CN110275825A - A kind of software reliability estimation method of Component- Based Development influence power - Google Patents
A kind of software reliability estimation method of Component- Based Development influence power Download PDFInfo
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Abstract
The invention discloses a kind of software reliability estimation methods of Component- Based Development influence power, belong to the technical field of software reliability evaluation, the present invention realizes the abstract and modeling to software system structure by digraph, define the relevant figure attributive character of software, and component affecting power is introduced to the influence of portraying different component to system reliability, component is divided into two class of input/output component and common components first, the influence power measurement model of two class components is established respectively, then the multifarious problem of architecture in complicated software system is handled by labyrinth state mapping mechanism, and then combination member influence power calculates the dependability parameter of each state after conversion, finally establishing reliability model using Markov Chain realizes the assessment of software reliability, improve the accuracy of fail-safe analysis, with stronger universality.
Description
Technical field
The present invention provides a kind of software reliability estimation method of Component- Based Development influence power, belongs to software reliability evaluation neck
Domain.
Background technique
Currently, software reliability evaluation model is broadly divided into two classes according to the difference of test method: based on test data
Reliability growth model (black-box model), the reliability analysis model (whitepack model) based on architecture.Black-box model relies on
The a large amount of fail datas collected in software test procedure carry out fail-safe analysis by probability theory or mathematical statistics knowledge, only
Suitable for the software development later period.Whitepack models coupling software inhouse structure and Member Reliability Analysis information to system global reliability into
Row assessment, can be through software design always, and obtains more and more concerns.In whitepack model, it is based on markov
The reliability estimation method of chain is most widely used.
Position of the different component in software systems is different, and influence of their failure to whole system also phase not to the utmost
Together.As software systems develop to direction is complicated, being continuously increased of scale and function, internal interaction mechanism are increasingly complicated,
Influence of the software inhouse different component to system reliability has been difficult to ignore, and component shadow should be analyzed during reliability assessment
It rings.And software reliability analysis method based on Markov chain require software inhouse component be all satisfied Markov property and
Independent failure condition, and actual software systems internal structure not necessarily all meets above-mentioned condition, directly goes to comment using above-mentioned model
The reliability for estimating these software systems is inaccurate.
As software systems develop to direction is complicated, being continuously increased of scale and function, internal interaction mechanism are increasingly
Complexity, influence of the software inhouse different component to system reliability have been difficult to ignore, and software inhouse structure has complexity
And Biodiversity Characteristics, composition component not necessarily all meets Markov property and independent failure is assumed.
It would therefore be desirable to which new method studies increasingly complicated software systems, component affecting can either be considered exist
It is interior, and complicated software system internal architecture diverse problems can be solved by certain conversion regime.
Summary of the invention
Goal of the invention: the purpose of the present invention is to provide a kind of software reliability estimation method of Component- Based Development influence power,
The method increase the accuracy of reliability assessment result, reasonability, there is stronger universality, and suitable for before software development
The reliability assessment and optimization design of phase works.
Technical solution: to achieve the above object, the present invention adopts the following technical scheme:
A kind of software reliability estimation method of Component- Based Development influence power, comprising the following steps:
S1, analysis software source code establish software architecture Directed Graph Model, define software correlation figure attributive character,
And it is mapped as adjacency matrix；
S2 introduces component affecting power and is used to describe influence of the different component to system reliability, Component- Based Development degree of influence
It measures model and calculates each component affecting power；
S3 completes the conversion of component to system mode according to labyrinth state mapping mechanism, and by these separate states
It is integrated into system global state model；
S4, the state model of combination member influence power and the system overall situation calculate the corresponding dependability parameter of each state；
S5 establishes state-transition matrix, establishes reliability model assessment software reliability using Markov Chain.
