CN101986268A - Method for transforming reliable model into GSPN model based on AADL description - Google Patents

Method for transforming reliable model into GSPN model based on AADL description Download PDF

Info

Publication number
CN101986268A
CN101986268A CN2010105542855A CN201010554285A CN101986268A CN 101986268 A CN101986268 A CN 101986268A CN 2010105542855 A CN2010105542855 A CN 2010105542855A CN 201010554285 A CN201010554285 A CN 201010554285A CN 101986268 A CN101986268 A CN 101986268A
Authority
CN
China
Prior art keywords
model
gspn
migration
error
arc
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Pending
Application number
CN2010105542855A
Other languages
Chinese (zh)
Inventor
张凡
畅绍枫
周兴社
董云卫
王广仁
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Northwestern Polytechnical University
Original Assignee
Northwestern Polytechnical University
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Northwestern Polytechnical University filed Critical Northwestern Polytechnical University
Priority to CN2010105542855A priority Critical patent/CN101986268A/en
Publication of CN101986268A publication Critical patent/CN101986268A/en
Pending legal-status Critical Current

Links

Images

Landscapes

  • Stored Programmes (AREA)

Abstract

The invention relates to a method for transforming a reliable model into a GSPN model based on AADL description, which is characterized in that basic error model elements are transformed into basic elements in a GSPN model; an Out-propagation rule for describing outspread errors of a component is transformed, and an In-propagation rule for describing received wrong spreading of the component is transformed; advanced dependence elements are transformed in accordance with interaction of basic dependence elements defined in the error model, and basic elements are added to the GSPN model of the system so as to obtain the GSPN model of the system, wherein the GSPN model of the system is provided with the advanced dependence; and identifications in positions obtained by transforming the Out-propagation rule are cleared so as to obtain an optimized GSPN model of the system. In the invention, the method and the mechanism for establishing the reliable computation model of the AADL based on the GSPON model elements are detailed, and one to one correspondence in the transformation from the AADL model elements to the reliable computation model of the GSPN is realized.

