CN104598219A - Service evolving consistency judgment method and system based on change - Google Patents

Abstract

The present invention provides a change-based service evolution consistency judgment method and system, establishes a change-based service version model according to the service description model, models the original service version and the target service version according to the service description model, and adopts a change vector extraction algorithm to obtain A change vector between the original service version and the target service version, adding the change vector to the change-based service version model, calculating service evolution consistency according to the change vector and a preset relaxation coefficient, Comparing the evolution consistency degree with a preset first threshold, if the service evolution consistency degree is greater than or equal to the preset first threshold value, it is determined that the service evolution meets consistency, and the method covers version modeling The wide range of information can clearly reflect the changes between different versions of the service, and it can more accurately quantitatively analyze the evolution consistency.

Description

Method and system for judging consistency of service evolution based on change

technical field

The invention relates to the technical field of web services, in particular to a change-based service evolution consistency determination method and system.

Background technique

In the application mode of service computing and cloud computing, all kinds of heterogeneous resources distributed on the Internet can be packaged as Web services for external use, such as: "Software-as-a-service (Saas)", Resource as a service (X-as-a-service, Xaas, where X represents any type of resource). This application mode not only helps resource reuse, but also facilitates large-scale programming, that is, users can quickly integrate various resources distributed on the Internet through service composition to complete more complex application goals or provide more Value-added services with practical value.

Since Web services are in an open, dynamic, and changeable network environment, in order to effectively respond to changes in customer needs, operating platforms, and external environments, services must have the ability to evolve. However, service evolution will lead to the generation of multiple service versions, and there may be version conflicts. Therefore, evolution consistency needs to be used to measure whether the service has the ability to maintain normal interaction with the original partner service or service user after evolution.

Aiming at the problem of judging the consistency of service evolution, the prior art mainly adopts a method based on subtype theory and an approximate tree matching method. The analysis based on subtyping theory can be divided into two types: one is at the interface level, matching is carried out through the criteria of input inversion and output covariance; the other is at the behavioral level, requiring the system to provide as many interactive capabilities. The approximate tree matching method evaluates the similarity of services by modeling WSDL as an unordered tag tree and calculating the edit distance.

However, the above methods cover one-sided information in the version modeling method, and cannot clearly reflect the changes between different versions of the service. They only provide qualitative analysis of evolution consistency, and cannot perform accurate quantitative analysis.

Contents of the invention

Aiming at the defects of the prior art, the present invention provides a change-based service evolution consistency determination method and system, which can adapt to a network environment with highly complex requirements, platforms, and external environments, and perform more accurate quantitative analysis of service changes.

On the one hand, the present invention provides a change-based service evolution consistency determination method, including:

S1. Establish a change-based service version model according to the service description model, where the service description model includes a service structure layer description and a service non-functional layer description;

S2. Model the original service version and the target service version according to the service description model, use a change vector extraction algorithm to obtain the change vector between the original service version and the target service version, and add the change vector to the Changing service versioning model;

S3. Calculate service evolution consistency according to the change vector and the preset relaxation coefficient;

S4. Compare the service evolution consistency degree with a preset first threshold, and if the service evolution consistency degree is greater than or equal to the preset first threshold, determine that the service evolution consistency is satisfied.

Optionally, the change vector extraction algorithm includes a structural layer change vector extraction algorithm and a non-functional layer change vector extraction algorithm;

The change vectors include structural layer change vectors and non-functional layer change vectors.

Optionally, the algorithm for extracting structural layer change vectors includes:

A1. According to the change-based service version model, model the original service version and the target service version as an original version structure tree and a target version structure tree respectively;

A2. Traverse each node in the original version structure tree and each node corresponding to the target version structure tree;

Judging whether the main attributes of each node in the original version structure tree and each node corresponding to the target version structure tree are the same, if so, linking each node in the original version structure tree with the target version structure Each node corresponding to the tree is regarded as a matching node, otherwise it is regarded as a non-matching node;

If there is an update change in the matching node, an update change vector of the matching node is generated, and the update change vector of the matching node is added to the structural layer change vector;

If there is an increase or deletion change in the non-matching node, a change vector for adding or deleting the non-matching node is generated, and the change vector for adding or deleting the non-matching node is added to the structural layer change vector.

Optionally, the non-functional layer change vector extraction algorithm includes:

B1. Inputting the non-functional description of the original service version and the non-functional description of the target service version;

B2. Dimensionless the non-functional description of the original service version and the non-functional description of the target service version;

B3. Traverse each QoS indicator in the non-functional description of the original service version and each corresponding QoS indicator in the non-functional description of the target service version;

Judging whether the main attribute of each QoS indicator in the non-functional description of the original service version is the same as that of each corresponding QoS indicator in the non-functional description of the target service version, if so, the non-functional description of the original service version Each QoS indicator in and each QoS indicator corresponding to the non-functional description of the target service version are regarded as matching QoS indicators, otherwise as non-matching QoS indicators;

If there is an update change in the matching QoS index, then generate an update change vector of the matching QoS index, and add the update change vector of the matching QoS index to the non-functional layer change vector;

If there is an increase or deletion change in the non-matching QoS index, generate the non-matching QoS index increase or deletion change vector, and add the non-matching QoS index increase or deletion change vector to the non-functional layer change vector.

Optionally, between the step S3 and the step S4, further comprising:

According to the change vector of the structure layer and the preset relaxation coefficient, calculate the consistency degree of the service structure layer, compare the consistency degree of the service structure layer with the preset second threshold, if the consistency degree of the service structure layer is greater than or equal to the preset The second threshold is determined to meet the consistency of the service structure layer;

According to the change vector of the non-functional layer and the preset relaxation coefficient, calculate the degree of consistency of the service non-functional layer, compare the degree of consistency of the service non-functional layer with the preset third threshold, if the degree of consistency of the service non-functional layer is greater than or equal to The preset third threshold is determined to meet the service non-functional layer consistency.

Optionally, the service evolution consistency degree can be calculated by the following formula,

ECD(ΔC)＝α·SCD(ΔC _S )+γ·NCD(ΔC _N )

Among them, ECD(ΔC) is the service evolution consistency degree based on the change-based service version model, α and γ are the weight coefficients set by the user, and SCD(ΔC _S ) is the sequence of structural layer change vectors ΔC _S extracted in step S2 Consistency of the service structure layer,

$\mathrm{<span\; class="notranslate">\; SCD</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; \&Delta;</span>}{\mathrm{<span\; class="notranslate">\; C</span>}}_{\mathrm{<span\; class="notranslate">\; S</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; =</span>\left\{\begin{array}{cc}\mathrm{<span\; class="notranslate">\; 0</span>}& <span\; class="notranslate">\; \&Exists;</span>{\mathrm{<span\; class="notranslate">\; e</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; \&Element;</span>\mathrm{<span\; class="notranslate">\; \&Delta;</span>}{\mathrm{<span\; class="notranslate">\; C</span>}}_{\mathrm{<span\; class="notranslate">\; add</span>}}<span\; class="notranslate">\; ^</span>{\mathrm{<span\; class="notranslate">\; e</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; \&Element;</span>\mathrm{<span\; class="notranslate">\; IRCs</span>}<span\; class="notranslate">\; |</span><span\; class="notranslate">\; \&Exists;</span>{\mathrm{<span\; class="notranslate">\; e</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; \&Element;</span>\mathrm{<span\; class="notranslate">\; \&Delta;</span>}{\mathrm{<span\; class="notranslate">\; C</span>}}_{\mathrm{<span\; class="notranslate">\; del</span>}}<span\; class="notranslate">\; ^</span>{\mathrm{<span\; class="notranslate">\; e</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; \&Element;</span>\mathrm{<span\; class="notranslate">\; ORCs</span>}\\ \mathrm{<span\; class="notranslate">\; BdCD</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; \&Delta;</span>}{\mathrm{<span\; class="notranslate">\; C</span>}}_{\mathrm{<span\; class="notranslate">\; update</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; *</span>\mathrm{<span\; class="notranslate">\; OPCD</span>}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; \&Delta;C</span>}}_{\mathrm{<span\; class="notranslate">\; update</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; *</span>\mathrm{<span\; class="notranslate">\; PtCD</span>}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; \&Delta;C</span>}}_{\mathrm{<span\; class="notranslate">\; update</span>}}<span\; class="notranslate">\; )</span>& \end{array}\right.$