Further, the step S1 includes parsing to the source code of software, by the class or function in source code
Regard component as, regards the inheritance between class or the call relation between function as side, then software configuration can be used one and have
To figure G=<C, E>describe；
Wherein, software correlation figure attributive character is defined as follows: each node C in digraph Gi(i=1,2 ..., m) table
Show that an independent component, m are the component sum for including inside software systems；Directed edge eikIndicate one may occur by structure
Part CiIt is directed toward component CkTransfer path, be denoted as Ci→Ck；By all by CiThe collection of the component of calling is collectively referred to as request and relies on component
Set, is denoted asBy all calling CiComponent collection be collectively referred to as service rely on component
Set, is denoted as M is the component sum for including inside software systems；From component CiOut
The quantity of whole directed edges of hair is known as component CiOut-degree, be denoted as dout(i)；End at component CiWhole directed edges quantity
Referred to as component CiIn-degree, be denoted as din(i)。
Further, the step S2 includes: that position of the different component in software systems is different, is failed to system
The influence of reliability is also different, and influence degree of the component failure to system is defined as component affecting power by we；First by component
It is divided into two class of input and output component and common components by type, provides input and output component affecting power θiCalculation formula is as follows:
In formula, E (μi) indicate component CiExecution frequency, i.e., the component C in system operationiIt is total to execute number μi's
Mathematic expectaion, the value can be obtained by transition probability between analysis Operation Profile and component；N indicates defeated included in software systems
Enter/the sum of output link；Particularly, it is inputted in single-input single-output system, the component affecting power that output link has is
1；
The component affecting power λ of common componentsiIt is then codetermined, is led to by the different degree of its own and the different degree of adjoining members
It crosses and relies on component service and request the analysis relied on, will abut against component and be further subdivided into forerunner's component (before front member is
Drive the server of component) and subsequent component (requestor that front member is subsequent component), therefore common components influence power calculates public affairs
Formula is as follows:
In formula, ImpiIndicate component CiDifferent degree, component C can be passed throughiExecution frequency E (μi) portray；N1 and n2
Request is respectively indicated to rely on component set A and service the element number relied in component set B；din(i) and dout(i) difference table
Show component CiIn-degree and out-degree；Parameter alpha1And α2For the ratio between adjustment means itself different degree and adjoining members different degree
Weight, hasValue between [0,1].
Further, the step S3 includes:
The component for identifying particular architecture according to component composition characteristic first, for sequence-branched structure, software structure
Part successively executes in order, and front member is finished, and next component can just execute, each component CiCorrespond to a state
Node Si；For concurrent structure, multiple components can complete the same task with concurrent working, will concurrently execute in state diagram
N component is merged into a concurrent state SPIt is calculated；For interrupting fault-tolerant architecture, when main member loses in program operation process
When effect, backup component replaces main member in time and works to guarantee the normal operation of software, will interrupt fault-tolerant knot in state diagram
N component of structure is merged into one and interrupts fault-tolerant state STIt is calculated；For non-interrupted fault-tolerant architecture, n more identical
Component concurrent working complete the same task, redundancy backup of the component of successful execution as failure member, it is considered that
Then the state no-failure occurs at least M (M >=[n/2]+1) a component successful execution, by non-interrupted fault-tolerant architecture in state diagram
Component be merged into a non-interrupted fault-tolerant state SNTo calculate；For calling-return structure, front member is to complete specific
It is engaged in and other member functions need to be called, continued to execute after the return of other component results, each component CiCorrespond to a state
Node Si；Above procedure is repeated, it, will be above-mentioned only until all system modes are all satisfied Markov property and independent failure condition
Vertical state is integrated into system global state, establishes new system global state model.
Further, the step S4 includes: to conclude to the affiliated type of state after conversion, if normal state
Si, corresponding dependability parameter are as follows:
In formula, riIt is the original dependability parameter of component, RiIt is to consider normal state S after component affecting poweriReliability ginseng
Number.If above formula illustrates certain component CiComponent affecting power it is very low close to 0, then Ri→ 1, that is, illustrate that the reliability of the component becomes
Change has little effect the reliability of software systems entirety；
The concurrent state S integrated for n componentP, corresponding dependability parameter are as follows:
The fault-tolerant state S of interruption integrated for n componentT, corresponding dependability parameter are as follows:
The non-interrupted fault-tolerant state S integrated for n componentN, corresponding dependability parameter are as follows:
Further, include: in the step S5
Q ' is enabled to be a m × m and consider the step random transferring probability matrix after component affecting power, RSIt is that software systems can
By property；Provide the software reliability evaluation model based on Markov theory are as follows:
In formula, I is the unit matrix of a m × m, | I-Q ' | the determinant of representing matrix (I-Q '), E are matrix (I-Q ')
The middle residual matrix deleted after m row and the 1st column, RmIt is end state SmDependability parameter after corresponding component affecting power.
