CN106598585A - Scoring-driven fast service matching and aggregating method in cloud environment - Google Patents
Scoring-driven fast service matching and aggregating method in cloud environment Download PDFInfo
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- CN106598585A CN106598585A CN201611123482.5A CN201611123482A CN106598585A CN 106598585 A CN106598585 A CN 106598585A CN 201611123482 A CN201611123482 A CN 201611123482A CN 106598585 A CN106598585 A CN 106598585A
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F8/00—Arrangements for software engineering
- G06F8/10—Requirements analysis; Specification techniques
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/90—Details of database functions independent of the retrieved data types
- G06F16/95—Retrieval from the web
- G06F16/953—Querying, e.g. by the use of web search engines
- G06F16/9535—Search customisation based on user profiles and personalisation
Abstract
The invention discloses a scoring-driven fast service matching and aggregating method in a cloud environment. The method comprises the following steps: decomposing target software service into multiple target service members; searching and matching to obtain a candidate service member of each target service member in the cloud environment; scoring and sorting the candidate service members; selecting the candidate service members, and aggregating the same to form primary target software service; and performing performance detection and correction on the primary target software service to obtain final primary target software service. According to the scoring-driven fast service matching and aggregating method disclosed by the invention, the target software service is divided into multiple target service members, the necessary service members are searched, screen, aggregated and detected in the cloud environment to accomplish the fast matching and aggregating of the target software service in the cloud environment, therefore by adoption of the method, the software service development efficiency in the cloud environment can be greatly improved, and meanwhile the method is simple, better in feasibility and high in reliability.
Description
Technical field
Present invention relates particularly to the service Rapid matching and polymerization of driving of scoring under a kind of cloud environment.
Background technology
With the development of economic technology and becoming increasingly popular for information technology, the extensively and profoundly production of people of " cloud " technology
And life, it is that people bring endless facility.So-called " cloud " technology, that is, refer to hardware, soft in wide area network or LAN
The series resources such as part, network are united, and realize calculating, storage, process and a kind of shared trustship technology of data.In cloud ring
Under border, user can obtain the resource of magnanimity, and can obtain the service of magnanimity.
Likewise, with the development of economic technology, the concept of " customized " has also progressively been rooted in the hearts of the people, particularly right
In personalization level is higher and the larger Software Industry of function differenceization, the differentiation software of " customized " is with its interface customizing
The significantly advantage such as change, customizing functions, receives the favor of users.
But, Software Industry has welcome " customized " the change epoch, has equally also welcome huge problem.Customized software
Be in fashion, it is meant that the acceptance level relative reduction of versatility software, equally also imply that the prolongation of software development cycle：Because
Developer is needed for per a software, redesigning framework, the service of software, data of software of software etc., and this is caused
The construction cycle of software is obviously prolonged, and greatly have impact on the development efficiency of software.
The content of the invention
It is an object of the invention to provide under a kind of cloud environment, software service development efficiency can greatly be improved, while
Method is simple, the service Rapid matching and polymerization of driving of scoring under the preferable cloud environment of feasibility.
Score under this cloud environment that the present invention is provided the service Rapid matching and polymerization of driving, including following step
Suddenly：
S1. it is N number of destination service component by target software service decomposition according to the characteristic of target software service, and determines
The parameter of each destination service component and requirement；
S2. based on cloud computing, the N number of destination service component searched for required for matching step S1 under cloud environment is obtained
To M candidate service component of each destination service component；
M candidate service component of each the destination service component for S3. obtaining to step S2 scores；
S4. the appraisal result for being obtained according to step S3, arranges M candidate service component of each destination service component
Sequence；
S5. according to the ranking results of the candidate service component of each destination service component, in each destination service component
A candidate service component is chosen in candidate service component, and the candidate service component of all selections is carried out into polymerization and form preliminary
Target software service；
S6. the preliminary target software service for obtaining for step S5 carries out performance detection and amendment, final so as to obtain
Target software service.
The parameter of each destination service component described in step S1 and requirement, the function of specifically including destination service component is special
Property, and the type of the input data of destination service component, number, length and precision, and the type of output data, number,
Length and precision.
Matching is scanned for destination service component described in step S2, search matching and target specially under cloud environment
The type of the input data of services component, number, length and precision, and the type of output data, number, length and precision be equal
It is identical, and the functional characteristic candidate service component similar with destination service component.
