CN105786514A - Framework dynamic maturity measuring method - Google Patents

Abstract

The invention provides a framework dynamic maturity measuring method. Framework performance related basic data and function related basic data are measured through framework dynamic simulation, formal verification and other methods. The user expectant satisfaction condition of the framework reflects to be performance through a computational formula in the aspect of performance, the constrain satisfaction condition of the framework reflects to be function accuracy, framework reliability and the like. According to the performance, the accuracy and reliability, the framework dynamic maturity is obtained, a use is helped to find the problems existing in the framework, and the framework quality is improved.

Description

A kind of dynamic Maturity measure of framework

Technical field

The present invention relates to a kind of method measuring the dynamic Maturity of framework, belong to software architecture tolerance field.

Background technology

The dynamic need of software includes the demands such as performance, safety, customer experience and reliability as the important component part of software quality demand, increasingly receives the concern of people.And the traditional software development approach of software dynamic need is only just paid close attention in the software development cycle later stage, the consequence such as excessive risk and high cost will be brought to developer, if the behavioral characteristics of software can be predicted at the commitment of software development cycle, software architecture Problems existing and development bottleneck can be found in advance, and find out possible prioritization scheme.

The present invention proposes the appraisal procedure of a kind of software development commitment, for the dynamic behaviour feature of software architecture, has invented the dynamic Maturity measure of a kind of framework.

Software architecture Maturity, i.e. DSAM, refer to software architecture degree close to ripe framework on behavioral characteristics, and in order to make problem be unlikely to too complicated and controlled, the behavioral characteristics paid close attention to here includes reliability, accuracy and performance.One ripe framework refers to that acute variation will not occur its mature indicator when architectural evolution is to certain phase, only fluctuates within the specific limits, and framework now reaches maturity state.Ripe framework is modified again, and its certain (or some) behavioral characteristics (such as, reliability) can become very poor so that this framework has been unsatisfactory for current demand.

Summary of the invention

Technical problem: the present invention provides one in software development early stage, Software Architecture Design to be measured, and helps the user discover that design problem, time update, reduces the dynamic Maturity measure of framework of risk and software development maintenance cost.

Technical scheme: the dynamic Maturity measure of framework of the present invention, it is characterised in that the method includes the steps of:

Step 1) qualification inspection: inspection framework describes whether the bibliographic structure of document comprises all documents carried out needed for DSAM tolerance, in this way, then enter step 2), otherwise, method ends flow process, described framework describes document and includes component diagram, deployment diagram, Use Case Map, precedence diagram, system sequence diagrams and constraint document.

Step 2) collect metadata and intermediate data, specific as follows:

1. the dynamic Maturity measure of framework, it is characterised in that the method includes the steps of:

Step 1) qualification inspection: inspection framework describes whether the bibliographic structure of document comprises all documents carried out needed for DSAM tolerance, in this way, then enter step 2), otherwise, method ends flow process, described framework describes document and includes component diagram, deployment diagram, Use Case Map, precedence diagram, system sequence diagrams and constraint document；

Step 2) collect metadata and intermediate data, specific as follows:

A) performance data is obtained:

First metadata is obtained: utilizing emulation technology to obtain the simulation result of framework, described simulation result includes maximum operation time, average operating time, maximum response time, average response time, maximum memory occupancy, the internal memory utilization of unit interval, maximum CPU occupancy and the CPU occupancy of unit interval；

Then intermediate data is obtained: the performance Performance according to equation below computing architecture:

$Performance=\left\{\begin{array}{c}(W_1\×\frac{AvgExcTime}{EpAET}+W_2\×\frac{Avg\mathrm{Re}sTime}{EpART}+W_3\×\frac{MemUseUnitTime}{EpMUUT}+W_4\×\frac{CPUUseUnitTime}{EpCUUT})\×\frac{1}{4}\\ (W_1\×\frac{MaxExcTime}{EpMET}+W_2\×\frac{Max\mathrm{Re}sTime}{EpMRT}+W_3\×\frac{MaxMemUse}{EpMMU}+W_4\×\frac{MaxCPUUse}{EpMCU})\×\frac{1}{4}\end{array}\right.$

Wherein, MaxExcTime represents the maximum operation time, and namely in all interaction sequence, the maximum duration of user and system interaction, AvgExcTime represents the average operation time, i.e. average time required for all interaction sequence；

MaxResTime represents maximum response time, namely in all user operations, and the maximum response time of system of users, AvgResTime represents average response time, namely in all user operations, the average response time of system of users；