Through the above steps, the building of the software reliability estimation method of Component- Based Development influence power can be completed, for soft
The reliability assessment of part initial stage of development works.
The utility model has the advantages that compared with prior art, the present invention uses software architecture result for blueprint and support, software is established
Architecture Directed Graph Model describes influence of the component to system by introducing a new parameter component affecting power, improves
Accuracy, the reasonability of fail-safe analysis；And new method and different architecture lower member is established respectively arrive system mode
Mapping mechanism is multifarious to solve the problems, such as complex software internal architecture, and then is established using Markov chain new soft
Part Reliability Evaluation Model has stronger universality；The experimental results showed that new method is commented in addition to available scientific and reasonable
Estimate result, moreover it can be used to component set relatively crucial and guidance in software systems reliability optimization process, identification software structure
The reliability design at software development initial stage works.
Detailed description of the invention
Fig. 1 is the software reliability estimation method flow diagram of Component- Based Development influence power；
Fig. 2 is to carry out the abstract component that generates to source code in the software reliability estimation method of Component- Based Development influence power to show
Example；
Fig. 3 is the software configuration Directed Graph Model of software instances；
Fig. 4 is the system mode graph model that software instances map；
Fig. 5 is the reliability growth test result of software instances.
Specific embodiment
To keep the technical problem to be solved in the present invention, technical solution and advantage clearer, below in conjunction with attached drawing and one
A actual software systems reliability analysis example is described in detail.
A kind of software reliability estimation method of Component- Based Development influence power, comprising the following steps:
S1, analysis software source code establish software architecture Directed Graph Model, define software correlation figure attributive character,
And it is mapped as adjacency matrix；
S2 introduces component affecting power and is used to describe influence of the different component to system reliability, Component- Based Development degree of influence
It measures model and calculates each component affecting power；
S3 completes the conversion of component to system mode according to labyrinth state mapping mechanism, and by these separate states
It is integrated into system global state model；
S4, the state model of combination member influence power and the system overall situation calculate the corresponding dependability parameter of each state；
S5 establishes state-transition matrix, establishes reliability model assessment software reliability using Markov Chain.
Step S1 includes parsing to the source code of software, by source code class or function regard component as, by class it
Between inheritance or function between call relation regard side as, then software configuration can be used digraph G=< C, E a > come
Description；
Wherein, software correlation figure attributive character is defined as follows: each node C in digraph Gi(i=1,2 ..., m) table
Show that an independent component, m are the component sum for including inside software systems；Directed edge eikIndicate one may occur by structure
Part CiIt is directed toward component CkTransfer path, be denoted as Ci→Ck；By all by CiThe collection of the component of calling is collectively referred to as request and relies on component
Set, is denoted asBy all calling CiComponent collection be collectively referred to as service rely on structure
Part set, is denoted as From component CiThe quantity of the whole directed edges to set out is known as component
CiOut-degree, be denoted as dout(i)；End at component CiThe quantity of whole directed edges be known as component CiIn-degree, be denoted as din(i)。
Step S2 includes: that position of the different component in software systems is different, the influence failed to system reliability
Difference, influence degree of the component failure to system is defined as component affecting power by we；Component is divided into input by type first
Two class of output link and common components provides input and output component affecting power θiCalculation formula it is as follows:
In formula, E (μi) indicate component CiExecution frequency, i.e., the component C in system operationiIt is total to execute number μi's
Mathematic expectaion, the value can be obtained by transition probability between analysis Operation Profile and component；N indicates defeated included in software systems
Enter/the sum of output link；Particularly, it is inputted in single-input single-output system, the component affecting power that output link has is
1；
The component affecting power λ of common componentsiIt is then codetermined, is led to by the different degree of its own and the different degree of adjoining members
It crosses and relies on component service and request the analysis relied on, will abut against component and be further subdivided into forerunner's component (before front member is
Drive the server of component) and subsequent component (requestor that front member is subsequent component), therefore common components influence power calculates public affairs
Formula is as follows:
In formula, ImpiIndicate component CiDifferent degree, component C can be passed throughiExecution frequency E (μi) portray；N1 and n2
Request is respectively indicated to rely on component set A and service the element number relied in component set B；din(i) and dout(i) difference table
Show component CiIn-degree and out-degree；Parameter alpha1And α2For the ratio between adjustment means itself different degree and adjoining members different degree
Weight, hasValue between [0,1].