The scoring that carries out to candidate service component described in step S3 is that candidate service component is entered using fuzzy evaluation rule
Row scoring.
Described employing fuzzy evaluation rule scores candidate service component, specifically includes following steps：
1) evaluation index of candidate service component is chosen, the index includes a class index R=[r1,r2…rn], and to every
One class index r of a class selecting index twoi=[rij], the 1≤i≤n；
2) for each two class index, scored using specialist system, so as to obtain commenting for each two class index
Divide Srij；
3) for each class index, the weighted value k of two class indexs under the class index is setj, it is each so as to obtain
The score of individual class index
4) each candidate service component is directed to again, set the weighted value q of each class indexi, and calculate each
The final score of candidate service componentThe score is higher, then the performance for showing candidate service component is got over
It is good.
A candidate service component, tool are chosen in the candidate service component of each destination service component described in step S5
Body is that the component of a highest scoring is chosen in the candidate service component of each destination service component as candidate service component.
Described in step S5 the candidate service component chosen is carried out being polymerized forming preliminary target software service, specifically then wrapped
Include following steps：
A. the adaptation of services component：Correct parameter is selected to be adapted to services component or change, so that services component
Software service can be applied to；
B. the polymerization of services component：On the basis of service-oriented component model, described by services component framework, architecture
Language, glue code, script and collaboration language technology, by the structure being adapted to a complete software service is aggregated into.
Performance detection is carried out to target software service described in step S6, following steps are specifically included：
I. performance detection is carried out to target software service；
II. judge the result of performance detection：
If detection passes through, target software service aggregating is completed；
If detection does not pass through, judge occur the type of mistake in detection；
III. wrongheaded type：
If some services component occurs in that test errors, then the services component that will appear from mistake is replaced with step S4
Obtain services component high by several times；
If software service integrated testability occurs in that mistake, then by all services components for constituting the software service,
The minimum services component of score is replaced with and obtain in step S4 services component high by several times；
IV. all of services component is polymerized again, and again to regrouping after target software service carry out
Performance detection；
V. I～step IV of repeat step, until the target software service of polymerization passes through performance detection；Or, if constituting mesh
The services component of mark software service is all replaced, then show this services component Rapid matching and the failure that is polymerized, and is sent
Report to the police, ask manual intervention.
Performance detection is carried out to target software service described in step S6, is specially surveyed using technique of dynamic measurement and black box
Examination technology is detected to target software service.
Score under this cloud environment that the present invention is provided the service Rapid matching and polymerization of driving, by the way that target is soft
Part service is disassembled as multiple services components, and under cloud environment required services component is scanned for, screens, is polymerized and examined
Survey, so as to complete cloud environment under destination service software Rapid matching and polymerization, therefore the inventive method can be under cloud environment
Software service development efficiency is greatly improved, while method is simple, preferably, reliability is high for feasibility.
Description of the drawings
Fig. 1 is the schematic flow sheet of the inventive method.
Fig. 2 is the detailed process schematic diagram of the inventive method.
Specific embodiment
The schematic flow sheet of the inventive method is illustrated in figure 1, Fig. 2 show the detailed process of the inventive method and illustrates
Figure：Score under this cloud environment that the present invention is provided the service Rapid matching and polymerization of driving, comprise the steps：
S1. it is N number of destination service component by target software service decomposition according to the characteristic of target software service, and determines
The parameter of each destination service component and requirement；
The parameter of each destination service component and requirement, specifically include the functional characteristic of destination service component, and target
The type of the input data of services component, number, length and precision, and the type of output data, number, length and precision etc.
Require；
S2. based on cloud computing, the N number of destination service component searched for required for matching step S1 under cloud environment is obtained
To M candidate service component of each destination service component；
In concrete search matching, the class of the input data of search matching and destination service component specially under cloud environment
Type, number, length and precision, and the type of output data, number, length and precision all same, and functional characteristic and target
The similar candidate service component of services component；
M candidate service component of each the destination service component for S3. obtaining to step S2 scores；
Specifically, candidate service component can be scored using fuzzy evaluation rule, specifically includes following steps：
1) evaluation index of candidate service component is chosen, the index includes a class index R=[r1,r2…rn], and to every
One class index r of a class selecting index twoi=[rij], the 1≤i≤n；
2) for each two class index, scored using specialist system, so as to obtain commenting for each two class index
Divide Srij；
3) for each class index, the weighted value k of two class indexs under the class index is setj, it is each so as to obtain
The score of individual class index
4) each candidate service component is directed to again, set the weighted value q of each class indexi, and calculate each
The final score of candidate service componentThe score is higher, then the performance for showing candidate service component is got over
It is good.