Among them, if there is a change vector e _i belonging to the increase change vector sequence ΔC _add in the input-related change set IRCs or the deletion change vector sequence ΔC _del in the output-related change set ORCs, then SCD(ΔC _S )=0,

BdCD(ΔC _update ) is the service binding consistency based on the change vector,

$\mathrm{<span\; class="notranslate">\; BdCD</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; \&Delta;</span>}{\mathrm{<span\; class="notranslate">\; C</span>}}_{\mathrm{<span\; class="notranslate">\; update</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; =</span>\frac{\underset{\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 0</span>}}{\overset{\mathrm{<span\; class="notranslate">\; no</span>}}{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}}\mathrm{<span\; class="notranslate">\; StD</span>}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; e</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; *</span>\mathrm{<span\; class="notranslate">\; TrD</span>}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; e</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; *</span>\mathrm{<span\; class="notranslate">\; LoD</span>}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; e</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; )</span>}{\mathrm{<span\; class="notranslate">\; no</span>}}$

Among them, n is the number of modification operation change vectors, StD(e _i ) is the service binding style consistency degree based on change vector e _i ,

$\mathrm{<span\; class="notranslate">\; StD</span>}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; e</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; =</span>\left\{\begin{array}{cc}\mathrm{<span\; class="notranslate">\; 1</span>}& {\mathrm{<span\; class="notranslate">\; style</span>}}_{\mathrm{<span\; class="notranslate">\; sou</span>}}<span\; class="notranslate">\; =</span>{\mathrm{<span\; class="notranslate">\; style</span>}}_{\mathrm{<span\; class="notranslate">\; tar</span>}}\\ \mathrm{<span\; class="notranslate">\; d</span>}& {\mathrm{<span\; class="notranslate">\; style</span>}}_{\mathrm{<span\; class="notranslate">\; sou</span>}}<span\; class="notranslate">\; \&NotEqual;</span>{\mathrm{<span\; class="notranslate">\; style</span>}}_{\mathrm{<span\; class="notranslate">\; tar</span>}}\end{array}\right.$

Among them, d is the custom binding style conversion coefficient, and 0≤d≤1, style _sou and style _tar are the binding styles corresponding to the binding conversion coefficients of the original service version and the target service version respectively;

TrD(e _i ) is the consistency degree of the service transmission protocol based on the change vector e _i ,

$\mathrm{<span\; class="notranslate">\; TrD</span>}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; e</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; =</span>\left\{\begin{array}{cc}\mathrm{<span\; class="notranslate">\; 1</span>}& {\mathrm{<span\; class="notranslate">\; transport</span>}}_{\mathrm{<span\; class="notranslate">\; sou</span>}}<span\; class="notranslate">\; =</span>{\mathrm{<span\; class="notranslate">\; transport</span>}}_{\mathrm{<span\; class="notranslate">\; tar</span>}}\\ \mathrm{<span\; class="notranslate">\; f</span>}& {\mathrm{<span\; class="notranslate">\; transport</span>}}_{\mathrm{<span\; class="notranslate">\; sou</span>}}<span\; class="notranslate">\; \&NotEqual;</span>{\mathrm{<span\; class="notranslate">\; transport</span>}}_{\mathrm{<span\; class="notranslate">\; tar</span>}}\end{array}\right.$

Among them, f is the transmission protocol conversion coefficient, and 0≤f≤1, transport _sou and transport _tar are the transmission protocols corresponding to the original service version and target service version and the transmission protocol conversion coefficient respectively;

LoD(e _i ) is the service binding address consistency based on the change vector e _i ,

$\mathrm{<span\; class="notranslate">\; LoD</span>}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; e</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; =</span>\left\{\begin{array}{cc}\mathrm{<span\; class="notranslate">\; 1</span>}& {\mathrm{<span\; class="notranslate">\; location</span>}}_{\mathrm{<span\; class="notranslate">\; sou</span>}}<span\; class="notranslate">\; =</span>{\mathrm{<span\; class="notranslate">\; location</span>}}_{\mathrm{<span\; class="notranslate">\; tar</span>}}\\ \mathrm{<span\; class="notranslate">\; g</span>}& {\mathrm{<span\; class="notranslate">\; location</span>}}_{\mathrm{<span\; class="notranslate">\; sou</span>}}<span\; class="notranslate">\; \&NotEqual;</span>{\mathrm{<span\; class="notranslate">\; location</span>}}_{\mathrm{<span\; class="notranslate">\; tar</span>}}\end{array}\right.$

Among them, g is the binding address conversion coefficient, and 0≤g≤1, Location _sou and Location _tar are the binding addresses corresponding to the binding address conversion coefficients of the original service version and the target service version respectively;

OpCD(ΔC _update ) is the service operation consistency degree based on the change vector,

$\mathrm{<span\; class="notranslate">\; OPCD</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; \&Delta;</span>}{\mathrm{<span\; class="notranslate">\; C</span>}}_{\mathrm{<span\; class="notranslate">\; update</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; =</span>\frac{\underset{\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 0</span>}}{\overset{\mathrm{<span\; class="notranslate">\; no</span>}}{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}}\mathrm{<span\; class="notranslate">\; MUD</span>}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; e</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; )</span>}{\mathrm{<span\; class="notranslate">\; no</span>}}$

Among them, MUD(e _i ) is the message consistency degree of a certain change vector e _i ,

$\mathrm{<span\; class="notranslate">\; MUD</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; e</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; =</span>\left\{\begin{array}{cc}\mathrm{<span\; class="notranslate">\; 0</span>}& {\mathrm{<span\; class="notranslate">\; MP</span>}}_{\mathrm{<span\; class="notranslate">\; sou</span>}}<span\; class="notranslate">\; \&NotEqual;</span>{\mathrm{<span\; class="notranslate">\; MP</span>}}_{\mathrm{<span\; class="notranslate">\; tar</span>}}\\ \mathrm{<span\; class="notranslate">\; c</span>}& {\mathrm{<span\; class="notranslate">\; MP</span>}}_{\mathrm{<span\; class="notranslate">\; sou</span>}}<span\; class="notranslate">\; =</span>{\mathrm{<span\; class="notranslate">\; MP</span>}}_{\mathrm{<span\; class="notranslate">\; sou</span>}}\\ \mathrm{<span\; class="notranslate">\; 1</span>}& {\mathrm{<span\; class="notranslate">\; MP</span>}}_{\mathrm{<span\; class="notranslate">\; sou</span>}}<span\; class="notranslate">\; =</span>{\mathrm{<span\; class="notranslate">\; MP</span>}}_{\mathrm{<span\; class="notranslate">\; tar</span>}}<span\; class="notranslate">\; ^</span>{\mathrm{<span\; class="notranslate">\; use</span>}}_{\mathrm{<span\; class="notranslate">\; sou</span>}}<span\; class="notranslate">\; =</span>{\mathrm{<span\; class="notranslate">\; use</span>}}_{\mathrm{<span\; class="notranslate">\; tar</span>}}\end{array}\right.$

Among them, MP _sou and MP _tar are the message interaction modes of the original service version and the target service version, use _sou and use _tar are the coding rules of the original service version and the target service version, c is the self-defined message coding style conversion coefficient, and 0≤c ≤1;

PtCD(ΔC _update ) is the service parameter consistency degree based on the change vector,

$\mathrm{<span\; class="notranslate">\; PtCD</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; \&Delta;</span>}{\mathrm{<span\; class="notranslate">\; C</span>}}_{\mathrm{<span\; class="notranslate">\; update</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; =</span>\frac{\underset{\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 0</span>}}{\overset{\mathrm{<span\; class="notranslate">\; no</span>}}{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}}\mathrm{<span\; class="notranslate">\; pSD</span>}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; e</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; *</span>\mathrm{<span\; class="notranslate">\; pDD</span>}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; e</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; )</span>}{\mathrm{<span\; class="notranslate">\; no</span>}}$