MaxMemUse represents maximum memory occupancy, and namely in all interaction sequence execution processes, the maximum occupancy of internal memory, MemUseUnitTime represents the internal memory utilization of unit interval, i.e. all interaction sequence unit interval internal memory utilizations；

MaxCPUUse represents maximum CPU occupancy, and namely in all interaction sequence execution processes, the maximum occupancy of CPU, CPUUseUnitTime represents the CPU occupancy of unit interval, i.e. all interaction sequence unit interval CPU utilizations；

EpAET represents the desired average operating time of user, and EpMET represents user's desired maximum operation time；

EpART represents the desired average response time of user, and EpMRT represents the desired maximum response time of user；

EpMUUT represents the desired unit interval internal memory utilization of user, and EpMMU represents the desired maximum memory occupancy of user；

EpCUUT represents user's utilization of desired unit interval CPU, and EpMCU represents the desired maximum CPU occupancy of user；

Condition, thus obtaining the function number being unsatisfactory for constraint, namely not exclusively correct function number；

Then intermediate data is obtained: calculate accuracy CorrectRate according to equation below:

Wherein, correct function number represents the function number meeting constraints, and general function number represents the function sum that this framework comprises.

C) reliability data is obtained:

First obtain metadata: the method using mathematical statistics or expertise, obtain the basic participant of framework and perform the probability of failure of probability and each member connecting；

Then intermediate data is obtained: calculate reliability Reliability according to equation below:

$\mathrm{Re}liabi1ity=\underset{i=1}{\overset{m}{\Σ}}({\mathrm{ActorEP}}_i\×\underset{j=1}{\overset{n}{\Σ}}({\mathrm{ucEP}}_j\×\frac{1}{k}\×\underset{1}{\overset{k}{\Σ}}(\underset{p}{\Π}{\mathrm{component}}_p^{x_p}\×\underset{q}{\Π}{\mathrm{component}}_q^{x_q})))$

Wherein, component_pIt is the probability of success of component p, x in component diagram_pIt is that it performs number of times；Connector_qIt is the probability of success of each connector, y in component diagram_qIt is that it performs number of times；K be in component diagram with certain use-case related application scene number；ucEP_jBeing the execution probability of use-case j, n is the number of the use-case being connected with certain user；ActorEP_iBeing the user i probability using system, m is the number of user；

Step 3) according to the dynamic Maturity DSAM of following formula computing architecture:

DSAM=(CorrectRate × Reliability)^Performance。

Further, in the inventive method, being all millisecond about the linear module of time in the formula of computing architecture performance Performance, the linear module of internal memory is all byte, and the linear module about CPU is the percentage ratio taken；Calculating in the process of accuracy CorrectRate, described constraints refers to the content of definition in user's linear time temporal logic constraint document；The i.e. corresponding function of each precedence diagram, each function need to meet multiple condition simultaneously, as long as there being a condition to be unsatisfactory for, then be considered as this function and do not satisfy the constraint condition.

Further, in the inventive method, described step 3) in, when accuracy and reliability, the two is arbitrary when being 0, according to the dynamic Maturity DSAM of following formula computing architecture:

DSAM=0.05^Performance

When accuracy and reliability are 1 simultaneously, according to the dynamic Maturity DSAM of following formula computing architecture:

DSAM=0.95^Performance。

DSAM chooses reliability, accuracy and three angles of performance and is the bigger the better to the metric showing the behavior characteristics of framework, reliability and accuracy, and performance is then the smaller the better, as follows according to this feature DSAM computing formula:

DSAM=(CorrectRate × Reliability)^Performance

The form of the computing formula of the dynamic Maturity of above-mentioned framework is exponential function, and with performance, reliability and accuracy for input parameter, wherein performance parameter is more big, represents and more can not meet user performance demand, calculates the dynamic Maturity of framework got more low；And accuracy and reliability are more big, represent use this framework exploitation software have bigger probability assurance function correctly run, failure, thus calculate the dynamic Maturity of framework higher.

The present invention utilizes framework attribute measure to realize the data collection that the dynamic Maturity of framework (DSAM, DynamicSoftwareArchitectureMaturity) is measured, and calculates DSAM according to the data collected further.

Beneficial effect: the present invention compared with prior art, has the advantage that

Framework represents the high-level design of software development, and for design measure often adopt expert assessment and evaluation, check design principle meet situation, etc. method carry out qualitative measure, and the design documentation paid close attention to mostly is detailed design phase product, such as class figure etc., the measurement results existed is too unilateral, excessively rely on the problems such as expertise, thus the present invention be compared with prior art, there is following advantage:

(1) the inventive method is measured for the framework document of software development commitment, instructs framework to improve further, such that it is able to effectively reduce the risk and cost in software development process；

(2) result that the present invention obtains using framework emulation, formal verification and attribute measure inputs parameter as DSAM tolerance, and Data Source is more rich, and inspection target is more, and more objective；

(3) result that the inventive method is final is the dynamic Maturity of framework, shows as concrete numerical value, instruction framework dynamic behaviour meets the situation of user's request, to user with direct feel.

