Abstract:Correction activities (CAs), which can take the form of redesign, rework, or repair, are essential to system development. Whereas verification activities (VAs) provide information about the state of the system, CAs modify the state of the system to facilitate its correct operation. However, existing approaches to modeling and optimizing verification strategies take a simplistic approach to CAs. Specifically, CAs are modeled as an expected cost to achieve a desired confidence level after a VA has failed and are… Show more
“…Kulkarni et al [24] assumed that CAs always happen if the system is not in its ideal state. In response to this gap, the BN model of verification proposed in [18] was extended to model CAs [8]. This paper leverages such an extended model to integrate VAs and CAs as dedicated decisions in a verification planning problem.…”
Section: A Mathematical Approaches For Verification Planningmentioning
confidence: 99%
“…CAs are defined as those activities that correct errors or defects that are found during system development [8]. In our previous study [8], uncertain evidence was leveraged to model the effects of CAs on the confidence of engineered systems. Three basic types of CAs were modeled with their uncertain evidence: rework, repair, and redesign.…”
Section: Proposed Joint Verification-correction Model (Jvcm) a Belief...mentioning
confidence: 99%
“…While the paradigm of verification planning is extended with CAs, this extended paradigm shares the same purpose as previous paradigms: maximizing confidence on verification coverage, minimizing risk of undetected problems, and minimizing invested effort [8]. These three aspects can be assessed in terms of their inherent value with respect to satisfying the objective of the project.…”
Section: Performance Measurement Of Jvcssmentioning
confidence: 99%
“…This section leverages a notional satellite communication instrument in a satellite as a demonstrative case to validate our framework. The notional instrument has been used to support prior research in verification [8]. Consider that the instrument is formed by a Signal Generator, an Amplifier, and an Antenna, as depicted in Fig.…”
Section: Case Study a Problem Descriptionmentioning
confidence: 99%
“…This simplification may undermine the value of the resulting verification strategies because of the potential suboptimality of CAs. In our previous work [8], a hybrid verification and correction framework was proposed to integrate CAs into verification strategies as dedicated decisions. The framework enables verification planning to be extended to include both VAs and CAs as a result of independent decisions.…”
System verification activities (VA) are used to identify potential errors and corrective activities (CA) are used to eliminate those errors. However, existing math-based methods to plan verification strategies do not consider decisions to implement VAs and perform CA jointly, ignoring their close interrelationship. In this paper, we present a joint verification-correction model to find optimal joint verification-correction strategies (JVCS). The model is constructed so that both VAs and CAs can be chosen as dedicated decisions with their own activity spaces. We adopt the belief model of Bayesian networks to represent the impact of VAs and CAs on verification planning and use three value factors to measure the performance of JVCSs. Moreover, we propose an order-based backward induction approach to solve for the optimal JVCS by updating all verification state values. A case study was conducted to show that our model can be applied to effectively solve the verification planning problem.
“…Kulkarni et al [24] assumed that CAs always happen if the system is not in its ideal state. In response to this gap, the BN model of verification proposed in [18] was extended to model CAs [8]. This paper leverages such an extended model to integrate VAs and CAs as dedicated decisions in a verification planning problem.…”
Section: A Mathematical Approaches For Verification Planningmentioning
confidence: 99%
“…CAs are defined as those activities that correct errors or defects that are found during system development [8]. In our previous study [8], uncertain evidence was leveraged to model the effects of CAs on the confidence of engineered systems. Three basic types of CAs were modeled with their uncertain evidence: rework, repair, and redesign.…”
Section: Proposed Joint Verification-correction Model (Jvcm) a Belief...mentioning
confidence: 99%
“…While the paradigm of verification planning is extended with CAs, this extended paradigm shares the same purpose as previous paradigms: maximizing confidence on verification coverage, minimizing risk of undetected problems, and minimizing invested effort [8]. These three aspects can be assessed in terms of their inherent value with respect to satisfying the objective of the project.…”
Section: Performance Measurement Of Jvcssmentioning
confidence: 99%
“…This section leverages a notional satellite communication instrument in a satellite as a demonstrative case to validate our framework. The notional instrument has been used to support prior research in verification [8]. Consider that the instrument is formed by a Signal Generator, an Amplifier, and an Antenna, as depicted in Fig.…”
Section: Case Study a Problem Descriptionmentioning
confidence: 99%
“…This simplification may undermine the value of the resulting verification strategies because of the potential suboptimality of CAs. In our previous work [8], a hybrid verification and correction framework was proposed to integrate CAs into verification strategies as dedicated decisions. The framework enables verification planning to be extended to include both VAs and CAs as a result of independent decisions.…”
System verification activities (VA) are used to identify potential errors and corrective activities (CA) are used to eliminate those errors. However, existing math-based methods to plan verification strategies do not consider decisions to implement VAs and perform CA jointly, ignoring their close interrelationship. In this paper, we present a joint verification-correction model to find optimal joint verification-correction strategies (JVCS). The model is constructed so that both VAs and CAs can be chosen as dedicated decisions with their own activity spaces. We adopt the belief model of Bayesian networks to represent the impact of VAs and CAs on verification planning and use three value factors to measure the performance of JVCSs. Moreover, we propose an order-based backward induction approach to solve for the optimal JVCS by updating all verification state values. A case study was conducted to show that our model can be applied to effectively solve the verification planning problem.
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