Among them, pSD(e _i ) is the consistency degree of service parameter structure,

$\mathrm{<span\; class="notranslate">\; PSD</span>}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; e</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; =</span>\frac{\mathrm{<span\; class="notranslate">\; Num</span>}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; MS</span>}}_{\mathrm{<span\; class="notranslate">\; sou</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; *</span>\mathrm{<span\; class="notranslate">\; deep</span>}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; MS</span>}}_{\mathrm{<span\; class="notranslate">\; sou</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; *</span>\mathrm{<span\; class="notranslate">\; Width</span>}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; MS</span>}}_{\mathrm{<span\; class="notranslate">\; sou</span>}}<span\; class="notranslate">\; )</span>}{\mathrm{<span\; class="notranslate">\; Num</span>}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; MS</span>}}_{\mathrm{<span\; class="notranslate">\; tar</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; *</span>\mathrm{<span\; class="notranslate">\; deep</span>}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; MS</span>}}_{\mathrm{<span\; class="notranslate">\; tar</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; *</span>\mathrm{<span\; class="notranslate">\; Width</span>}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; MS</span>}}_{\mathrm{<span\; class="notranslate">\; tar</span>}}<span\; class="notranslate">\; )</span>}$

Among them, Num(MS _sou ), Num(MS _tar ) are the number of nodes in the schema tree established by the original service version and target service version with parameters, Deep(MS _sou ), Deep(MS _tar ) are the original service version, target service version The depth of the schema tree established by the version, Width(MS _sou ), Width(MS _tar ) is the width of the schema tree established by the original service version and the target service version;

pDD(e _i ) is the consistency degree of service parameter data type,

$\mathrm{<span\; class="notranslate">\; PDD</span>}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; e</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; =</span>\left\{\begin{array}{cc}\mathrm{<span\; class="notranslate">\; DtCD</span>}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; type</span>}}_{\mathrm{<span\; class="notranslate">\; sou</span>}}<span\; class="notranslate">\; ,</span>{\mathrm{<span\; class="notranslate">\; type</span>}}_{\mathrm{<span\; class="notranslate">\; sou</span>}}<span\; class="notranslate">\; )</span>& \mathrm{<span\; class="notranslate">\; e</span>}<span\; class="notranslate">\; \&Element;</span>\mathrm{<span\; class="notranslate">\; IRCs</span>}\\ \mathrm{<span\; class="notranslate">\; DtCD</span>}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; type</span>}}_{\mathrm{<span\; class="notranslate">\; tar</span>}}<span\; class="notranslate">\; ,</span>{\mathrm{<span\; class="notranslate">\; type</span>}}_{\mathrm{<span\; class="notranslate">\; tar</span>}}<span\; class="notranslate">\; )</span>& \mathrm{<span\; class="notranslate">\; e</span>}<span\; class="notranslate">\; \&Element;</span>\mathrm{<span\; class="notranslate">\; ORCs</span>}\end{array}\right.$

Among them, DtCD(type _sou ,type _sou ), DtCD(type _tar ,type _tar ) are the service parameter data consistency degree of original service version and target service version,

Among them, L(T) is the level of the data type T in this category, LN(T) is the total number of levels in the classification of the data type T, a is the conversion difficulty coefficient between different levels, and a>0, b is the conversion difficulty coefficient between different categories, and b>0;

NCD(ΔC _N ) is the non-functional layer consistency degree based on the non-functional layer change vector sequence ΔC _N extracted in step S2;

$\mathrm{<span\; class="notranslate">\; NCD</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; \&Delta;</span>}{\mathrm{<span\; class="notranslate">\; C</span>}}_{\mathrm{<span\; class="notranslate">\; N</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; =</span>\left\{\begin{array}{cc}\mathrm{<span\; class="notranslate">\; 0</span>}& <span\; class="notranslate">\; \&Exists;</span>{\mathrm{<span\; class="notranslate">\; e</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; \&Element;</span>\mathrm{<span\; class="notranslate">\; \&Delta;</span>}{\mathrm{<span\; class="notranslate">\; C</span>}}_{\mathrm{<span\; class="notranslate">\; del</span>}}\\ \mathrm{<span\; class="notranslate">\; \&Sigma;QD</span>}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; e</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; )</span>& {\mathrm{<span\; class="notranslate">\; e</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; \&Element;</span>\mathrm{<span\; class="notranslate">\; \&Delta;</span>}{\mathrm{<span\; class="notranslate">\; C</span>}}_{\mathrm{<span\; class="notranslate">\; update</span>}}\end{array}\right.$

Wherein, if there is a change vector e _i belonging to the deleted change vector ΔC _del in the change vector sequence, then NCD(ΔC _N )=0;

QD(e _i ) is the service QoS consistency degree based on the change vector,

Among them, h is the tolerance degree of self-defined adjustment to the change of QoS indicators, value _sou and value _tar are the QoS indicator attribute values of the original service version and the target service version, antitonic is the proportional attribute of the QoS indicator, and monotonic is the inverse proportional attribute of the QoS indicator;

Wherein, the above-mentioned a, b, c, d, f, g, h are preset relaxation coefficients.

On the other hand, the present invention provides a change-based service evolution consistency judgment system, including:

A change-based service version model establishment unit, configured to establish a change-based service version model according to a service description model, the service description model including a service structure layer description and a service non-functional layer description;

A change vector acquisition unit, configured to model the original service version and the target service version according to the service description model, use a change vector extraction algorithm to obtain a change vector between the original service version and the target service version, and convert the change vector to add to said change-based service versioning model;

A service evolution consistency calculation unit, configured to calculate the service evolution consistency according to the change vector and a preset relaxation coefficient;

A service evolution consistency judging unit, configured to compare the service evolution consistency with a preset first threshold, and determine that the service evolution consistency is satisfied if the service evolution consistency is greater than or equal to the preset first threshold.

It can be seen from the above technical solution that the change-based service evolution consistency determination method and system of the present invention first establishes a change-based service version model based on the service description model, which includes service structure layer description and service non-functional layer description , establish a service instance model according to the service description model, use the change vector extraction algorithm to obtain the change vector in the service instance, calculate the service evolution consistency degree according to the change vector and the preset relaxation coefficient, and compare the evolution consistency degree with the predicted The first threshold is set for comparison, and if the service evolution consistency degree is greater than or equal to the preset first threshold, it is determined that the service evolution meets the consistency. This method covers a wide range of information in version modeling and can clearly reflect Changes between different versions of the service, and more accurate quantitative analysis of evolutionary consistency.

Description of drawings

FIG. 1 is a schematic flowchart of a change-based service evolution consistency determination method provided by the first embodiment of the present invention;

FIG. 2 is a schematic flowchart of a change-based service evolution consistency determination method provided by the second embodiment of the present invention;

Fig. 3 is a schematic diagram of the steps of extracting the structural layer change vector provided by the second embodiment of the present invention;

FIG. 4 is a schematic structural diagram of a tree in the acquisition structure layer change vector provided by the second embodiment of the present invention;

FIG. 5 is a schematic structural diagram of a change-based service evolution consistency judgment system provided by the third embodiment of the present invention;

FIG. 6 is a detailed structural diagram of a change-based service evolution consistency determination system provided by the third embodiment of the present invention.

Detailed ways

The specific implementation manners of the present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. The following examples are used to illustrate the present invention, but are not intended to limit the scope of the present invention.

Fig. 1 shows a schematic flowchart of a change-based service evolution consistency determination method provided by the first embodiment of the present invention. As shown in Fig. 1 , the method of this embodiment is described as follows.

101. Establish a change-based service version model according to a service description model, where the service description model includes a service structure layer description and a service non-functional layer description.

In this step, there are various standards for the description of web services at present. In order to standardize the follow-up work, it is necessary to establish a service version description model based on changes.

The system can maintain and manage multiple versions of multiple services, and provide service names, service version number additions, deletions, and associations between service descriptions and service versions.

102. Model the original service version and the target service version according to the service description model, use a change vector extraction algorithm to obtain a change vector between the original service version and the target service version, and add the change vector to the Vary service version model.

In this step, it should be noted that in the change vector extraction stage, since the current web service description adopts a standard description such as WSDL, the change extraction cannot be performed directly. Therefore, it is necessary to model the original service version as a suitable changed service version, and then obtain the change vector between versions through the change extraction algorithm.

It can be understood that, from the above service description model, the original service version and the target service version also include the service structure layer and the service non-functional layer respectively, and then the change vector extraction algorithm is used to obtain the original service version and the change vector between target service versions;

Wherein, the change vector extraction algorithm includes a structural layer change vector extraction algorithm and a non-functional layer change vector extraction, and the change vector includes a structural layer change vector and a non-functional layer change vector, and the structure is obtained through the structural layer change vector extraction algorithm. The layer change vector is obtained through the non-functional layer change vector extraction algorithm, and the structural layer change vector and the non-functional layer change vector are added to the change-based service version model in step 101 .