Description

A kind of reliability model of describing based on AADL is to the conversion method of GSPN model
Technical field
The present invention relates to the conversion method of a kind of reliability model of describing based on AADL to the GSPN model, but relate to embedded software use in the AADL reliability model to the conversion method of computation model.
Background technology
For the demand of the embedded system that satisfies development of new, U.S. Mechanic Engineer association has issued air standard AS5506---and framework analysis and design language (Architecture Analysis and Design Language, AADL).AADL is to having good support based on the analysis of model and the description of complicated real time embedded system, and the binding by mutual, the software component between member and member, hardware component and the component of a system is described and analyzes real-time highly reliable embedded system; And system's NOT-function attribute is analyzed and assessed based on the interaction models of system, if the AADL model can not satisfy the demand of NOT-function attribute, can redesign and construct system in this rank of framework so, the feasible requirement of finally satisfying reliability.
The AADL model comprises AADL framework model and AADL error model.The AADL error model replenishes exploitation for AADL carries out the reliability modeling.With AADL framework model and AADL error model is the center, just can set up the AADL reliability model of system.In reliability model, the error model of member is a probabilistic automata, and the composition rule of this probabilistic automata depends on contingent erroneous transmissions and the misdeed management of stating in structure.But though utilize the AADL error model to carry out the reliability modeling to the AADL system architecture, the model of being built has only been described the system model of a static state.For AADL system architecture model is carried out fail-safe analysis and checking, need be described the dynamic interaction behavior between the component of a system in the AADL system architecture reliability model.
Stochastic Petri net has expanded its representation function by introduce time parameter in the Petri net.Stochastic Petri net is as cancellated information flow, is target with the institutional framework and the dynamic behaviour of research model system, in the attention location system contingent various state variation and change between relation.At present, ripe at the research of stochastic Petri net, not only there are solid Fundamentals of Mathematics that a considerable amount of analysis software are also arranged.And various improved stochastic Petri pessimistic concurrency controls constantly are suggested and are applied in the middle of the fail-safe analysis of system.In conjunction with AADL the feature of embedded system is described, and the meaning of petri network element element at random, the state of each member in the AADL model and the transition between state can the use location and migration represent.Therefore can be that stochastic Petri net is analyzed with the AADL model conversion.Consider under the bigger situation of system scale, the problem of state space blast can occur, select model conversion to the Stochastic Petri Nets model.
Stochastic Petri Nets (GSPN) is a kind of expansion to stochastic Petri net, mainly shows migration is divided into two classes: time-shift and instantaneous migration.Wherein, time-shift is associated with the enforcement time-delay of exponential distribution, and the time-delay of instantaneous migration is zero, it is associated with random switching, the priority of instantaneous migration is higher than time-shift, if promptly instantaneous migration and time-shift can be implemented simultaneously, must be that instantaneous migration is implemented.The sign that instantaneous migration produces is the sign that disappears, and is to want cancellation, occurs among the reachability graph that the space of promptly not being at state constitutes, and so just the state space blast problem to system model has played certain mitigation.
Some are arranged at present about from the replacement theory of AADL reliability model to the GSPN model of reliability calculation, by these theoretical analysises, can realize the conversion of fundamental errors model element, basic dependence element (Out-propagation, In-propagation and between the two mutual) and senior dependence element (Guard_In, Guard_Out) to the GSPN model of reliability calculation.Yet, research before is when realizing the AADL element to the GSPN model conversion, mainly adopted the mode of application example that these elements are described, and realizing that dependence element (as Out-In-propagation, Guard_In, Guard_Out) is when the GSPN model element is changed, dependence element and GSPN model element are not realized correspondence clearly, brought many challenges based on the systems reliability analysis assessment automation tools of AADL model for like this design.
Summary of the invention
The technical matters that solves
For fear of the deficiencies in the prior art part, the present invention proposes the conversion method of a kind of reliability model of describing based on AADL to the GSPN model, refinement set up the method and the mechanism of AADL model of reliability calculation based on the GSPN model element, realized that the AADL model element is transformed into the one-to-one relationship between the GSPN reliability model element.
Technical scheme
A kind of reliability model of describing based on AADL is characterized in that to the conversion method of GSPN model step is as follows:
Step 1: the fundamental errors model element is converted to fundamental element in the GSPN model, obtains the basic GSPN model of member, described transformation rule is as follows:
With erroneous state transitions is the position;
With the initial error state exchange is the position of tape identification;
Situation according to Poisson distribution or fixation probability distribution take place to obey error event is converted into two kinds of time-shift and instantaneous migrations respectively, and wherein the parameter of Qian Yi time parameter and error event is identical;
Transition between error condition are converted to the arc and the arc of moving to position of position to migration;
