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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.


Phases of software component reliability prediction.
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pone.0163346.g001: Phases of software component reliability prediction.

Mentions: For ease of exposition, the proposed technique is depicted as a three-phase process as shown in Fig 1. Broadly, the requirements specification is the main source utilized by the technique to synthesize the component behaviour model. Finite state machines (FSMs) are the basic elements that used in the behaviour synthesis. The behaviour model can be used for two purposes: as a simulation of the component behaviour and as a source for obtaining and identifying the elements of a probabilistic dependency graph. The simulation provides an execution log for the component, and the log serves as the runtime observation data required as input to generate operational data for the component. The operational data are necessary to determine the values of the dependency graph’s parameters. Finally, the constructed graph (which is a component probabilistic dependency graph (CPDG)) is used as input to a tree transversal algorithm which works to compute the component reliability.


Technique for Early Reliability Prediction of Software Components Using Behaviour Models
Phases of software component reliability prediction.
© Copyright Policy
Related In: Results  -  Collection

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

pone.0163346.g001: Phases of software component reliability prediction.
Mentions: For ease of exposition, the proposed technique is depicted as a three-phase process as shown in Fig 1. Broadly, the requirements specification is the main source utilized by the technique to synthesize the component behaviour model. Finite state machines (FSMs) are the basic elements that used in the behaviour synthesis. The behaviour model can be used for two purposes: as a simulation of the component behaviour and as a source for obtaining and identifying the elements of a probabilistic dependency graph. The simulation provides an execution log for the component, and the log serves as the runtime observation data required as input to generate operational data for the component. The operational data are necessary to determine the values of the dependency graph’s parameters. Finally, the constructed graph (which is a component probabilistic dependency graph (CPDG)) is used as input to a tree transversal algorithm which works to compute the component reliability.

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.