Step S3 includes:
The component for identifying particular architecture according to component composition characteristic first, for sequence-branched structure, software structure
Part successively executes in order, and front member is finished, and next component can just execute, each component CiCorrespond to a state
Node Si；For concurrent structure, multiple components can complete the same task with concurrent working, will concurrently execute in state diagram
N component is merged into a concurrent state SPIt is calculated；For interrupting fault-tolerant architecture, when main member loses in program operation process
When effect, backup component replaces main member in time and works to guarantee the normal operation of software, will interrupt fault-tolerant knot in state diagram
N component of structure is merged into one and interrupts fault-tolerant state STIt is calculated；For non-interrupted fault-tolerant architecture, n more identical
Component concurrent working complete the same task, redundancy backup of the component of successful execution as failure member, it is considered that
Then the state no-failure occurs at least M (M >=[n/2]+1) a component successful execution, by non-interrupted fault-tolerant architecture in state diagram
Component be merged into a non-interrupted fault-tolerant state SNTo calculate；For calling-return structure, front member is to complete specific
It is engaged in and other member functions need to be called, continued to execute after the return of other component results, each component CiCorrespond to a state
Node Si；Above procedure is repeated, it, will be above-mentioned only until all system modes are all satisfied Markov property and independent failure condition
Vertical state is integrated into system global state, establishes new system global state model.
Step S4 includes:
The affiliated type of state after conversion is concluded, if normal state Si, corresponding dependability parameter are as follows:
In formula, riIt is the original dependability parameter of component, RiIt is to consider normal state S after component affecting poweriReliability ginseng
Number.If above formula illustrates certain component CiComponent affecting power it is very low close to 0, then Ri→ 1, that is, illustrate that the reliability of the component becomes
Change has little effect the reliability of software systems entirety；
The concurrent state S integrated for n componentP, corresponding dependability parameter are as follows:
The fault-tolerant state S of interruption integrated for n componentT, corresponding dependability parameter are as follows:
The non-interrupted fault-tolerant state S integrated for n componentN, corresponding dependability parameter are as follows:
Step S5 includes: that Q ' is enabled to be a m × m and consider the step random transferring probability matrix after component affecting power, RS
It is software systems reliability；Provide the software reliability evaluation model based on Markov theory are as follows:
In formula, I is the unit matrix of a m × m, | I-Q ' | the determinant of representing matrix (I-Q '), E are matrix (I-Q ')
The middle residual matrix deleted after m row and the 1st column, RmIt is end state SmDependability parameter after corresponding component affecting power.