Step 2: according to the difference of the outside error propagation regularity of distribution of member, the Out-propagation rule of describing the outside propagate errors of member is changed, and change describing the In-propagation rule that member receives error propagation, realized conversion, obtained the GSPN model of each member basic dependence element;
According to the difference of the outside error propagation regularity of distribution of member, the Out-propagation rule of describing the outside propagate errors of member is converted to following 2 kinds:
When obeying Poisson distribution, in the basic GSPN model of member, add two fundamental elements: time-shift and position; Adopt the one-way arc tie-time to move to the position then, adopt and forbid that the arc link position moved to the time, the initial error state of employing one-way arc connecting elements correspondence moved to the time, and the one-way arc tie-time is moved to the purpose error condition of member correspondence; The error source of noting the position is the initial error state of member;
When obeying the fixation probability distribution, in the basic GSPN model of member, add two instantaneous migration fundamental elements: prop and Notprop; Two position fundamental element: Outprop and NotOutprop; Adopt one-way arc to connect prop to Outprop then, one-way arc connects Notprop to NotOutprop; Employing forbids that arc connects Outprop to prop, forbids that arc connects NotOutprop to Notprop; Employing forbids that arc connects Outprop to Notprop, forbids that arc connects NotOutprop to prop; The initial error state that adopts one-way arc connecting elements correspondence is to instantaneous migration prop, and one-way arc connects the purpose error condition of instantaneous migration prop to the member correspondence; The wrong original state that adopts two-way arc connecting elements is to instantaneous migration Notprop; Position and instantaneous migration that described Outprop and prop represent to make a mistake and propagate; Position and instantaneous migration that described NotOutprop and Notprop represent not make a mistake and propagate; The error source of position that noting makes a mistake propagates and the position of not making a mistake propagation all is the initial error state of member;
The In-propagation rule of describing member reception error propagation is changed: in the basic GSPN model of member, add an instantaneous migration fundamental element, the initial error state that adopts one-way arc connecting elements correspondence is to instantaneous migration, and one-way arc connects instantaneous purpose error condition of moving to the member correspondence;
Step 3: mutual according to the basic dependence element that defines in the error model, to between the GSPN of member model, add two-way arc fundamental element, adopt two-way arc to connect to make a mistake the position of propagating to instantaneous migration, obtain having GSPN model basic dependence, that realized system mutual between member; The reception sources of the position that noting makes a mistake propagates is the initial error state of the member that is connected with this instantaneous migration, and the position of the propagation that do not make a mistake does not have reception sources;
Step 4: senior dependence element is changed, in the GSPN of system model, added the arc fundamental element, obtain having the GSPN model of the system of senior dependence:
Adopt the arc link position to the regular applied migration of Guard_Out: according to the conditional logic expression formula in the when statement in the Guard_Out rule, if the variable in the expression formula is the form of stateorpropagation, adopt two-way arc link position to migration, if the form of Not stateorpropagation then adopts and forbids that the arc link position is to migration;
Adopt the arc link position to the regular applied migration of Guard_In: according to the conditional logic expression formula in the when statement in the Guard_In rule, if the variable in the expression formula is the form of stateorpropagation, adopt two-way arc link position to migration, if the form of Not stateorpropagation adopts and forbids that the arc link position is to migration;
Step 5: the sign in the position that the Out-propagation rule in the step 2 is converted to empties:
In the GSPN of system model, add instantaneous migration fundamental element;
Set up Boolean expression:
Figure BSA00000355138100051
Wherein Locative error source,
Figure BSA00000355138100053
Locative reception sources; The abbreviation expression formula, variable in the IF expression is the form of stateorpropagation, then adopt two-way arc connection error source or reception sources to instantaneous migration, if the form of Not stateorpropagation then adopts and forbids that arc connection error source or reception sources are to instantaneous migration; Adopt the one-way arc link position to instantaneous migration at last.All implement said process for each position, the GSPN model of the system that is optimized at last.
Beneficial effect
The present invention proposes a kind of reliability model of describing based on AADL is to the conversion method of GSPN model, refinement set up the method and the mechanism of AADL model of reliability calculation based on the GSPN model element, realized that the AADL model element is transformed into the one-to-one relationship between the GSPN reliability model element.
Description of drawings
Fig. 1 has described flow process of the invention process;
Fig. 2 is the system architecture diagram of the embodiment of the invention;
The basic GSPN model of each member in Fig. 3 system;
The GSPN model that has each member of basic dependence in Fig. 4 system;
The GSPN model of the basic dependence element interactions of Fig. 5;
The GSPN model of the senior dependence element of Fig. 6;
Fig. 7 has the system GSPN model of senior dependence;
Fig. 8 empties the GSPN model that identifies in the position;
The GSPN model of Fig. 9 Sample system.
Embodiment
Now in conjunction with the embodiments, accompanying drawing is further described the present invention: the AADL framework model code of system:
system?sample
end?sample;
system?proptofirst
features
tofirst:out?data?port;