Such as, using specialist system, each candidate service component is scored according to the index described in table 1 below；
The Score index of the candidate service component of table 1 illustrates table
Be directed to each class index again, set the weighted value of two class indexs under the class index, and calculate each one
The score of class index；For some candidate service component, its functional scoring, completeness for excellent, i.e., 5 points；Interoperability
Score as excellent, i.e., 5 points；The scoring of standard for good, i.e., 4 points；Then the component feature scoring two class indexs weight
It is worth for completeness accounting 0.4, interoperability accounting 0.2, standard accounting 0.4, then the feature scoring 5*0.4+5*0.2 of the component
+ 4*0.4=4.6；For each candidate service component, the weighted value of each class index is set, and calculate each time
Select the final score of services component；The score is higher, then show that the performance of candidate service component is better；
S4. the appraisal result for being obtained according to step S3, arranges M candidate service component of each destination service component
Sequence；
S5. according to the ranking results of the candidate service component of each destination service component, in each destination service component
The candidate service component of a highest scoring is chosen in candidate service component, and the candidate service component of all selections is gathered
Conjunction forms preliminary target software service；
In polymerization, then including two aspects：
A. the adaptation of services component：Correct parameter is selected to be adapted to services component or change, so that services component
Software service can be applied to；
B. the polymerization of services component：On the basis of service-oriented component model, described by services component framework, architecture
Language, glue code, script and collaboration language technology, by the structure being adapted to a complete software service is aggregated into；
S6. the preliminary target software service for obtaining for step S5 carries out performance detection and amendment, final so as to obtain
Target software service.
When performance detection is carried out to target software service, following steps can be specifically adopted：
I. performance detection is carried out to target software service；
II. judge the result of performance detection：
If detection passes through, target software service aggregating is completed；
If detection does not pass through, judge occur the type of mistake in detection；
III. wrongheaded type：
If some services component occurs in that test errors, then the services component that will appear from mistake is replaced with step S4
Obtain services component high by several times；
If software service integrated testability occurs in that mistake, then by all services components for constituting the software service,
The minimum services component of score is replaced with and obtain in step S4 services component high by several times；
IV. all of services component is polymerized again, and again to regrouping after target software service carry out
Performance detection；
V. I～step IV of repeat step, until the target software service of polymerization passes through performance detection；Or, if constituting mesh
The services component of mark software service is all replaced, then show this services component Rapid matching and the failure that is polymerized, and is sent
Report to the police, ask manual intervention.
And performance detection is carried out to target software service, then can be using technique of dynamic measurement and Black-box Testing technology to target
Software service is detected.
Patent of the present invention obtains state natural sciences fund (bullets 61304184 and bullets 61672221)
Support.
Claims (9)
1. score under a kind of cloud environment the service Rapid matching and polymerization of driving, comprise the steps：
S1. it is N number of destination service component by target software service decomposition according to the characteristic of target software service, and determines each
The parameter of destination service component and requirement；
S2. based on cloud computing, the N number of destination service component searched for required for matching step S1 under cloud environment obtains every
M candidate service component of individual destination service component；
M candidate service component of each the destination service component for S3. obtaining to step S2 scores；
S4. the appraisal result for being obtained according to step S3, is ranked up to M candidate service component of each destination service component；
S5. according to the ranking results of the candidate service component of each destination service component, in the candidate of each destination service component
A candidate service component is chosen in services component, and the candidate service component of all selections is carried out being polymerized forming preliminary mesh
Mark software service；
S6. the preliminary target software service for obtaining for step S5 carries out performance detection and amendment, so as to obtain final mesh
Mark software service.
2. score under cloud environment according to claim 1 the service Rapid matching and polymerization of driving, it is characterised in that
The parameter of each destination service component described in step S1 and requirement, specifically include the functional characteristic of destination service component, and
The type of the input data of destination service component, number, length and precision, and the type of output data, number, length and essence
Degree.