As shown in Figure 1, the present invention provides a kind of software reliability estimation method of Component- Based Development influence power, including walk as follows
It is rapid:
Step 1, the software given for one, first parses the source code of software, by source code class or
Function regards component as, regards the inheritance between class or the call relation between function as side, using digraph to software knot
Structure is modeled, and is mapped as adjacency matrix；
According to the difference of software programming language, class or function is selected to regard component node as, inheritance or letter between class
Several call relations regard side as, and then are abstracted to the structure of software systems, and Fig. 2, which is that certain software source code is abstract, generates structure
The example of part, Fig. 3 are the software configuration Directed Graph Model schematic diagram that a practical bank transaction software systems are established, and are mapped
The adjacency matrix arrived is as follows:
Step 2, according to adjacency matrix, importance, out-degree, in-degree, request component set A and the service of each component are obtained
Software inhouse component is divided into input and output component C by component set B by type1, C10With two class C of common components2, C3..., C9,
Calculate separately the failure effect power of each component；
For bank transaction software systems as shown in Figure 3, proportionality coefficient is takenFor balance component itself
The influence of different degree and adjoining members different degree obtains each component affecting power and is as follows:
Each component affecting power result of table 1
| λ1 | λ2 | λ3 | λ4 | λ5 |
| 1 | 0.7767 | 0.7115 | 0.793 | 0.793 |
| λ6 | λ7 | λ8 | λ9 | λ10 |
| 0.7851 | 0.7851 | 0.8256 | 0.8457 | 1 |
Step 3, component is sorted out according to the composition characteristic of software architecture, by the specific structure identified
Component is converted into corresponding system mode according to labyrinth state mapping mechanism, and it is complete that these separate states are integrated into system
In the state model of office；
The bank transaction software systems are made of the component of ten different function.Wherein, C1It is input link, by external thing
Part triggering；C10It is output link, is mainly used to complete bill printing function；Component C2And C3Transaction and currency conversion are provided respectively
Two class services；Component C4And C5It can be used to complete task schedule function, C5It is C4Spare component；Component C6And C7Belong to concurrent
Relationship completes the decomposition of task and synchronism output result to component C in same timeslice10；Particularly, component C6, C7And C8?
Need component invoking C9Return to current currency exchange rate information.Based on above-mentioned analysis, turned using labyrinth state mapping mechanism
It changes, wherein component C4And C5Merge into fault-tolerant state ST, component C6And C7Merge into concurrent state Sp, all system modes after conversion
It is all satisfied Markov property and independent failure condition, above-mentioned independent state is integrated into system global state, final
System mode graph model to the bank transaction software is as shown in Figure 5.
Step 4, the state model of combination member influence power and the system overall situation calculates the corresponding dependability parameter of each state；
In conjunction with Fig. 4 and table 1, the corresponding dependability parameter of each state is calculated and is as follows:
Each state transition probability of table 2 and dependability parameter
| System mode | Transition probability | Reliability |
| S1 | P1,2=0.49, P1,3=0.51 | 0.999 |
| S2 | P2, T=1.0 | 0.9797 |
| S3 | P3, T=1.0 | 0.9786 |
| ST | PT, P=0.8, PT, 8=0.2 | 0.9995 |
| SP | PP, 9=0.75, PP, 10=0.25 | 0.9874 |
| S8 | P8,9=0.75, P8,10=0.25 | 0.9934 |
| S9 | P9, P=0.5, P9,8=0.5 | 0.9788 |
| S10 | - | 0.964 |
Step 5, state-transition matrix is established, establishes reliability model using Markov Chain, and calculate using MATLAB
Tools assessment software reliability.
The state-transition matrix for establishing the bank transaction software systems is as follows,
The reliability assessment result for finally obtaining the bank transaction system is
It is 0.865 that the system, which obtains assessment reliability through software test, can be used as system achieved reliability.It is of the present invention
Method introduces influence of the component affecting power from component failure and the multiple angle analysis different components of fault propagation to system reliability
Degree, and labyrinth state mapping mechanism processing software internal architecture diverse problems are established, it can obtain reasonable
Reliability assessment as a result, and system achieved reliability deviation be also only 1.39%.
Due to the limitation of length, reliability optimization process only selects two components to carry out simple analysis, can from table 2
C out9Component affecting power it is maximum, C3Component affecting power it is minimum, which illustrates component C9It may be contacted with other components tighter
It is close, once failure can produce bigger effect system global reliability, and component C3Influence to system global reliability is smaller.