end?proptofirst;
system?first
features
inp:in?data?port;
firsttothird:out?data?port;
end?first;
system?second
features
secondtothird:out?data?port;
end?second;
system?third
features
fromfirst:in?data?port;
fromsecond:in?data?port;
--fromsecond_1:in?data?port;
end?third;
system?implementation?sample.impl
subcomponents
comp0:system?proptofirst.impl;
comp1:system?first.impl;
comp2:system?second.impl;
comp3:system?third.impl;
connections
dataconnection1:data?port?comp0.tofirst->comp1.inp;
dataconnection2:data?port?comp1.firsttothird->comp3.fromfirst;
dataconnection3:data?port?comp2.secondtothird->comp3.fromsecond;
end?sample.impl;
system?implementation?proptofirst.impl
annex?Error_Model{**
Model=>errormodels::propEM.impl;
**};
end?proptofirst.impl;
system?implementation?first.impl
annex?Error_Model{**
Model=>errormodels::firstEM.impl;
Guard_Out=>outprop1?when?inp[outprop]and?self[s1],
mask?when?others
applies?to?firsttothird;
**};
end?first.impl;
system?implementation?second.impl
annex?Error_Model{**
Model=>errormodels::secondEM.impl;
**};
end?second.impl;
system?implementation?third.impl
annex?Error_Model{**
Model=>errormodels::thirdEM.impl;
Guard_In=>
prop1?when?fromfirst[outprop1]and?fromsecond[s2],
prop2?when(not?fromfirst[outprop1])and?fromsecond[s2],
mask?when?others
applies?to?fromfirst,fromsecond;
**};
end?third.impl;
Be corresponding error model code below:
package?errormodels
public
annex?Error_Model{**
error?model?propEM
features
error_free:initial?error?state;
failed:error?state;
outprop:out?error?propagation{occurrence=>fixed?0.99};
end?propEM;
error?model?implementation?propEM.impl
transitions
error_free-[out?outprop]->failed;
end?propEM.impl;
error?model?firstEM
features
s1:initial?error?state;
failed:error?state;
outprop1:out?error?propagation{occurrence=>poisson?0.9};
end?firstEM;
error?model?implementation?firstEM.impl
transitions
s1-[out?outprop1]->failed;
end?firstEM.impl;
error?model?secondEM
features
s2:initial?error?state;
fail:error?state;
sec_failedprop:out?error?propagation{occurrence=>poisson?0.89};
recover:error?event{occurrence=>poisson?0.89};
end?secondEM;
error?modelimplementation?secondEM.impl
transitions
s2-[recover]->s2;
s2-[out?sec_failedprop]->fail;
end?secondEM.impl;
error?model?thirdEM
features
In_src:initial?error?state;
In_dst1,In_dst2,fail:error?state;
prop1,prop2,sec_failedprop:in?error?propagation;
end?thirdEM;
error?model?implementation?thirdEM.impl
transitions
In_src-[prop1]->In_dst1;
In_src-[prop2]->In_dst2;
In_src-[in?sec_failedprop]->fail;
end?thirdEM.impl;
**};
end?errormodels;
1 the error state in the error model in the AADL system and error event be converted to position and migration fundamental element respectively set by step.Convert the status change that defines in the transitions rule to the arc fundamental element, obtain the basic GSPN model of each member, as shown in Figure 3.
2 (1) the Out-propagation rule of describing the outside propagate errors of member changed set by step, in the GSPN of member comp0 model, add two instantaneous migration fundamental elements: comp0.outpropT and comp0.NotoutpropT, two position fundamental element: comp0.outprop and comp0.Notoutprop then adopt one-way arc, forbid that arc connects corresponding position to migration.Add time-shift fundamental element: comp1.outprop1T in the GSPN of member comp1 model, position fundamental element comp1.outprop1 then adopts one-way arc, forbids that arc connects corresponding position to migration that the conversion of member comp2 is similar.
(2) the In-propagation rule of describing member reception error propagation is changed, in the GSPN of member comp3 model, add instantaneous migration fundamental element: comp3.prop1, comp3.prop2 and comp3.sec_failedprop, the initial error state that adopts the one-way arc connecting elements is to instantaneous migration, and one-way arc connects the instantaneous purpose error condition of moving to.
Said process has been realized the conversion to basic dependence element, has obtained the GSPN model of each member, as shown in Figure 4.
Set by step 3, there be the mutual of error propagation between member comp2 and the member comp3, adopt two-way arc link position comp2.sec_failedprop to migration comp3.sec_failedprop, obtain having GSPN model basic dependence, that realized system mutual between member.As shown in Figure 5, observe for convenient, only provide the two-way arc that adds in this step 3 among Fig. 5, other parts of the GSPN model of system are identical with Fig. 4.
Defined the Guard_Out rule in the framework model of 4 (1) member comp1 set by step, adopted two-way arc to connect comp0.outprop to comp1.outprop1T, two-way arc connects comp1.s1 to comp1.outprop1T;
(2) defined the Guard_In rule in the framework model of member comp3, adopted two-way arc link position comp1.outprop1 to instantaneous migration comp3.prop1, two-way arc link position comp2.s2 respectively arrives instantaneous migration comp3.prop1 and comp3.prop2; Employing forbids that arc connects comp1.outprop1 to instantaneous migration comp3.prop2.
The arc that adds in the step 4 as shown in Figure 6.So far, obtained having the GSPN model of the system of senior dependence, as shown in Figure 7.
Sign in the position that is converted to of the 5 pairs of Out-propagation rules set by step.The position that need in the GSPN model of this system empty has: comp0.outprop, comp0.Notoutprop, comp1.outprop1 and comp2.sec_failedprop.The method that comp0.outprop is emptied is as follows: add instantaneous migration fundamental element T7 to the GSPN of system model; The error source of position comp0.outprop is comp0.error_free, and reception sources is comp1.s1, sets up Boolean expression to be:
Figure BSA00000355138100101
, adopt and forbid arc link position comp0.error_free to T7, forbid that arc connects comp1.s1 to T7; Adopt one-way arc to connect comp0.outprop to T7, the GSPN model that obtains as shown in Figure 8.
The method that empties to other positions is identical, the system GSPN model that is optimized at last, as shown in Figure 9.
So far, method has realized the conversion to the GSPN model of reliability calculation of fundamental errors model element, basic dependence element (Out-propagation, In-propagation and between the two mutual) and senior dependence element (Guard_In, Guard_Out), and has realized the optimization to system model.