103. Calculate service evolution consistency according to the change vector and a preset relaxation coefficient.

In this step, it should be noted that for more accurate quantitative analysis of service changes, the degree of evolution consistency between the two service versions is taken as the degree of evolution consistency, according to the change vector obtained in step 102 combined with user-defined The slack coefficients are used to calculate the consistency of the service structure layer and the consistency of the service non-functional layer, and then use the weighted average method to obtain the consistency of service evolution according to the weight set by the user.

104. Compare the service evolution consistency degree with a preset first threshold, and if the service evolution consistency degree is greater than or equal to the preset first threshold, determine that the service evolution consistency is satisfied.

In this step, the evolution consistency degree obtained in step 103 is compared with the preset first threshold to obtain the judgment result. It should be noted that the value range of the preset first threshold in this embodiment is 0-1, and the user It can be defined according to actual needs.

In the change-based service evolution consistency determination method of this embodiment, firstly, a change-based service version model is established according to the service description model, the service description model includes a service structure layer description and a service non-functional layer description, and the original Modeling of the service version and the target service version, using a change vector extraction algorithm to obtain the change vector between the original service version and the target service version, adding the change vector to the change-based service version model, according to the The change vector and the preset relaxation coefficient are used to calculate the service evolution consistency degree, and the evolution consistency degree is compared with the preset first threshold value. If the service evolution consistency degree is greater than or equal to the preset first threshold value, it is determined that the service evolution consistency degree is satisfied Service evolution consistency, this method covers a wide range of information in version modeling, can clearly reflect changes between different versions of services, and can more accurately quantitatively analyze evolution consistency.

Fig. 2 shows a schematic flowchart of a change-based service evolution consistency determination method provided by the second embodiment of the present invention. As shown in Fig. 2 , the method of this embodiment is described as follows.

201. Establish a service structure layer and a service non-functional layer based on a change-based service version model respectively according to the service description model;

In this step, the service description model in this embodiment includes a service structure layer and a service non-functional layer, described as follows:

1. The service structure is expressed as an octet: Structure=<service, port, binding, portType, operation, message, part, dataType>. Among them, service means service description, port means port description, binding means binding description, operation means operation description, part means parameter description, dataType means data type description.

2. A service is expressed as a triplet: service=<name, des, Port>. Among them, name represents the service name, des represents the semantic description of the service, and Port represents the set of ports contained in the service.

3. The port is expressed as a two-tuple: port=<name, Binding>. Among them, name represents the port name, and Bingding represents the collection bound in the port.

4. Binding is expressed as a five-tuple bingding=<name, style, transport, location, PortType>. Among them, name is the binding name; style is the binding style, such as RPC, SOAP/document, etc.; transport indicates the transmission protocol of the message, such as HTTP, SMTP, etc.; location indicates the port address information merged from the Port type; PortType is the binding A collection of defined port types.

5. The port type is expressed as a two-tuple portType=<name, Operation>. Among them, name represents the name of the port type, and Operation is the set of operations contained in the port type.

6. The operation is expressed as a five-tuple: operation=<name, messagePattern, use, MI, MO>. Among them, name indicates the name of the operation; messagePattern indicates the message exchange mode, and WSDL1.1 supports four message exchange modes, namely One-Way, Request-Response, Solocit-Response, Notifacation; use indicates the coding rules used for serializing XML documents , such as iteral, SOAP, etc.; MI indicates the input message of the service; MO indicates the output message of the service.

7. A message is represented as a triplet: message=<name, Part>, where name represents the name of the message; Part represents the set of parameters contained in the message.

8. Parameters are expressed as a two-tuple: part=<name, DataType>. Among them, name represents the parameter name, and DataType represents the collection of data types contained in the parameter.

9. The data type is expressed as a two-tuple: dataType=<name, type, MS>. Among them, name represents the parameter name, type represents the data type, and MS represents the message structure, which can describe the complex data type represented by XMLSchema, which can be described as a schema tree.

10. The service non-functional layer is expressed as a set of quality of service Non_fuction=<QoS>.

11. Quality of Service QoS=<des, Item>. Among them, des represents the description of QoS, and Item represents the collection of QoS indicators in this QoS.

12. The QoS index is expressed as a quadruple: QoS_item=<item_name, item_type, item_unit, item_value>. Among them, item_name is the QoS indicator name; item_type∈{monotonic,antitonic} is the indicator type; item_unit is the indicator unit; item_value is the indicator value.

Based on the above service description model, a change-based service version model is established, which is described as follows:

1. Service version change vector. Expressed as a quaternion e=<L,Oper,CoVs,CoVt>, where L∈{structure,behavirorl,non-function} indicates the service level for the change; Oper∈{ add,del,update}, represents the change operation; CoVs represents the change source, CoVt represents the change target, when Oper=add, CoVs represents the increase operation at the position, when Oper=del

2. The sequence of service version change vectors is an ordered sequence of change vectors, ΔC=(e1, e2, e3, . . . , ei).

The service version V1 can be obtained by applying the change vector sequence ΔC1 to the service version V2, expressed as: V1×ΔC1=V2.

3. Change-based service version description model: service version Vn=<Vn-1,ΔC>, when n=1, V0 is defined as the service structure of an empty version.

202. Model the original service version and the target service version according to the service description model, obtain a structural layer change vector, and add the structural layer change vector to the change-based service version model;

In this step, FIG. 3 shows a schematic diagram of the step of extracting the structural layer change vector provided by the second embodiment of the present invention. As shown in FIG. 3 , the acquisition of the structural layer change vector is specifically:

A1. According to the change-based service version model, model the original service version and the target service version as an original version structure tree and a target version structure tree respectively.

Fig. 4 shows a schematic diagram of the structure of the tree in the acquisition structure layer change vector provided by the second embodiment of the present invention. As shown in Fig. 4, in this tree, the hierarchical relationship of the structure layer is reflected in the relationship between the parent and child nodes in the structure tree , regardless of the order between sibling nodes, the syntax information of the structure layer is retained in the attribute information of the nodes.

A2. Traverse each node in the original version structure tree and each node corresponding to the target version structure tree;

Judging whether the main attributes of each node in the original version structure tree and each node corresponding to the target version structure tree are the same, if so, linking each node in the original version structure tree with the target version structure Each node corresponding to the tree is regarded as a matching node, otherwise it is regarded as a non-matching node;

If there is an update change in the matching node, an update change vector of the matching node is generated, and the update change vector of the matching node is added to the structural layer change vector;

Table 1 shows the corresponding rule table of the change operation. As shown in the table, if there is the above change, a corresponding change vector is generated, and the change vector is added to the structure change vector.

Table 1

If there is an increase or deletion change in the non-matching node, a change vector for adding or deleting the non-matching node is generated, and the change vector for adding or deleting the non-matching node is added to the structural layer change vector.

203. Calculate the consistency degree of the service structure layer according to the structure layer change vector and the preset relaxation coefficient.

In this step, the consistency degree of the service structure layer can be calculated by the following formula,

SCD(ΔC _S ) is the consistency degree of the service structure layer based on the structure layer change vector sequence ΔC _S extracted in step 202,

$\mathrm{<span\; class="notranslate">\; SCD</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; \&Delta;</span>}{\mathrm{<span\; class="notranslate">\; C</span>}}_{\mathrm{<span\; class="notranslate">\; S</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; =</span>\left\{\begin{array}{cc}\mathrm{<span\; class="notranslate">\; 0</span>}& <span\; class="notranslate">\; \&Exists;</span>{\mathrm{<span\; class="notranslate">\; e</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; \&Element;</span>\mathrm{<span\; class="notranslate">\; \&Delta;</span>}{\mathrm{<span\; class="notranslate">\; C</span>}}_{\mathrm{<span\; class="notranslate">\; add</span>}}<span\; class="notranslate">\; ^</span>{\mathrm{<span\; class="notranslate">\; e</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; \&Element;</span>\mathrm{<span\; class="notranslate">\; IRCs</span>}<span\; class="notranslate">\; |</span><span\; class="notranslate">\; \&Exists;</span>{\mathrm{<span\; class="notranslate">\; e</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; \&Element;</span>\mathrm{<span\; class="notranslate">\; \&Delta;</span>}{\mathrm{<span\; class="notranslate">\; C</span>}}_{\mathrm{<span\; class="notranslate">\; del</span>}}<span\; class="notranslate">\; ^</span>{\mathrm{<span\; class="notranslate">\; e</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; \&Element;</span>\mathrm{<span\; class="notranslate">\; ORCs</span>}\\ \mathrm{<span\; class="notranslate">\; BdCD</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; \&Delta;</span>}{\mathrm{<span\; class="notranslate">\; C</span>}}_{\mathrm{<span\; class="notranslate">\; update</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; *</span>\mathrm{<span\; class="notranslate">\; OPCD</span>}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; \&Delta;C</span>}}_{\mathrm{<span\; class="notranslate">\; update</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; *</span>\mathrm{<span\; class="notranslate">\; PtCD</span>}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; \&Delta;C</span>}}_{\mathrm{<span\; class="notranslate">\; update</span>}}<span\; class="notranslate">\; )</span>& \end{array}\right.$

