Reliability analysis of safety‐critical and control systems: a state‐of‐the‐art review

Kumar, Vinay; Singh, Lalit Kumar; Tripathi, Anil Kumar

doi:10.1049/iet-sen.2017.0053

Cited by 19 publications

(15 citation statements)

References 57 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…For assessing and predicting the reliability, many software reliability models (SRMs) [4][5][6] have been proposed in the last few decades. 1-3 Safety-critical system (SCS) performance relies severely on the software program being used.…”

Section: Introductionmentioning

confidence: 99%

“…The software program is developed with superior quality and high reliability using international standards and hence confronts rare failures. For assessing and predicting the reliability, many software reliability models (SRMs) [4][5][6] have been proposed in the last few decades. Various SRMs are reviewed for their potential use in quantifying software reliability and probabilities to support the reliability modeling of digital systems in SCS.…”

Section: Introductionmentioning

confidence: 99%

“…6,7 In general, the existing SRM assumes unrealistic assumptions and use failure history to estimate the parameters of the models in order to calculate the reliability. Since the 1970s, researchers are continuing to propose software reliability models for reliability estimation of software.…”

mentioning

confidence: 99%

“…6,7 In general, the existing SRM assumes unrealistic assumptions and use failure history to estimate the parameters of the models in order to calculate the reliability. 6,7 In general, the existing SRM assumes unrealistic assumptions and use failure history to estimate the parameters of the models in order to calculate the reliability.…”

mentioning

confidence: 99%

“…The models should have proper verification and validation ways.Several models do not have description of intended uses of the method and all assumptions. 6,7 In general, the existing SRM assumes unrealistic assumptions and use failure history to estimate the parameters of the models in order to calculate the reliability. As of our knowledge, we have found very few SRM which consider the specific operating conditions of the software.…”

mentioning

confidence: 99%

See 4 more Smart Citations

Software reliability analysis for safety‐critical and control systems

Kumar

Singh

Kumar

2019

Quality & Reliability Eng

View full text Add to dashboard Cite

The transition from analog to digital safety-critical instrumentation and control (I&C) systems has introduced new challenges for software experts to deliver increased software reliability. Since the 1970s, researchers are continuing to propose software reliability models for reliability estimation of software. However, these approaches rely on the failure history for the assessment of reliability. Due to insufficient failure data, these models fail to predict the reliability of safety critical systems. This paper utilizes the Bayesian update methodology and proposes a framework for the reliability assessment of the safety-critical systems (SCSs). The proposed methodology is validated using experiments performed on real data of 12 safety-critical control systems of nuclear power plants.We believe that SRM for SCS must have some special desirable characteristics:1. There should be acceptable documentation of the method and its applications that can be understood and evaluated. 2. There should be a strong justification of the assumptions made. 3. It should be possible to consider the specific operating conditions of the software. 4. It should be able to address all the uncertainties for better accuracy. 5. There should be sufficiency of model parameters. 6. The models should have proper verification and validation ways.Several models do not have description of intended uses of the method and all assumptions. 6,7 In general, the existing SRM assumes unrealistic assumptions and use failure history to estimate the parameters of the models in order to calculate the reliability. As of our knowledge, we have found very few SRM which consider the specific operating conditions of the software. 8 Software reliability growth model (SRGM) estimates the software reliability with high accuracy, if there is sufficiency of failure data and therefore are not suitable to SCS.Software errors are generally due to unstated, ambiguous, and unrealistic requirements or because of design errors. From this, we believe that if it is possible to formulate any model that can accommodate errors in each phase of software development life cycle (SDLC) and also can propagate them in next phase, prior to the completion of software development, it will give more accurate reliability prediction results. A perfect designed software requirement and specification (SRS) not only depends on the requirements and analysis but also on the expert's opinion, the domain knowledge, and the experience of the SRS designing team, the resources available, and many other constraints. Taking these as the inputs for the requirements phase, a perfect SRS is designed. These inputs may be considered as "safety cases" or "safety arguments" as these are the collection of evidence responsible for the proper development of final product. Evidence for safety cases or safety arguments for each phase exists. Using these evidences, we can create BBN model for each phase of life cycle model and calculate the inferred probability using the safety argument values. A proper conditio...

show abstract

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

See 3 more Smart Citations

Software reliability analysis for safety‐critical and control systems

Kumar

Singh

Kumar

2019

Quality & Reliability Eng

View full text Add to dashboard Cite

show abstract

Reliability of safety‐critical systems: A state‐of‐the‐art review

Maurya

Kumar

2020

Quality & Reliability Eng

View full text Add to dashboard Cite

Safety-critical systems are designed to prevent catastrophic consequences from failure, such as injury or death to humans and environmental damage. These must be carefully designed to ensure reliability requirements. The purpose of this paper is to identify the number of models in the reliability analysis of safety-critical systems. To achieve this goal, we conducted a systematic review of 40 shortlisted studies. The selected studies are classified based on various techniques used in safety-critical systems. This paper summarizes the literature review in the field of reliability of safety-critical systems. The limitations of the literature are exquisitely represented. The international safety norms and applications of safety-critical systems are discussed systematically in this paper. This paper emerges research trends, research challenges and insights of the researcher for future research direction in the area of safety-critical systems.

show abstract