Claims (1)

1. a reliability model of describing based on AADL is characterized in that to the conversion method of GSPN model step is as follows:
Step 1: the fundamental errors model element is converted to fundamental element in the GSPN model, obtains the basic GSPN model of member, described transformation rule is as follows:
With erroneous state transitions is the position;
With the initial error state exchange is the position of tape identification;
Situation according to Poisson distribution or fixation probability distribution take place to obey error event is converted into two kinds of time-shift and instantaneous migrations respectively, and wherein the parameter of Qian Yi time parameter and error event is identical;
Transition between error condition are converted to the arc and the arc of moving to position of position to migration;
Step 2: according to the difference of the outside error propagation regularity of distribution of member, the Out-propagation rule of describing the outside propagate errors of member is changed, and change describing the In-propagation rule that member receives error propagation, realized conversion, obtained the GSPN model of each member basic dependence element;
According to the difference of the outside error propagation regularity of distribution of member, the Out-propagation rule of describing the outside propagate errors of member is converted to following 2 kinds:
When obeying Poisson distribution, in the basic GSPN model of member, add two fundamental elements: time-shift and position; Adopt the one-way arc tie-time to move to the position then, adopt and forbid that the arc link position moved to the time, the initial error state of employing one-way arc connecting elements correspondence moved to the time, and the one-way arc tie-time is moved to the purpose error condition of member correspondence; The error source of noting the position is the initial error state of member;
When obeying the fixation probability distribution, in the basic GSPN model of member, add two instantaneous migration fundamental elements: prop and Notprop; Two position fundamental element: Outprop and NotOutprop; Adopt one-way arc to connect prop to Outprop then, one-way arc connects Notprop to NotOutprop; Employing forbids that arc connects Outprop to prop, forbids that arc connects NotOutprop to Notprop; Employing forbids that arc connects Outprop to Notprop, forbids that arc connects NotOutprop to prop; The initial error state that adopts one-way arc connecting elements correspondence is to instantaneous migration prop, and one-way arc connects the purpose error condition of instantaneous migration prop to the member correspondence; The wrong original state that adopts two-way arc connecting elements is to instantaneous migration Notprop; Position and instantaneous migration that described Outprop and prop represent to make a mistake and propagate; Position and instantaneous migration that described NotOutprop and Notprop represent not make a mistake and propagate; The error source of position that noting makes a mistake propagates and the position of not making a mistake propagation all is the initial error state of member;
The In-propagation rule of describing member reception error propagation is changed: in the basic GSPN model of member, add an instantaneous migration fundamental element, the initial error state that adopts one-way arc connecting elements correspondence is to instantaneous migration, and one-way arc connects instantaneous purpose error condition of moving to the member correspondence;
Step 3: mutual according to the basic dependence element that defines in the error model, to between the GSPN of member model, add two-way arc fundamental element, adopt two-way arc to connect to make a mistake the position of propagating to instantaneous migration, obtain having GSPN model basic dependence, that realized system mutual between member; The reception sources of the position that noting makes a mistake propagates is the initial error state of the member that is connected with this instantaneous migration, and the position of the propagation that do not make a mistake does not have reception sources;
Step 4: senior dependence element is changed, in the GSPN of system model, added the arc fundamental element, obtain having the GSPN model of the system of senior dependence:
Adopt the arc link position to the regular applied migration of Guard_Out: according to the conditional logic expression formula in the when statement in the Guard_Out rule, if the variable in the expression formula is the form of stateorpropagation, adopt two-way arc link position to migration, if the form of Not stateorpropagation then adopts and forbids that the arc link position is to migration;
Adopt the arc link position to the regular applied migration of Guard_In: according to the conditional logic expression formula in the when statement in the Guard_In rule, if the variable in the expression formula is the form of stateorpropagation, adopt two-way arc link position to migration, if the form of Not stateorpropagation adopts and forbids that the arc link position is to migration;
Step 5: the sign in the position that the Out-propagation rule in the step 2 is converted to empties:
In the GSPN of system model, add instantaneous migration fundamental element;
Set up Boolean expression:
Figure FSA00000355138000031
Wherein
Figure FSA00000355138000032
Locative error source,
Figure FSA00000355138000033
Locative reception sources; The abbreviation expression formula, variable in the IF expression is the form of stateorpropagation, then adopt two-way arc connection error source or reception sources to instantaneous migration, if the form of Not stateorpropagation then adopts and forbids that arc connection error source or reception sources are to instantaneous migration; Adopt the one-way arc link position to instantaneous migration at last.All implement said process for each position, the GSPN model of the system that is optimized at last.
CN2010105542855A 2010-11-18 2010-11-18 Method for transforming reliable model into GSPN model based on AADL description Pending CN101986268A (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN2010105542855A CN101986268A (en) 2010-11-18 2010-11-18 Method for transforming reliable model into GSPN model based on AADL description