Among them, if there is a change vector e _i belonging to the increase change vector sequence ΔC _add in the input-related change set IRCs or the deletion change vector sequence ΔC _del in the output-related change set ORCs, then SCD(ΔC _S )=0;

BdCD(ΔC _update ) is the service binding consistency based on the change vector,

$\mathrm{<span\; class="notranslate">\; BdCD</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; \&Delta;</span>}{\mathrm{<span\; class="notranslate">\; C</span>}}_{\mathrm{<span\; class="notranslate">\; update</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; =</span>\frac{\underset{\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 0</span>}}{\overset{\mathrm{<span\; class="notranslate">\; no</span>}}{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}}\mathrm{<span\; class="notranslate">\; StD</span>}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; e</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; *</span>\mathrm{<span\; class="notranslate">\; TrD</span>}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; e</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; *</span>\mathrm{<span\; class="notranslate">\; LoD</span>}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; e</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; )</span>}{\mathrm{<span\; class="notranslate">\; no</span>}}$

Among them, n is the number of modification operation change vectors, StD(e _i ) is the service binding style consistency degree based on change vector e _i ,

$\mathrm{<span\; class="notranslate">\; StD</span>}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; e</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; =</span>\left\{\begin{array}{cc}\mathrm{<span\; class="notranslate">\; 1</span>}& {\mathrm{<span\; class="notranslate">\; style</span>}}_{\mathrm{<span\; class="notranslate">\; sou</span>}}<span\; class="notranslate">\; =</span>{\mathrm{<span\; class="notranslate">\; style</span>}}_{\mathrm{<span\; class="notranslate">\; tar</span>}}\\ \mathrm{<span\; class="notranslate">\; d</span>}& {\mathrm{<span\; class="notranslate">\; style</span>}}_{\mathrm{<span\; class="notranslate">\; sou</span>}}<span\; class="notranslate">\; \&NotEqual;</span>{\mathrm{<span\; class="notranslate">\; style</span>}}_{\mathrm{<span\; class="notranslate">\; tar</span>}}\end{array}\right.$

Among them, d is the custom binding style conversion coefficient, and 0≤d≤1, style _sou and style _tar are the binding styles corresponding to the binding conversion coefficients of the original service version and the target service version respectively;

TrD(e _i ) is the consistency degree of the service transmission protocol based on the change vector e _i ,

$\mathrm{<span\; class="notranslate">\; TrD</span>}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; e</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; =</span>\left\{\begin{array}{cc}\mathrm{<span\; class="notranslate">\; 1</span>}& {\mathrm{<span\; class="notranslate">\; transport</span>}}_{\mathrm{<span\; class="notranslate">\; sou</span>}}<span\; class="notranslate">\; =</span>{\mathrm{<span\; class="notranslate">\; transport</span>}}_{\mathrm{<span\; class="notranslate">\; tar</span>}}\\ \mathrm{<span\; class="notranslate">\; f</span>}& {\mathrm{<span\; class="notranslate">\; transport</span>}}_{\mathrm{<span\; class="notranslate">\; sou</span>}}<span\; class="notranslate">\; \&NotEqual;</span>{\mathrm{<span\; class="notranslate">\; transport</span>}}_{\mathrm{<span\; class="notranslate">\; tar</span>}}\end{array}\right.$

Among them, f is the transmission protocol conversion coefficient, and 0≤f≤1, transport _sou and transport _tar are the transmission protocols corresponding to the original service version and target service version and the transmission protocol conversion coefficient respectively;

LoD(e _i ) is the service binding address consistency based on the change vector e _i ,

$\mathrm{<span\; class="notranslate">\; LoD</span>}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; e</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; =</span>\left\{\begin{array}{cc}\mathrm{<span\; class="notranslate">\; 1</span>}& {\mathrm{<span\; class="notranslate">\; location</span>}}_{\mathrm{<span\; class="notranslate">\; sou</span>}}<span\; class="notranslate">\; =</span>{\mathrm{<span\; class="notranslate">\; location</span>}}_{\mathrm{<span\; class="notranslate">\; tar</span>}}\\ \mathrm{<span\; class="notranslate">\; g</span>}& {\mathrm{<span\; class="notranslate">\; location</span>}}_{\mathrm{<span\; class="notranslate">\; sou</span>}}<span\; class="notranslate">\; \&NotEqual;</span>{\mathrm{<span\; class="notranslate">\; location</span>}}_{\mathrm{<span\; class="notranslate">\; tar</span>}}\end{array}\right.$

Among them, g is the binding address conversion coefficient, and 0≤g≤1, Location _sou and Location _tar are the binding addresses corresponding to the binding address conversion coefficients of the original service version and the target service version respectively;

OpCD(ΔC _update ) is the service operation consistency degree based on the change vector,

$\mathrm{<span\; class="notranslate">\; OPCD</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; \&Delta;</span>}{\mathrm{<span\; class="notranslate">\; C</span>}}_{\mathrm{<span\; class="notranslate">\; update</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; =</span>\frac{\underset{\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 0</span>}}{\overset{\mathrm{<span\; class="notranslate">\; no</span>}}{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}}\mathrm{<span\; class="notranslate">\; MUD</span>}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; e</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; )</span>}{\mathrm{<span\; class="notranslate">\; no</span>}}$

Among them, MUD(e _i ) is the service message consistency degree based on the change vector e _i ,

$\mathrm{<span\; class="notranslate">\; MUD</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; e</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; =</span>\left\{\begin{array}{cc}\mathrm{<span\; class="notranslate">\; 0</span>}& {\mathrm{<span\; class="notranslate">\; MP</span>}}_{\mathrm{<span\; class="notranslate">\; sou</span>}}<span\; class="notranslate">\; \&NotEqual;</span>{\mathrm{<span\; class="notranslate">\; MP</span>}}_{\mathrm{<span\; class="notranslate">\; tar</span>}}\\ \mathrm{<span\; class="notranslate">\; c</span>}& {\mathrm{<span\; class="notranslate">\; MP</span>}}_{\mathrm{<span\; class="notranslate">\; sou</span>}}<span\; class="notranslate">\; =</span>{\mathrm{<span\; class="notranslate">\; MP</span>}}_{\mathrm{<span\; class="notranslate">\; sou</span>}}\\ \mathrm{<span\; class="notranslate">\; 1</span>}& {\mathrm{<span\; class="notranslate">\; MP</span>}}_{\mathrm{<span\; class="notranslate">\; sou</span>}}<span\; class="notranslate">\; =</span>{\mathrm{<span\; class="notranslate">\; MP</span>}}_{\mathrm{<span\; class="notranslate">\; tar</span>}}<span\; class="notranslate">\; ^</span>{\mathrm{<span\; class="notranslate">\; use</span>}}_{\mathrm{<span\; class="notranslate">\; sou</span>}}<span\; class="notranslate">\; =</span>{\mathrm{<span\; class="notranslate">\; use</span>}}_{\mathrm{<span\; class="notranslate">\; tar</span>}}\end{array}\right.$

Among them, MP _sou and MP _tar are the message interaction modes of the original service version and the target service version, use _sou and use _tar are the coding rules of the original service version and the target service version, c is the self-defined message coding style conversion coefficient, and 0≤c ≤1;

PtCD(ΔC _update ) is the service parameter consistency degree based on the change vector,

$\mathrm{<span\; class="notranslate">\; PtCD</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; \&Delta;</span>}{\mathrm{<span\; class="notranslate">\; C</span>}}_{\mathrm{<span\; class="notranslate">\; update</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; =</span>\frac{\underset{\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 0</span>}}{\overset{\mathrm{<span\; class="notranslate">\; no</span>}}{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}}\mathrm{<span\; class="notranslate">\; pSD</span>}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; e</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; *</span>\mathrm{<span\; class="notranslate">\; pDD</span>}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; e</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; )</span>}{\mathrm{<span\; class="notranslate">\; no</span>}}$

