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Technique for Early Reliability Prediction of Software Components Using Behaviour Models

View Article: PubMed Central - PubMed

ABSTRACT

Behaviour models are the most commonly used input for predicting the reliability of a software system at the early design stage. A component behaviour model reveals the structure and behaviour of the component during the execution of system-level functionalities. There are various challenges related to component reliability prediction at the early design stage based on behaviour models. For example, most of the current reliability techniques do not provide fine-grained sequential behaviour models of individual components and fail to consider the loop entry and exit points in the reliability computation. Moreover, some of the current techniques do not tackle the problem of operational data unavailability and the lack of analysis results that can be valuable for software architects at the early design stage. This paper proposes a reliability prediction technique that, pragmatically, synthesizes system behaviour in the form of a state machine, given a set of scenarios and corresponding constraints as input. The state machine is utilized as a base for generating the component-relevant operational data. The state machine is also used as a source for identifying the nodes and edges of a component probabilistic dependency graph (CPDG). Based on the CPDG, a stack-based algorithm is used to compute the reliability. The proposed technique is evaluated by a comparison with existing techniques and the application of sensitivity analysis to a robotic wheelchair system as a case study. The results indicate that the proposed technique is more relevant at the early design stage compared to existing works, and can provide a more realistic and meaningful prediction.

No MeSH data available.


State machine of “Bank” component (as a result of merging the FSMs shown in Fig 4).
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pone.0163346.g005: State machine of “Bank” component (as a result of merging the FSMs shown in Fig 4).

Mentions: In the final activity in behaviour model construction, we merge the different FSMs of the component by identifying identical terminal and starting states. Two different FSMs will be merged if and only if the terminal state of one is similar to the starting state of the other. The merging transition will be created from a terminal to a start (the transition from a start to a terminal is not allowed). The similarity between the states is determined based on the state vector values of the states. The final output of this phase is the LTS which represents the behaviour of the component. Fig 5 shows the LTS as a result of merging the component FSMs of the “Bank” component shown above in Fig 4.


Technique for Early Reliability Prediction of Software Components Using Behaviour Models
State machine of “Bank” component (as a result of merging the FSMs shown in Fig 4).
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC5036808&req=5

pone.0163346.g005: State machine of “Bank” component (as a result of merging the FSMs shown in Fig 4).
Mentions: In the final activity in behaviour model construction, we merge the different FSMs of the component by identifying identical terminal and starting states. Two different FSMs will be merged if and only if the terminal state of one is similar to the starting state of the other. The merging transition will be created from a terminal to a start (the transition from a start to a terminal is not allowed). The similarity between the states is determined based on the state vector values of the states. The final output of this phase is the LTS which represents the behaviour of the component. Fig 5 shows the LTS as a result of merging the component FSMs of the “Bank” component shown above in Fig 4.

View Article: PubMed Central - PubMed

ABSTRACT

Behaviour models are the most commonly used input for predicting the reliability of a software system at the early design stage. A component behaviour model reveals the structure and behaviour of the component during the execution of system-level functionalities. There are various challenges related to component reliability prediction at the early design stage based on behaviour models. For example, most of the current reliability techniques do not provide fine-grained sequential behaviour models of individual components and fail to consider the loop entry and exit points in the reliability computation. Moreover, some of the current techniques do not tackle the problem of operational data unavailability and the lack of analysis results that can be valuable for software architects at the early design stage. This paper proposes a reliability prediction technique that, pragmatically, synthesizes system behaviour in the form of a state machine, given a set of scenarios and corresponding constraints as input. The state machine is utilized as a base for generating the component-relevant operational data. The state machine is also used as a source for identifying the nodes and edges of a component probabilistic dependency graph (CPDG). Based on the CPDG, a stack-based algorithm is used to compute the reliability. The proposed technique is evaluated by a comparison with existing techniques and the application of sensitivity analysis to a robotic wheelchair system as a case study. The results indicate that the proposed technique is more relevant at the early design stage compared to existing works, and can provide a more realistic and meaningful prediction.

No MeSH data available.