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN2010105542855A CN101986268A (en) 2010-11-18 2010-11-18 Method for transforming reliable model into GSPN model based on AADL description

Publications (1)

Publication Number Publication Date
CN101986268A true CN101986268A (en) 2011-03-16

Family

ID=43710617

Family Applications (1)

Application Number Title Priority Date Filing Date
CN2010105542855A Pending CN101986268A (en) 2010-11-18 2010-11-18 Method for transforming reliable model into GSPN model based on AADL description

Country Status (1)

Country Link
CN (1) CN101986268A (en)

Cited By (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN104598302A (en) * 2015-02-09 2015-05-06 西北工业大学 AADL model schedulability verification method based on resource competition model
CN104680014A (en) * 2015-03-02 2015-06-03 西北工业大学 Quantitative risk analysis method based on embedded system architecture model
CN105701277A (en) * 2016-01-05 2016-06-22 中国航空无线电电子研究所 AADL modeling based avionics system architecture real-time performance analysis method
CN109901825A (en) * 2019-02-28 2019-06-18 北方民族大学 Analysis of Data Conversion method based on AADL V1 and HiP-HOPS
CN112100062A (en) * 2020-08-31 2020-12-18 西北工业大学 Software and hardware integrated AADL (architecture analysis and design language) model reliability evaluation method based on generalized stochastic Petri network