Among them, pSD(e _i ) is the consistency degree of service parameter structure based on the change vector e _i ,

$\mathrm{<span\; class="notranslate">\; PSD</span>}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; e</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; =</span>\frac{\mathrm{<span\; class="notranslate">\; Num</span>}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; MS</span>}}_{\mathrm{<span\; class="notranslate">\; sou</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; *</span>\mathrm{<span\; class="notranslate">\; deep</span>}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; MS</span>}}_{\mathrm{<span\; class="notranslate">\; sou</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; *</span>\mathrm{<span\; class="notranslate">\; Width</span>}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; MS</span>}}_{\mathrm{<span\; class="notranslate">\; sou</span>}}<span\; class="notranslate">\; )</span>}{\mathrm{<span\; class="notranslate">\; Num</span>}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; MS</span>}}_{\mathrm{<span\; class="notranslate">\; tar</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; *</span>\mathrm{<span\; class="notranslate">\; deep</span>}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; MS</span>}}_{\mathrm{<span\; class="notranslate">\; tar</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; *</span>\mathrm{<span\; class="notranslate">\; Width</span>}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; MS</span>}}_{\mathrm{<span\; class="notranslate">\; tar</span>}}<span\; class="notranslate">\; )</span>}$

Among them, Num(MS _sou ), Num(MS _tar ) are the number of nodes in the schema tree established by the original service version and target service version with parameters, Deep(MS _sou ), Deep(MS _tar ) are the original service version, target service version The depth of the schema tree established by the version, Width(MS _sou ), Width(MS _tar ) is the width of the schema tree established by the original service version and the target service version;

pDD(e _i ) is the consistency degree of service parameter data type based on the change vector e _i ,

$\mathrm{<span\; class="notranslate">\; PDD</span>}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; e</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; =</span>\left\{\begin{array}{cc}\mathrm{<span\; class="notranslate">\; DtCD</span>}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; type</span>}}_{\mathrm{<span\; class="notranslate">\; sou</span>}}<span\; class="notranslate">\; ,</span>{\mathrm{<span\; class="notranslate">\; type</span>}}_{\mathrm{<span\; class="notranslate">\; sou</span>}}<span\; class="notranslate">\; )</span>& \mathrm{<span\; class="notranslate">\; e</span>}<span\; class="notranslate">\; \&Element;</span>\mathrm{<span\; class="notranslate">\; IRCs</span>}\\ \mathrm{<span\; class="notranslate">\; DtCD</span>}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; type</span>}}_{\mathrm{<span\; class="notranslate">\; tar</span>}}<span\; class="notranslate">\; ,</span>{\mathrm{<span\; class="notranslate">\; type</span>}}_{\mathrm{<span\; class="notranslate">\; tar</span>}}<span\; class="notranslate">\; )</span>& \mathrm{<span\; class="notranslate">\; e</span>}<span\; class="notranslate">\; \&Element;</span>\mathrm{<span\; class="notranslate">\; ORCs</span>}\end{array}\right.$

Among them, DtCD(type _sou ,type _sou ), DtCD(type _tar ,type _tar ) are the service parameter data consistency degree of original service version and target service version,

Among them, L(T) is the level of the data type T in this category, LN(T) is the total number of levels in the classification of the data type T, a is the conversion difficulty coefficient between different levels, and a>0, b is the conversion difficulty coefficient between different categories, and b>0;

Wherein, the above-mentioned a, b, c, d, f, g are preset relaxation coefficients.

204. Compare the degree of consistency of the service structure layer with a preset second threshold, and if the degree of consistency of the service structure layer is greater than or equal to the preset second threshold, determine that the consistency of the service structure layer is satisfied.

In this step, it should be noted that the value range of the preset second threshold in this embodiment is 0-1, which can be defined by the user according to actual needs.

205. Acquire a non-functional layer change vector, and add the non-functional layer change vector to a change-based service version model.

In this step, the non-functional layer change vector is obtained specifically as follows:

B1. Inputting the non-functional description of the original service version and the non-functional description of the target service version;

B2. Dimensionless the non-functional description of the original service version and the non-functional description of the target service version;

B3. Traverse each QoS indicator in the non-functional description of the original service version and each corresponding QoS indicator in the non-functional description of the target service version;

Judging whether the main attribute of each QoS indicator in the non-functional description of the original service version is the same as that of each corresponding QoS indicator in the non-functional description of the target service version, if so, the non-functional description of the original service version Each QoS indicator in and each QoS indicator corresponding to the non-functional description of the target service version are regarded as matching QoS indicators, otherwise as non-matching QoS indicators;

If there is an update change in the matching QoS index, then generate an update change vector of the matching QoS index, and add the update change vector of the matching QoS index to the non-functional layer change vector;

If there is an increase or deletion change in the non-matching QoS index, generate the non-matching QoS index increase or deletion change vector, and add the non-matching QoS index increase or deletion change vector to the non-functional layer change vector.

206. Calculate the consistency degree of the service non-functional layer according to the non-functional layer change vector and the preset relaxation coefficient.

In this step, the consistency degree of the service non-functional layer can be calculated by the following formula,

SCD(ΔC _S ) is the service non-functional layer consistency degree based on the non-functional layer change vector sequence ΔC _N extracted in step 202, $\mathrm{NCD}\left(\mathrm{\&Delta;}{C}_N\right)=\left\{\begin{array}{cc}0& \&Exists;e_i\&Element;\mathrm{\&Delta;}{C}_{\mathrm{del}}\\ \mathrm{\&Sigma;QD}\left(e_i\right)& e_i\&Element;\mathrm{\&Delta;}{C}_{\mathrm{update}}\end{array}\right.$

Wherein, if there is a change vector e _i belonging to the deleted change vector ΔC _del in the change vector sequence, then NCD(ΔC _N )=0;

QD(e _i ) is the service QoS consistency degree based on the change vector,

Among them, h is the tolerance degree of self-defined adjustment to the change of QoS indicators, value _sou and value _tar are the QoS indicator attribute values of the original service version and the target service version, antitonic is the proportional attribute of QoS indicator, and monotonic is the inverse proportional attribute of QoS indicator.

Among them, h is the preset slack coefficient, and the above-mentioned determination of the QoS index attribute value of the original service version and the target service version adopts the Allen interval algebra definition formula,

${\mathrm{<span\; class="notranslate">\; value</span>}}_{\mathrm{<span\; class="notranslate">\; sou</span>}}<span\; class="notranslate">\; \&le;</span>{\mathrm{<span\; class="notranslate">\; value</span>}}_{\mathrm{<span\; class="notranslate">\; tar</span>}}<span\; class="notranslate">\; \&DoubleLeftRightArrow;</span>\left\{\begin{array}{cc}{\mathrm{<span\; class="notranslate">\; value</span>}}_{\mathrm{<span\; class="notranslate">\; sou</span>}}<span\; class="notranslate">\; \{</span><span\; class="notranslate">\; =</span><span\; class="notranslate">\; ,</span><span\; class="notranslate">\; ></span><span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; f</span>}<span\; class="notranslate">\; ,</span>\stackrel{<span\; class="notranslate">\; \&OverBar;</span>}{\mathrm{<span\; class="notranslate">\; the\; s</span>}}<span\; class="notranslate">\; ,</span>\stackrel{<span\; class="notranslate">\; \&OverBar;</span>}{\mathrm{<span\; class="notranslate">\; m</span>}}<span\; class="notranslate">\; ,</span>\stackrel{<span\; class="notranslate">\; \&OverBar;</span>}{\mathrm{<span\; class="notranslate">\; o</span>}}<span\; class="notranslate">\; \}</span>{\mathrm{<span\; class="notranslate">\; value</span>}}_{\mathrm{<span\; class="notranslate">\; tar</span>}}& \mathrm{<span\; class="notranslate">\; type</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; monotonic</span>}\\ {\mathrm{<span\; class="notranslate">\; value</span>}}_{\mathrm{<span\; class="notranslate">\; sou</span>}}<span\; class="notranslate">\; \{</span><span\; class="notranslate">\; =</span><span\; class="notranslate">\; ,</span><span\; class="notranslate">\; <</span><span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; the\; s</span>}<span\; class="notranslate">\; ,</span>\stackrel{<span\; class="notranslate">\; \&OverBar;</span>}{\mathrm{<span\; class="notranslate">\; f</span>}}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; m</span>}<span\; class="notranslate">\; .</span>\mathrm{<span\; class="notranslate">\; o</span>}<span\; class="notranslate">\; \}</span>{\mathrm{<span\; class="notranslate">\; value</span>}}_{\mathrm{<span\; class="notranslate">\; tar</span>}}& \mathrm{<span\; class="notranslate">\; type</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; Antitonic</span>}\end{array}\right.$

Table 2 shows the Allen interval algebra, as shown in Table 2, Indicates the inverse relation of f, s, m, o,

Table 2

207. Compare the consistency degree of the service non-functional layer with a preset third threshold, and if the consistency degree of the service non-functional layer is greater than or equal to the preset third threshold, determine that the consistency of the service non-functional layer is satisfied.