Accompanying drawing explanation

Fig. 1 is that DSAM measures flow chart；

Fig. 2 is component diagram

Fig. 3 is deployment diagram

Fig. 4 is system sequence diagrams

Fig. 5 is Use Case Map

Fig. 6 is Metric precedence diagram

Fig. 7 is ScenarioEvaluate precedence diagram

Fig. 8 is Simulation precedence diagram

Fig. 9 is verification precedence diagram.

Detailed description of the invention

Below in conjunction with embodiment and Figure of description, the present invention is further illustrated.

Describe in order to convenient, it is assumed that there is an examples of architectures, this example uses EA (EnterpriseArchitect) modeling tool to draw component diagram, deployment diagram, system sequence diagrams, Use Case Map and precedence diagram, as shown in Fig. 2 to Fig. 9, and assume that the project that this framework is corresponding is ArchitectureTool and start context is 2.3.

Step 1) qualification inspection: check that whether bibliographic structure and indispensable framework document be complete, wherein bibliographic structure design documentation realizes based on EA instrument, wherein framework describes document and includes component diagram, deployment diagram, Use Case Map, precedence diagram, system sequence diagrams and constraint document, this framework is qualified on inspection, it is possible to carry out step 2).

Step 2) data collection, including metadata and intermediate data, specific as follows:

A) performance data is obtained:

In order to better show the performance of this framework, above-mentioned simulation parameter is divided into maximum case and the big class of average case two calculate the worst behavior pattern and average behavior pattern here respectively, further it is divided by with user's expectation, this framework can be obtained at aspect of performance relative to the desired satisfaction degree of user, thus the quality of systematic function is described.It should be noted that value of calculation is more little, illustrate that performance is more high.

Utilize the performance metadata that emulation technology obtains as follows:

User's expected results is as shown in the table:

Weighted value is as follows:

	W1	W2	W3	W4
					Weighted value	1	0.6	0.9	0.8

Then intermediate data is obtained: according to data above in conjunction with Performance formula, calculation of performance indicators, result is 0.553155 (performance indications under bad situation) and 0.75535 (performance indications under average case), the result of performance is the smaller the better, obvious the two numerical value shows that this framework has substantially met the expection of user, but the performance under bad situation to be far superior to the performance indications under average case.

B) accuracy data are obtained:

Accuracy response system provides function to meet the situation of user-defined constraints.Wherein, constraints refers to that user LTL (linear time temporal logic) retrains the condition that in document, the system of definition need to meet, here it is considered that, each precedence diagram is a function, each function need to meet some conditions, as long as having a condition to be unsatisfactory for, then it is incorrect for being considered as this function.Verifying whether this framework meets LTL constraints used here as Formal Verification instrument Spin, metric is more big, represents that the function accuracy of this framework is more high.

First metadata is obtained: it is as follows that the LTL of this framework retrains document content,

//LTLinfo

//Attribute:Correctness

<>(XMIRead>0)

//Attribute:Assertion

([](！(getSDTimeSimulationResult>0)))&&(<>((getSDTimeSimulationResult>0)||(<>getSDResourceSimulationResult)))

//Attribute:Safety

(<>(selectUML>0))->(！(selectUML>0>0)U(analyzeUML>0))

//Attribute:Liveness

(<>(create>0))U(<>(MaintainabilityAnalysis>0))

//Attribute:Fairness

[](((StateXMIRead)&&(！startSDSimulation))->((！startSDSimulation)U(((startSSDSimulation)&&(！startSDSimulation))||([](！startSDSimulation)))))

Above-mentioned LTL retrains in document, defines 5 base attribute: Correctness, Assertion, Safety, Liveness and Fairness altogether.Run Spin instrument, result show ScenarioEvaluate corresponding for Fig. 7 violate in Safety attribute "！(selectUML > 0 > 0) U (analyzeUML > 0) "; represent that selectUML is false until analyzeUML sets up; namely selectUML off-duty is until analyzeUML has run selectUML and just run; and in Fig. 7, the sequential relationship of the two statement representative is that selectUML runs prior to analyzeUML, it is clear that LTL constraint is not satisfied；Simulation precedence diagram corresponding for Fig. 8 violate in Assertion attribute " [] (！(getSDTimeSimulationResult > 0)) ", represent that getSDTimeSimulationResult sets up never, in Fig. 8, this statement is then bound to be run, it is clear that LTL constraint is not satisfied.