3. score under cloud environment according to claim 1 the service Rapid matching and polymerization of driving, it is characterised in that
Matching is scanned for destination service component described in step S2, search matching and destination service component specially under cloud environment
The type of input data, number, length and precision, and the type of output data, number, length and precision all same, and
The functional characteristic candidate service component similar with destination service component.
4. score under the cloud environment according to one of claims 1 to 3 the service Rapid matching and polymerization of driving, it is special
Levy be scoring that candidate service component is carried out described in step S3 be that candidate service component is carried out using fuzzy evaluation rule
Scoring.
5. score under the cloud environment stated according to claim 4 the service Rapid matching and polymerization of driving, it is characterised in that institute
The employing fuzzy evaluation rule stated scores candidate service component, specifically includes following steps：
1) evaluation index of candidate service component is chosen, the index includes a class index R=[r1,r2…rn], and to each
Class index r of one class selecting index twoi=[rij], the 1≤i≤n；
2) for each two class index, scored using specialist system, so as to obtain the scoring of each two class index
Srij；
3) for each class index, the weighted value k of two class indexs under the class index is setj, so as to obtain each class
The score of index
4) each candidate service component is directed to again, set the weighted value q of each class indexi, and calculate each candidate's clothes
The final score of business componentThe score is higher, then show that the performance of candidate service component is better.
6. score under cloud environment according to claim 5 the service Rapid matching and polymerization of driving, it is characterised in that
A candidate service component is chosen in the candidate service component of each destination service component described in step S5, specially every
The component of a highest scoring is chosen in the candidate service component of individual destination service component as candidate service component.
7. score under the cloud environment according to one of claims 1 to 3 the service Rapid matching and polymerization of driving, it is special
It is to carry out being polymerized forming preliminary target software service by the candidate service component chosen described in step S5 to levy, and is specifically then included
Following steps：
A. the adaptation of services component：Correct parameter is selected to be adapted to services component or change, so that services component can
Suitable for software service；
B. the polymerization of services component：On the basis of service-oriented component model, language is described by services component framework, architecture
Speech, glue code, script and collaboration language technology, by the structure being adapted to a complete software service is aggregated into.
8. score under the cloud environment according to one of claims 1 to 3 the service Rapid matching and polymerization of driving, it is special
It is to carry out performance detection to target software service described in step S6 to levy, and specifically includes following steps：
I. performance detection is carried out to target software service；
II. judge the result of performance detection：
If detection passes through, target software service aggregating is completed；
If detection does not pass through, judge occur the type of mistake in detection；
III. wrongheaded type：
If some services component occurs in that test errors, then the services component that will appear from mistake replaces with score in step S4
Secondary high services component；
If software service integrated testability occurs in that mistake, then by all services components for constituting the software service, score
Minimum services component is replaced with and obtain in step S4 services component high by several times；
IV. all of services component is polymerized again, and again to regrouping after target software service carry out performance
Detection；
V. I～step IV of repeat step, until the target software service of polymerization passes through performance detection；Or, if it is soft to constitute target
The services component of part service is all replaced, then show this services component Rapid matching and the failure that is polymerized, and sends warning,
Request manual intervention.
9. score under the cloud environment according to one of claims 1 to 3 the service Rapid matching and polymerization of driving, it is special
It is to carry out performance detection to target software service described in step S6 to levy, specially using technique of dynamic measurement and Black-box Testing
Technology is detected to target software service.
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| CN109344301A (en) * | 2018-09-26 | 2019-02-15 | 长沙学院 | Method, computer data processing system, the information management system of construction ballot mark table |
| WO2019075977A1 (en) * | 2017-10-19 | 2019-04-25 | 平安科技（深圳）有限公司 | Method and apparatus for splitting software system, readable storage medium and terminal device |
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| US20120233588A1 (en) * | 2011-03-10 | 2012-09-13 | Infosys Technologies Ltd. | Blended service creation, test, and deployment environment for multiple service endpoints |
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
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| WO2019075977A1 (en) * | 2017-10-19 | 2019-04-25 | 平安科技（深圳）有限公司 | Method and apparatus for splitting software system, readable storage medium and terminal device |
| CN109344301A (en) * | 2018-09-26 | 2019-02-15 | 长沙学院 | Method, computer data processing system, the information management system of construction ballot mark table |
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