In this step, it should be noted that the value range of the preset third threshold in this embodiment is 0-1, which can be defined by the user according to actual needs.

208. Calculate a service evolution consistency degree according to the service structure layer consistency degree and the service non-functional layer consistency degree.

In this step, the service evolution consistency degree can be calculated by the following formula,

ECD(ΔC)＝α·SCD(ΔC _S )+γ·NCD(ΔC _N )

Among them, ECD(ΔC) is the consistency degree of service evolution based on the change service version model, and α and γ are weight coefficients set by users.

209. Compare the service evolution consistency degree with a preset first threshold, and determine that the service evolution consistency is satisfied if the service evolution consistency degree is greater than or equal to the preset first threshold.

The change-based service evolution consistency determination method in this embodiment calculates the service structural layer consistency and service non-functional layer consistency by establishing a change-based service version model, and obtaining structural layer change vectors and non-functional layer change vectors hierarchically Degree of service structure layer consistency and service non-functional layer consistency can be determined respectively, and service evolution consistency degree can be calculated according to the service structure layer consistency degree and service non-functional layer consistency degree to determine service evolution consistency, avoiding the The way in which the existing technology determines the consistency is too strict can more accurately quantitatively analyze the evolution consistency.

Fig. 5 shows a schematic structural diagram of a change-based service evolution consistency judgment system provided by the third embodiment of the present invention. As shown in Fig. 5, the change-based service evolution consistency system in this implementation includes: change-based service Version model establishment unit 51, change vector acquisition unit 52, service evolution consistency calculation unit 53, service evolution consistency determination unit 54,

Wherein, the change-based service version model establishing unit 51 is used to establish a change-based service version model according to the service description model, and the service description model includes a service structure layer description and a service non-functional layer description;

The change vector acquisition unit 52 is used to model the original service version and the target service version according to the service description model, use a change vector extraction algorithm to obtain the change vector between the original service version and the target service version, and convert the change vector to add to said change-based service versioning model;

The service evolution consistency degree calculation unit 53 is used to calculate the service evolution consistency degree according to the change vector and the preset relaxation coefficient;

The service evolution consistency determining unit 54 is configured to compare the service evolution consistency degree with a preset first threshold, and if the service evolution consistency degree is greater than or equal to the preset first threshold, it is determined that the service evolution consistency is satisfied.

Fig. 6 shows the detailed structural diagram of the change-based service evolution consistency judgment system provided by the third embodiment of the present invention, select the source service version and the target service version according to the actual needs of users, and select the source service version and the target service version from the Perform layered change vector extraction, calculate the service evolution consistency degree according to the extracted change vector and the parameters set by the user, and judge the service evolution consistency degree and the preset threshold to obtain the judgment result. The change-based The service evolution consistency judgment system can reflect the continuous process of development and also reflect the changes between the old and new versions, effectively solving the problem of evolution consistency judgment.

Finally, it should be noted that: the above embodiments are only used to illustrate the technical solutions of the present invention, rather than limiting them; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that: It is still possible to modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements for some or all of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions depart from the scope defined by the claims of the present invention .

Claims (7)

1., based on a service Evolution consistency decision method for change, it is characterized in that, comprising:

S1, set up the service release model based on change according to service description model, described service description model comprises service structure layer and to describe and service NOT-function layer describes;

S2, according to service description model to original service version and the modeling of destination service version, employing change vector extraction algorithm obtains the change vector between described original service version and described destination service version, described change vector is added to the described service release model based on change;

S3, according to described change vector and default coefficient of relaxation, calculation services evolution consistent degree;

S4, described service evolution consistent degree and preset first threshold value to be compared, if described service evolution consistent degree is more than or equal to described preset first threshold value, then judge to meet service Evolution consistency.

2. method according to claim 1, is characterized in that, described change vector extraction algorithm comprises structural sheet change vector extraction algorithm and NOT function ergosphere change vector extraction algorithm;

Described change vector comprises structural sheet change vector and NOT function ergosphere change vector.

3. method according to claim 2, is characterized in that, described structural sheet change vector extraction algorithm, comprising:

A1, according to described based on change service release model, described original service version and described destination service version are modeled as original version structure tree and target version structure tree respectively;

A2, each node that each node traveled through in described original version structure tree is corresponding with described target version structure tree;

Judge that whether the primary attribute of each node that each node in described original version structure tree is corresponding with described target version structure tree is identical, if, each node that each node in described original version structure tree is corresponding with described target version structure tree as matched node, otherwise as non-matching node;

If described matched node exists more new change, then produce described matched node and upgrade change vector, described matched node is upgraded change vector and adds described structural sheet change vector;

If described non-matching node exists increase, deletion change, then producing described non-matching node increases, deletes change vector, and described non-matching node increase, deletion change vector are added described structural sheet change vector.

4. method according to claim 2, is characterized in that, described NOT function ergosphere change vector extraction algorithm, comprising:

B1, input the non-functional description of described original service version and the non-functional description of described destination service version;

B2, nondimensionalization is carried out to the non-functional description of described original service version and the non-functional description of described destination service version;

B3, travel through described original service version non-functional description in each QoS index and described destination service version non-functional description in corresponding each QoS index;

Judge that in the non-functional description of described original service version, whether each QoS index is identical with the primary attribute of each QoS index corresponding in the non-functional description of described destination service version, if, using each QoS index corresponding in the non-functional description of each QoS index and described destination service version in the non-functional description of described original service version as coupling QoS index, otherwise as non-matching QoS index;

If described coupling QoS index exists more new change, then produce described coupling QoS index and upgrade change vector, described coupling QoS index is upgraded change vector and adds described NOT function ergosphere change vector;

If described non-matching QoS index exists increase, deletion change, then producing described non-matching QoS index increases, deletes change vector, and described non-matching QoS index increase, deletion change vector are added NOT function ergosphere change vector.

5. method according to claim 1, is characterized in that, between described step S3 and described step S4, also comprises:

According to described structural sheet change vector and default coefficient of relaxation, calculation services structural sheet consistent degree, described service structure layer consistent degree is compared with default Second Threshold, if described service structure layer consistent degree is more than or equal to described default Second Threshold, then judges to meet service structure layer consistance;

According to described NOT function ergosphere change vector and default coefficient of relaxation, calculation services NOT function ergosphere consistent degree, described service NOT function ergosphere consistent degree is compared with default 3rd threshold value, if described service NOT function ergosphere consistent degree is more than or equal to described default 3rd threshold value, then judge to meet service NOT function ergosphere consistance.