This framework has 4 precedence diagrams (Fig. 6～Fig. 9), i.e. 4 functions, and Fig. 7 and Fig. 8 violates the Safety attribute in LTL constraint and Assertion attribute respectively, and namely mistake function number is 2.

Then obtaining intermediate data: mistake function number is 2, general function number is 4, then the accuracy of this framework is 0.5.

C) reliability data is obtained:

Reliability investigates the interaction of intermodule, the component of software for calculation framework and the connector probability of success in each application scenarios of system, thus doping system risk probability.Metric is more big, represents that the reliability of this framework is more high.

First obtaining metadata: according to system running log, can obtain each module probability of failure of system, following table illustrates component probability of failure.

Component name	Probability of failure
		ComprehensiveEvaluation	0.001
Metric	0.0005
		RunFrame	0.001
Scenario	0.002
		Simulation	0.001
Validator	0.001
		Verification	0.001

The contrast relationship of object occurrence number and component in precedence diagram, as shown in the table:

In this example, in conjunction with upper table and precedence diagram 7 to Fig. 9, it is known that the component related in scene is all disposed in the same node, thus the reliability of this framework is not constituted impact by connector.

Use-case performs probability, such as following table.

ComprehensiveEvaluation	0.1
		InputCheck	0.1
Metric	0.2
		Scenario	0.2
Simulation	0.2
		Verification	0.2

As seen from Figure 5, system user only one of which, this user uses the probability of system to be 1, and this user employs 6 use-cases.

Then obtain intermediate data: utilize above-mentioned data, calculate reliability as follows:

Reliability=1* (the 0.1*ComprehensiveEvaluation probability of success+0.1*InputCheck probability of success+0.2*Metric probability of success+0.2*Scenario probability of success+0.2*Simulation probability of success+0.2*Verification probability of success)

=1* (0.1*1+0.1*1+0.2* (1-0.0005) ^ (1+5+1+2+2+1)+0.2* (1-0.002) ^ (3+8+1+5)+0.2* (1-0.001) ^ (6+2+2+2)+0.2* (1-0.001) ^ (3+5+1+1+1+1))

=0.1+0.1+0.2*0.995^12+0.2*0.998^17+0.2*0.999^12+0.2*0.999 ^12

≈0.9769

Step 3) the dynamic Maturity DSAM of computing architecture:

According to formula by step 2) result bring into, obtaining DSAM measurement results under worst performance conditions is 0.67277, and the measurement results under average behavior situation is 0.58204, and the former is substantially better than the latter, and both gaps are caused by do as one likes energy.From DSAM result, this framework known also has the space promoted further, if it is desired to the dynamic Maturity of Lifting Scheme should be started with from the average behavior situation that framework accuracy and framework emulate further.

Above-described embodiment is only the preferred embodiment of the present invention; it is noted that, for those skilled in the art; under the premise without departing from the principles of the invention; some improvement and equivalent replacement can also be made; the claims in the present invention are improved and are equal to the technical scheme after replacing by these, each fall within protection scope of the present invention.

Claims (3)

1. the dynamic Maturity measure of framework, it is characterised in that the method includes the steps of:

Step 1) qualification inspection: inspection framework describes whether the bibliographic structure of document comprises all documents carried out needed for DSAM tolerance, in this way, then enter step 2), otherwise, method ends flow process, described framework describes document and includes component diagram, deployment diagram, Use Case Map, precedence diagram, system sequence diagrams and constraint document；

Step 2) collect metadata and intermediate data, specific as follows:

A) performance data is obtained:

First metadata is obtained: utilizing emulation technology to obtain the simulation result of framework, described simulation result includes maximum operation time, average operating time, maximum response time, average response time, maximum memory occupancy, the internal memory utilization of unit interval, maximum CPU occupancy and the CPU occupancy of unit interval；

Then intermediate data is obtained: the performance Performance according to equation below computing architecture:

$Performance=\left\{\begin{array}{c}(W_1\&times;\frac{AvgExcTime}{EpAET}+W_2\&times;\frac{Avg\mathrm{Re}sTime}{EpART}+W_3\&times;\frac{MemUseUnitTime}{EpMUUT}+W_4\&times;\frac{CPUUseUnitTime}{EpCUUT})\&times;\frac{1}{4}\\ (W_1\&times;\frac{MaxExcTime}{EpMET}+W_2\&times;\frac{Max\mathrm{Re}sTime}{EpMRT}+W_3\&times;\frac{MaxMemUse}{EpMMU}+W_4\&times;\frac{MaxCPUUse}{EpMCU})\&times;\frac{1}{4}\end{array}\right.$