Therefore component C9Than component C3It is more important, improve C9Reliability bring effect of optimization be greater than improve C3Reliability to mentioning
The influence of high system global reliability.For verify this as a result, we using Cheung model to improving Member Reliability Analysis to being
The influence of system global reliability is analyzed, as a result as shown in Figure 5.Fig. 5 illustrates with component C9The growth of reliability, system are whole
Body reliability can be promoted effectively, and be greater than component C3Reliability, which changes bring, to be influenced, the knot that the method for this and we obtain
By identical.
Through the above steps, the building of the software reliability estimation method to Component- Based Development influence power can be completed.At this
In item technology, we use software architecture for blueprint and support, establish software architecture Directed Graph Model, introduce component
Influence power is used to portray influence of the different component to system reliability, and software-based figure attributive character provides component affecting power
Measurement model finally utilizes Ma Er then in conjunction with the state model of component affecting power and the state mapping mechanism building system overall situation
Can husband's chain software reliability is assessed.The experimental results showed that the available reasonable assessment result of the method for the invention,
And it is suitable for reliability assessment and the optimization design work of software development early period.
Non-elaborated part of the present invention belongs to techniques well known.
The above, part specific embodiment only of the present invention, but scope of protection of the present invention is not limited thereto, appoints
In the technical scope disclosed by the present invention, any changes or substitutions that can be easily thought of, should all cover by what those skilled in the art
Within protection scope of the present invention.
Claims (6)
1. a kind of software reliability estimation method of Component- Based Development influence power, it is characterised in that: the following steps are included:
S1, analysis software source code establish software architecture Directed Graph Model, define software correlation figure attributive character, and reflect
It penetrates as adjacency matrix；
S2 introduces component affecting power and is used to describe influence of the different component to system reliability, and Component- Based Development influence power measures mould
Type calculates each component affecting power；
S3 completes the conversion of component to system mode according to labyrinth state mapping mechanism, and these separate states is integrated
Into system global state model；
S4, the state model of combination member influence power and the system overall situation calculate the corresponding dependability parameter of each state；
S5 establishes state-transition matrix, establishes reliability model assessment software reliability using Markov Chain.
2. the software reliability estimation method of Component- Based Development influence power according to claim 1, it is characterised in that: described
Step S1 includes parsing to the source code of software, by source code class or function regard component as, by the succession between class
Call relation between relationship or function regards side as, then software configuration uses digraph a G=<C, E>describe；Software phase
Pass figure attributive character is defined as follows:
Each node C in digraph GiIndicate an independent component, wherein i=1,2 ..., m, m, which are inside software systems, includes
Component sum；Directed edge eikIndicate one may occur by component CiIt is directed toward component CkTransfer path, be denoted as Ci→Ck；It will
It is all by CiThe collection of the component of calling is collectively referred to as request and relies on component set, is denoted as
By all calling CiComponent collection be collectively referred to as service rely on component set, be denoted as
From component CiThe quantity of the whole directed edges to set out is known as component CiOut-degree, be denoted as dout(i)；End at component CiWhole have
It is known as component C to the quantity on sideiIn-degree, be denoted as din(i)。
3. the software reliability estimation method of Component- Based Development influence power according to claim 2, it is characterised in that: described
Step S2 includes:
Influence degree of the component failure to system is defined as component affecting power；Component is divided into input and output structure by type first
Two class of part and common components provides input and output component affecting power θi, wherein i=1,2 ..., m, calculation formula are as follows:
In formula, E (μi) indicate component CiExecution frequency, i.e., the component C in system operationiIt is total to execute number μiThe mathematics phase
It hopes, which can be obtained by transition probability between analysis Operation Profile and component；M is the component sum for including inside software systems；n
Indicate the sum of input/output component included in software systems；
The component affecting power λ of common componentsi, wherein i=1,2 ..., m, then by the important of the different degree of its own and adjoining members
Degree codetermines, and by relying on component service and requesting the analysis relied on, will abut against component and is further subdivided into forerunner's component
With subsequent component, therefore common components influence power calculation formula is as follows:
In formula, ImpiIndicate component CiDifferent degree, pass through component CiExecution frequency E (μi) portray；M is inside software systems
The component sum for including；N1 and n2 respectively indicates request and relies on component set A and service the element relied in component set B
Number；din(i) and dout(i) component C is respectively indicatediIn-degree and out-degree；Parameter alpha1And α2For adjustment means itself different degree and
Specific gravity between adjoining members different degree, has Value between [0,1].