6. method according to claim 1, is characterized in that, described service evolution consistent degree calculates by following formula,

ECD(ΔC)＝α·SCD(ΔC _S)+γ·NCD(ΔC _N)

Wherein, ECD (Δ C) is the service evolution consistent degree of the service release model based on change, and α, γ are the weight coefficient that user sets, SCD (Δ C _s) be based on the structural sheet change vector sequence Δ C extracted in step S2 _sservice structure layer consistent degree,

$\mathrm{SCD}\left({\mathrm{\&Delta;C}}_S\right)=\left\{\begin{array}{cc}0& \&Exists;e_i\&Element;{\mathrm{\&Delta;C}}_{\mathrm{add}}^e_i\&Element;\mathrm{IRCs}|\&Exists;e_i\&Element;\mathrm{\&Delta;}{C}_{\mathrm{del}}^e_i\&Element;\mathrm{ORCs}\\ \mathrm{BdCD}\left(\mathrm{\&Delta;}{C}_{\mathrm{update}}\right)*\mathrm{OpCD}\left(\mathrm{\&Delta;}{C}_{\mathrm{update}}\right)*\mathrm{PtCD}\left(\mathrm{\&Delta;}{C}_{\mathrm{update}}\right)& \end{array}\right.$

Wherein, if there is change vector e _ibelong to the increase change vector sequence Δ C in input associated change collection IRCs _addor belong to the deletion change vector sequence Δ C exported in associated change collection ORCs _del, then SCD (Δ C _s)=0,

BdCD (Δ C _update) be service binding consistent degree based on change vector,

$\mathrm{BdCD}\left(\mathrm{\&Delta;}{C}_{\mathrm{update}}\right)=\frac{\underset{i=0}{\overset{n}{\mathrm{\&Sigma;}}}\mathrm{StD}\left(e_i\right)*\mathrm{TrD}\left(e_i\right)*\mathrm{LoD}\left(e_i\right)}{n}$

Wherein, n is the number of retouching operation change vector, StD (e _i) be based on change vector e _iservice binding style consistent degree,

$\mathrm{StD}\left(e_i\right)=\left\{\begin{array}{cc}1& {\mathrm{style}}_{\mathrm{sou}}={\mathrm{style}}_{\mathrm{tar}}\\ d& {\mathrm{style}}_{\mathrm{sou}}\&NotEqual;{\mathrm{style}}_{\mathrm{tar}}\end{array}\right.$

Wherein, d is self-defined binding style conversion coefficient, and 0≤d≤1, style _sou, style _tarfor the binding style that original service version, destination service version are corresponding with described binding conversion coefficient respectively;

TrD (e _i) be based on change vector e _iservice Delivery Protocol consistent degree,

$\mathrm{TrD}\left(e_i\right)=\left\{\begin{array}{cc}1& {\mathrm{transport}}_{\mathrm{sou}}={\mathrm{transport}}_{\mathrm{tar}}\\ f& {\mathrm{transport}}_{\mathrm{sou}}\&NotEqual;{\mathrm{transport}}_{\mathrm{tar}}\end{array}\right.$

Wherein, f is transport protocol conversion coefficient, and 0≤f≤1, transport _sou, transport _tarfor original service version, host-host protocol that destination service version is corresponding with transport protocol conversion coefficient respectively;

LoD (e _i) be based on change vector e _iservice binding address consistent degree,

$\mathrm{LoD}\left(e_i\right)=\left\{\begin{array}{cc}1& {\mathrm{location}}_{\mathrm{sou}}={\mathrm{Location}}_{\mathrm{tar}}\\ g& {\mathrm{Location}}_{\mathrm{sou}}\&NotEqual;{\mathrm{Location}}_{\mathrm{tar}}\end{array}\right.$

Wherein, g is bind address conversion coefficient, and 0≤g≤1, Location _sou, Location _tarfor original service version, bind address that destination service version is corresponding with bind address conversion coefficient respectively;

OpCD (Δ C _update) be service operations consistent degree based on change vector,

$\mathrm{OpCD}\left(\mathrm{\&Delta;}{C}_{\mathrm{update}}\right)=\frac{\underset{i=0}{\overset{n}{\mathrm{\&Sigma;}}}\mathrm{MUD}\left(e_i\right)}{n}$

Wherein, MUD (e _i) be a certain change vector e _imessage consistent degree,

$\mathrm{MUD}\left(e\right)=\left\{\begin{array}{cc}0& {\mathrm{MP}}_{\mathrm{sou}}\&NotEqual;{\mathrm{MP}}_{\mathrm{tar}}\\ c& {\mathrm{MP}}_{\mathrm{sou}}={\mathrm{MP}}_{\mathrm{sou}}\\ 1& {\mathrm{MP}}_{\mathrm{sou}}={\mathrm{MP}}_{\mathrm{tar}}^{\mathrm{use}}_{\mathrm{sou}}={\mathrm{use}}_{\mathrm{tar}}\end{array}\right.$

Wherein, MP _sou, MP _tarfor original service version, destination service version message interactive mode, use _sou, use _tarfor original service version, destination service version coding rule, c is self-defining message coding style conversion coefficient, and 0≤c≤1;

PtCD (Δ C _update) be service parameter consistent degree based on change vector,

$\mathrm{PcCD}\left(\mathrm{\&Delta;}{C}_{\mathrm{update}}\right)\frac{\underset{i=0}{\overset{n}{\mathrm{\&Sigma;}}}\mathrm{pSD}\left(e_i\right)*\mathrm{pDD}\left(e_i\right)}{n}$

Wherein, pSD (e _i) be service parameter structure consistent degree,

$\mathrm{PsD}\left(e_i\right)=\frac{\mathrm{Num}\left({\mathrm{MS}}_{\mathrm{sou}}\right)*\mathrm{Deep}\left({\mathrm{MS}}_{\mathrm{sou}}\right)*\mathrm{Width}\left({\mathrm{MS}}_{\mathrm{sou}}\right)}{\mathrm{Num}\left({\mathrm{MS}}_{\mathrm{tar}}\right)*\mathrm{Deep}\left({\mathrm{MS}}_{\mathrm{tar}}\right)*\mathrm{Width}\left({\mathrm{MS}}_{\mathrm{tar}}\right)}$

Wherein, Num (MS _sou), Num (MS _tar) number of nodes in the schema tree of setting up with parameter for original service version, destination service version, Deep (MS _sou), Deep (MS _tar) for original service version, destination service version set up schema tree the degree of depth, Width (MS _sou), Width (MS _tar) for original service version, destination service version set up schema tree width;

PDD (e _i) be service parameter data type consistent degree,

$\mathrm{PDD}\left(e_i\right)=\left\{\begin{array}{cc}\mathrm{DtCD}({\mathrm{type}}_{\mathrm{sou}},{\mathrm{type}}_{\mathrm{sou}})& e\&Element;\mathrm{IRCs}\\ \mathrm{DtCD}({\mathrm{type}}_{\mathrm{tar}},{\mathrm{type}}_{\mathrm{tar}})& e\&Element;\mathrm{ORCs}\end{array}\right.$

Wherein, DtCD (type _sou, type _sou), DtCD (type _tar, type _tar) be the service parameter data consistent degree of original service version, destination service version,

Wherein, L (T) is the rank residing in this classification of data type T, total number of levels that LN (T) classifies for data type T place, a is the conversion degree-of-difficulty factor between different stage, and a>0, b be different classes of between conversion degree-of-difficulty factor, and b>0;

NCD (Δ C _n) be based on the NOT function ergosphere change vector sequence Δ C extracted in step S2 _nnOT function ergosphere consistent degree;

$\mathrm{NCD}\left(\mathrm{\&Delta;}{C}_N\right)=\left\{\begin{array}{cc}0& \&Exists;e_i\&Element;\mathrm{\&Delta;}{C}_{\mathrm{del}}\\ \mathrm{\&Sigma;QD}\left(e_i\right)& e_i\&Element;\mathrm{\&Delta;}{C}_{\mathrm{update}}\end{array}\right.$

Wherein, if there is change vector e _ibelong to the deletion change vector Δ C in change vector sequence _del, then NCD (Δ C _n)=0;

QD (e _i) be service QoS consistent degree based on change vector,

Wherein, h is the degrees of tolerance that self-defined adjustment changes QoS index, value _sou, value _tarfor the QoS index property value of original service version, destination service version, antitonic is the direct ratio attribute of QoS index, and monotonic is the inverse ratio attribute of QoS index;

Wherein, above-mentioned a, b, c, d, f, g, h are for presetting coefficient of relaxation.

7., based on a service Evolution consistency decision-making system for change, it is characterized in that, comprising:

Unit set up by service release model based on change, and for setting up the service release model based on change according to service description model, described service description model comprises the description of service structure layer and service NOT-function layer describes;

Change vector acquiring unit, for according to service description model to original service version and the modeling of destination service version, employing change vector extraction algorithm obtains the change vector between described original service version and described destination service version, described change vector is added to the described service release model based on change;

Service evolution consistent degree computing unit, for according to described change vector and default coefficient of relaxation, calculation services evolution consistent degree;

Service Evolution consistency identifying unit, for described service evolution consistent degree and preset first threshold value being compared, if described service evolution consistent degree is more than or equal to described preset first threshold value, then judges to meet service Evolution consistency.