Wherein, MaxExcTime represents the maximum operation time, and namely in all interaction sequence, the maximum duration of user and system interaction, AvgExcTime represents the average operation time, i.e. average time required for all interaction sequence；

MaxResTime represents maximum response time, namely in all user operations, and the maximum response time of system of users, AvgResTime represents average response time, namely in all user operations, the average response time of system of users；

MaxMemUse represents maximum memory occupancy, and namely in all interaction sequence execution processes, the maximum occupancy of internal memory, MemUseUnitTime represents the internal memory utilization of unit interval, i.e. all interaction sequence unit interval internal memory utilizations；

MaxCPUUse represents maximum CPU occupancy, and namely in all interaction sequence execution processes, the maximum occupancy of CPU, CPUUseUnitTime represents the CPU occupancy of unit interval, i.e. all interaction sequence unit interval CPU utilizations；

EpAET represents the desired average operating time of user, and EpMET represents user's desired maximum operation time；

EpART represents the desired average response time of user, and EpMRT represents the desired maximum response time of user；

EpMUUT represents the desired unit interval internal memory utilization of user, and EpMMU represents the desired maximum memory occupancy of user；

EpCUUT represents user's utilization of desired unit interval CPU, and EpMCU represents the desired maximum CPU occupancy of user；

W₁, W₂, W₃And W₄For weight parameter, wherein W₁Represent the weight of operation time, W₂Represent the weight of response time, W₃Represent the weight of EMS memory occupation amount, W₄Represent that CPU makes the weight of consumption.Further, W₁, W₂, W₃And W₄Span be all (0,1)；

B) accuracy data are obtained:

First obtaining metadata: utilize Formal Verification, verify whether precedence diagram corresponding to each function meets constraints, statistics obtains the function number being unsatisfactory for constraint further, i.e. mistake function number；

Then intermediate data is obtained: calculate accuracy CorrectRate according to equation below:

Wherein, correct function number represents the function number meeting constraints, and general function number represents the function sum that this framework comprises；

C) reliability data is obtained:

First obtaining metadata: the method using mathematical statistics or expertise, the participant obtaining framework performs the probability of failure of probability and each member connecting；

Then intermediate data is obtained: according to equation below computing architecture reliability Reliability:

$\mathrm{Re}liability=\underset{i=1}{\overset{m}{\&Sigma;}}({\mathrm{ActorEP}}_i\&times;\underset{j=1}{\overset{n}{\&Sigma;}}({\mathrm{ucEP}}_j\&times;\frac{1}{k}\&times;\underset{1}{\overset{k}{\&Sigma;}}\left(\underset{p}{\&Pi;}{\mathrm{component}}_p^{x_p}\&times;\underset{q}{\&Pi;}{\mathrm{component}}_q^{x_q}\right)\left)\right)$

Wherein, component_pIt is the probability of success of component p, x in component diagram_pIt is that it performs number of times；Connector_qIt is the probability of success of each connector, y in component diagram_qIt is that it performs number of times；K be in component diagram with certain use-case related application scene number；ucEP_jBeing the execution probability of use-case j, n is the number of the use-case being connected with certain user；ActorEP_iBeing the user i probability using system, m is the number of user；

Step 3) according to the dynamic Maturity DSAM of following formula computing architecture:

DSAM=(CorrectRate × Reliability)^Performance。

2. a kind of dynamic Maturity measure of framework according to claim 1, it is characterized in that, described step 2) in, the formula of computing architecture performance Performance is all millisecond about the linear module of time, the linear module of internal memory is all byte, and the linear module about CPU is the percentage ratio taken；Calculating in the process of accuracy CorrectRate, described constraints refers to the content of definition in user's linear time temporal logic constraint document；The i.e. corresponding function of each precedence diagram, each function need to meet multiple condition simultaneously, as long as there being a condition to be unsatisfactory for, then be considered as this function and do not satisfy the constraint condition.

3. a kind of dynamic Maturity measure of framework according to claim 1, it is characterised in that described step 3) in, when accuracy and reliability, the two is arbitrary when being 0, according to the dynamic Maturity DSAM of following formula computing architecture:

DSAM=0.05^Performance

When accuracy and reliability are 1 simultaneously, according to the dynamic Maturity DSAM of following formula computing architecture:

DSAM=0.95^Performance。