公司 Test case design method, device, management system and medium
CN116148641A (en) * 2023-04-20 2023-05-23 长鑫存储技术有限公司 Method, apparatus, computer device and readable storage medium for chip classification
CN118606218A (en) * 2024-08-07 2024-09-06 恒生电子股份有限公司 Test case selection method and device

Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN105528288A (en) * 2015-12-01 2016-04-27 深圳市迪菲特科技股份有限公司 Software testing method and apparatus
CN108153661A (en) * 2016-12-05 2018-06-12 腾讯科技(深圳)有限公司 The method and apparatus of implementation of test cases
CN108268366A (en) * 2016-12-30 2018-07-10 腾讯科技(深圳)有限公司 Test example executing method and device

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN105528288A (en) * 2015-12-01 2016-04-27 深圳市迪菲特科技股份有限公司 Software testing method and apparatus
CN108153661A (en) * 2016-12-05 2018-06-12 腾讯科技(深圳)有限公司 The method and apparatus of implementation of test cases
CN108268366A (en) * 2016-12-30 2018-07-10 腾讯科技(深圳)有限公司 Test example executing method and device

Non-Patent Citations (3)

* Cited by examiner, † Cited by third party
Title
徐宏哲等: "《21世纪大学计算机专业教材 UML自动化测试技术》", 31 August 2006, 西安交通大学出版社 *
林青霞: "基于One-test-at-a-time策略的组合测试优先级排序方法的研究", 《中国优秀博硕士学位论文全文数据库(硕士) 信息科技辑》 *
谭武梁: "《IT项目管理》", 31 August 2007, 中国铁道出版社 *

Cited By (13)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN110597729A (en) * 2019-09-20 2019-12-20 中国银行股份有限公司 Dimension-based pressure testing method, device and system
CN110597729B (en) * 2019-09-20 2023-10-24 中国银行股份有限公司 Pressure testing method, device and system based on dimension
CN111047150A (en) * 2019-11-22 2020-04-21 浙江蓝卓工业互联网信息技术有限公司 Method, device and system for calculating stability rate of process industrial device
CN111209208B (en) * 2020-01-14 2023-05-16 网易(杭州)网络有限公司 Test scheme generation method, device, equipment and storage medium
CN111209208A (en) * 2020-01-14 2020-05-29 网易(杭州)网络有限公司 Test scheme generation method, device, equipment and storage medium
CN112580887B (en) * 2020-12-25 2023-12-01 百果园技术(新加坡)有限公司 Weight determination method, device, equipment and storage medium for multi-target fusion evaluation
CN112580887A (en) * 2020-12-25 2021-03-30 百果园技术(新加坡)有限公司 Weight determination method, device and equipment for multi-target fusion evaluation and storage medium
CN114185810A (en) * 2021-12-30 2022-03-15 北京网太科技发展有限公司 Test case design method, device, management system and medium
CN114185810B (en) * 2021-12-30 2024-10-15 北京网太科技发展有限公司 Test case design method, device, management system and medium
CN116148641A (en) * 2023-04-20 2023-05-23 长鑫存储技术有限公司 Method, apparatus, computer device and readable storage medium for chip classification
CN116148641B (en) * 2023-04-20 2023-09-19 长鑫存储技术有限公司 Method, apparatus, computer device and readable storage medium for chip classification
CN118606218A (en) * 2024-08-07 2024-09-06 恒生电子股份有限公司 Test case selection method and device
CN118606218B (en) * 2024-08-07 2024-12-03 恒生电子股份有限公司 Test case selection method and device

Similar Documents

Publication Publication Date Title
CN109902019A (en) A kind of automatic test stage division and system based on multidimensional weight
Rai et al. A survey of clustering techniques
Smith et al. Structure and dynamics of the global economy: network analysis of international trade 1965–1980
Müller et al. Relevant subspace clustering: Mining the most interesting non-redundant concepts in high dimensional data
Zhou et al. A robust clustering algorithm based on the identification of core points and KNN kernel density estimation
US12014436B2 (en) Intellectual-property landscaping platform
CN103119582A (en) Reducing the dissimilarity between a first multivariate data set and a second multivariate data set
US12073479B2 (en) Intellectual-property landscaping platform
Mohammadi et al. An improved evolutionary algorithm for handling many-objective optimization problems
Khoshnevis et al. Prioritizing ground‐motion validation metrics using semisupervised and supervised learning
CN113095680A (en) Evaluation index system and construction method of electric power big data model
Jiang et al. An efficient differential memetic algorithm for clustering problem
CN117437001A (en) Target object index data processing method and device and computer equipment
CN113988670A (en) Comprehensive enterprise credit risk early warning method and system
CN115712836A (en) Interactive iterative modeling method
US20240370954A1 (en) Intellectual-property landscaping platform
Fitriani et al. Growth Externalities on the Environmental Quality Index of East Java Indonesia, Spatial Econometrics Model of STIRPAT
Kay Mahamaneerat et al. Domain‐concept association rules mining for large‐scale and complex cellular manufacturing tasks
CN115587762A (en) Model classification management method and device
Koch et al. MOCS: Multi-objective clustering selection evolutionary algorithm
CN118114093B (en) Main data processing method, system, equipment and storage medium
CN118229117B (en) Territorial space planning implementation monitoring model
Rajagukguk et al. Optimizing Earthquake Forecast Through Clustering: K-Means and DBSCAN Approaches
Zhou et al. DdBB: A data-driven framework for building energy use benchmarking
CN117454141A (en) Method and device for generating credit rating cause of user

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
RJ01 Rejection of invention patent application after publication

Application publication date: 20190618

RJ01 Rejection of invention patent application after publication