Cited By (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN104598302A (en) * 2015-02-09 2015-05-06 西北工业大学 AADL model schedulability verification method based on resource competition model
CN104598302B (en) * 2015-02-09 2017-10-27 西北工业大学 AADL model schedulability verification methods based on resource contention model
CN104680014A (en) * 2015-03-02 2015-06-03 西北工业大学 Quantitative risk analysis method based on embedded system architecture model
CN105701277A (en) * 2016-01-05 2016-06-22 中国航空无线电电子研究所 AADL modeling based avionics system architecture real-time performance analysis method
CN105701277B (en) * 2016-01-05 2018-11-27 中国航空无线电电子研究所 A kind of avionics system framework real time analysis method based on AADL modeling
CN109901825A (en) * 2019-02-28 2019-06-18 北方民族大学 Analysis of Data Conversion method based on AADL V1 and HiP-HOPS
CN112100062A (en) * 2020-08-31 2020-12-18 西北工业大学 Software and hardware integrated AADL (architecture analysis and design language) model reliability evaluation method based on generalized stochastic Petri network
CN112100062B (en) * 2020-08-31 2023-01-17 西北工业大学 Software and hardware integrated AADL (architecture analysis and design language) model reliability evaluation method based on generalized stochastic Petri network

Similar Documents

Publication Publication Date Title
US9575877B2 (en) Method and system for testing control software of a controlled system
CN101901186B (en) Embedded system reliability analysis and evaluation method
Walker et al. Automatic optimisation of system architectures using EAST-ADL
CN101986268A (en) Method for transforming reliable model into GSPN model based on AADL description
CN108376221A (en) A kind of software system security verification and appraisal procedure based on AADL model extensions
Kang et al. Verifying functional behaviors of automotive products in EAST-ADL2 using UPPAAL-PORT
CN103036739B (en) Formalization method for verification and performance analysis of high reliable communication system
Wan et al. Investigation on composition mechanisms for cyber physical systems
CN110866341A (en) Method for modeling information physical fusion system based on AADL-Modelica
Liu et al. Modeling timed concurrent systems
Denil et al. DEVS for AUTOSAR-based system deployment modeling and simulation
CN102339232B (en) Modeling simulation verification language (MSVL) asynchronous communication system and method
Bu et al. From bounded reachability analysis of linear hybrid automata to verification of industrial CPS and IoT
CN111709138A (en) CPS (cyber physical System) -space-time property oriented hybrid AADL (architecture analysis and design language) modeling and model conversion method
CN102609260A (en) TASM2UPPAAL (timed abstract state machine to UPPAAL) model transforming method
Li et al. Hardware-in-the-loop real-time simulation interface software design
Yi Algebraic reasoning for real-time probabilistic processes with uncertain information
In der Rieden et al. An approach to the pervasive formal specification and verification of an automotive system: Status report
CN113283008A (en) Civil aircraft system behavior state safety verification method based on model conversion
KR101125365B1 (en) Integrated design method of communication protocols with sdl-opnet co-simmulation technique
Schonwald et al. Network-on-chip architecture exploration framework
Su et al. Modeling and verification of component-based systems with data passing using bip
Bagheri et al. Magnifier: A compositional analysis approach for autonomous traffic control
Shaik Reliability modelling and improvement using replications for Cyber Physical Systems
Wang et al. Modelling and verifying communication failure of hybrid systems in HCSP

Legal Events

Date Code Title Description
C06 Publication
PB01 Publication
C10 Entry into substantive examination
SE01 Entry into force of request for substantive examination
RJ01 Rejection of invention patent application after publication

Application publication date: 20110316

RJ01 Rejection of invention patent application after publication