4. the software reliability estimation method of Component- Based Development influence power according to claim 1, it is characterised in that: described
Step S3 includes:
S3.1 identifies the component of particular architecture according to component composition characteristic first, for sequence-branched structure, software
Component successively executes in order, and front member is finished, and next component can just execute, each component CiCorrespond to a shape
State node Si；
S3.2, for concurrent structure, multiple components can complete the same task with concurrent working, will concurrently execute in state diagram
N component be merged into a concurrent state SPIt is calculated；
S3.3, for interrupting fault-tolerant architecture, when major component failure in program operation process, backup component replaces main member in time
It works to guarantee the normal operation of software, n component for interrupting fault-tolerant architecture is merged into an interruption in state diagram and is held
Wrong state STIt is calculated；
S3.4, for non-interrupted fault-tolerant architecture, the same task is completed in n more identical component concurrent workings, success
Redundancy backup of the component of execution as failure member, in state diagram by the component of non-interrupted fault-tolerant architecture be merged into one it is non-in
Break fault-tolerant state SNTo calculate；
S3.5, for calling-return structure, front member is to complete particular task and need to call other member functions, to other
Component result continues to execute after returning, each component CiCorrespond to a state node Si；
S3.6 repeats above procedure, will be above-mentioned until all system modes are all satisfied Markov property and independent failure condition
Independent state is integrated into system global state, establishes new system global state model.
5. the software reliability estimation method of Component- Based Development influence power according to claim 4, it is characterised in that: described
Step S4 includes:
The affiliated type of state after conversion is concluded, if normal state Si, corresponding dependability parameter are as follows:
In formula, riIt is the original dependability parameter of component, RiIt is to consider normal state S after component affecting poweriReliability parameter；
The concurrent state S integrated for n componentP, corresponding dependability parameter RPAre as follows:
The fault-tolerant state S of interruption integrated for n componentT, corresponding dependability parameter RTAre as follows:
The non-interrupted fault-tolerant state S integrated for n componentN, corresponding dependability parameter RNAre as follows:
6. the software reliability estimation method of Component- Based Development influence power according to claim 1, it is characterised in that: described
Step S5 includes:
Q ' is enabled to be a m × m and consider the step random transferring probability matrix after component affecting power, RSIt is software systems reliability；
Provide the software reliability evaluation model based on Markov theory are as follows:
In formula, I is the unit matrix of a m × m, | I-Q ' | the determinant of representing matrix (I-Q '), E are deleted in matrix (I-Q ')
Except the residual matrix after m row and the 1st column, RmIt is end state SmDependability parameter after corresponding component affecting power.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
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| CN110955227A (en) * | 2019-11-22 | 2020-04-03 | 西安电子科技大学 | System fuzzy reliability analysis method based on fuzzy dynamic Bayesian network |
| CN112131723A (en) * | 2020-09-09 | 2020-12-25 | 广西大学 | Markov theory-based energy management system reliability analysis method |
| CN112799890A (en) * | 2020-12-31 | 2021-05-14 | 南京航空航天大学 | Bus SEU-resistant reliability modeling and evaluating method |
| CN113010437A (en) * | 2021-04-27 | 2021-06-22 | 中国人民解放军国防科技大学 | Software system reliability management method and system based on fault analysis |
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| CN110955227A (en) * | 2019-11-22 | 2020-04-03 | 西安电子科技大学 | System fuzzy reliability analysis method based on fuzzy dynamic Bayesian network |
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| CN112799890A (en) * | 2020-12-31 | 2021-05-14 | 南京航空航天大学 | Bus SEU-resistant reliability modeling and evaluating method |
| CN113010437A (en) * | 2021-04-27 | 2021-06-22 | 中国人民解放军国防科技大学 | Software system reliability management method and system based on fault analysis |
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