The Experts below are selected from a list of 6489 Experts worldwide ranked by ideXlab platform
Kishor S. Trivedi - One of the best experts on this subject based on the ideXlab platform.
-
understanding the impacts of influencing factors on time to a datarace Software Failure
International Symposium on Software Reliability Engineering, 2017Co-Authors: Zheng Zheng, Kishor S. TrivediAbstract:Datarace is a common problem on shared-memory parallel computers, including multicores. Due to its dependence on the thread scheduling scheme of its execution environment, the time to a datarace Failure is usually very long. How to accelerate the occurrence of a datarace Failure and further estimate the mean time to Failure (MTTF) is an important topic to be studied. In this paper, the influencing factors for Failures triggered by datarace bugs are explored and their influences on the time to datarace Failure including the relationship with the MTTF are empirically studied. Experiments are conducted on real datarace suffering programs to verify the factors and their influences. Empirical results show that the influencing factors do have influences on the time to datarace Failure of the subjects. They can be used to accelerate the occurrence of datarace Failures and accurately estimate the MTTF.
-
Future research directions in design of reliable communication systems
Telecommunication Systems, 2015Co-Authors: Janusz Rak, Javier Alonso Lopez, Arie M.c.a. Koster, Egemen K. Cetinkaya, James P.g. Sterbenz, Mario Pickavet, Teresa Gomes, Matthias Gunkel, Kishor S. Trivedi, Krzysztof WalkowiakAbstract:In this position paper on reliable networks, we discuss new trends in the design of reliable communication systems. We focus on a wide range of research directions including protection against Software Failures as well as Failures of communication systems equipment. In particular, we outline future research trends in Software Failure mitigation, reliability of wireless communications, robust optimization and network design, multilevel and multirealm network resilience, multiple criteria routing approaches in multilayer networks, resilience options of the fixed IP backbone network in the interplay with the optical layer survivability, reliability of cloud computing networks, and resiliency of Software-defined networks. Described research directions are frequently enhanced with examples.
-
the nature of the times to flight Software Failure during space missions
International Symposium on Software Reliability Engineering, 2012Co-Authors: Javier Alonso, Michael Grottke, Allen P Nikora, Kishor S. TrivediAbstract:The growing complexity of mission-critical space mission Software makes it prone to suffer Failures during operations. The success of space missions depends on the ability of the systems to deal with Software Failures, or to avoid them in the first place. In order to develop more effective mitigation techniques, it is necessary to understand the nature of the Failures and the underlying Software faults. Based on their characteristics, Software faults can be classified into Bohrbugs, non-aging-related Mandelbugs, and aging-related bugs. Each type of fault requires different kinds of mitigation techniques. While Bohrbugs are usually easy to fix during development or testing, this is not the case for non-aging-related Mandelbugs and aging-related bugs due to their inherent complexity. Systems need mechanisms like Software restart, Software replication or Software rejuvenation to deal with Failures caused by these faults during the operational phase. In a previous study, we classified space mission flight Software faults into the three above-mentioned categories based on problems reported during operations. That study concentrated on the percentages of the faults of each type and the variation of these percentages within and across different missions. This paper extends that work by exploring the nature of the times to Software Failure due to Bohrbugs and non-aging-related Mandelbugs for eight JPL/NASA missions. We start by applying trend tests to the times to Failure to check if there is any reliability growth (or decay) for each type of Failure. For those times to Failure sequences with no trend, we fit distributions to the data sets and carry out goodness-of-fit tests. The results will be used to guide the development of improved operational Failure mitigation techniques, thereby increasing the reliability of space mission Software.
-
ISSRE - The Nature of the Times to Flight Software Failure during Space Missions
2012 IEEE 23rd International Symposium on Software Reliability Engineering, 2012Co-Authors: Javier Alonso, Michael Grottke, Allen P Nikora, Kishor S. TrivediAbstract:The growing complexity of mission-critical space mission Software makes it prone to suffer Failures during operations. The success of space missions depends on the ability of the systems to deal with Software Failures, or to avoid them in the first place. In order to develop more effective mitigation techniques, it is necessary to understand the nature of the Failures and the underlying Software faults. Based on their characteristics, Software faults can be classified into Bohrbugs, non-aging-related Mandelbugs, and aging-related bugs. Each type of fault requires different kinds of mitigation techniques. While Bohrbugs are usually easy to fix during development or testing, this is not the case for non-aging-related Mandelbugs and aging-related bugs due to their inherent complexity. Systems need mechanisms like Software restart, Software replication or Software rejuvenation to deal with Failures caused by these faults during the operational phase. In a previous study, we classified space mission flight Software faults into the three above-mentioned categories based on problems reported during operations. That study concentrated on the percentages of the faults of each type and the variation of these percentages within and across different missions. This paper extends that work by exploring the nature of the times to Software Failure due to Bohrbugs and non-aging-related Mandelbugs for eight JPL/NASA missions. We start by applying trend tests to the times to Failure to check if there is any reliability growth (or decay) for each type of Failure. For those times to Failure sequences with no trend, we fit distributions to the data sets and carry out goodness-of-fit tests. The results will be used to guide the development of improved operational Failure mitigation techniques, thereby increasing the reliability of space mission Software.
Jeevith Hegde - One of the best experts on this subject based on the ideXlab platform.
-
incorporating Software Failure in risk analysis part 2 risk modeling process and case study
Reliability Engineering & System Safety, 2020Co-Authors: Christoph Alexander Thieme, Ali Mosleh, Ingrid Bouwer Utne, Jeevith HegdeAbstract:Abstract The advent of autonomous cars, drones, and ships, the complexity of these systems is increasing, challenging risk analysis and risk mitigation, since the incorporation of Software Failures intro traditional risk analysis currently is difficult. Current methods that attempt Software risk analysis, consider the interaction with hardware and Software only superficially. These methods are often inconsistent regarding the level of analysis and cover often only selected Software Failures. This paper is a follow-up article of Thieme et al. [1] and presents a process for the analysis of functional Software Failures, their propagation, and incorporation of the results in traditional risk analysis methods, such as fault trees, and event trees. A functional view on Software is taken, that allows for integration of Software Failure modes into risk analysis of the events and effects, and a common foundation for communication between risk analysts and domain experts. The proposed process can be applied during system development and operation in order to analyses the risk level and identify measures for system improvement. A case study focusing on a decision support system for an autonomous remotely operated vehicle working on a subsea oil and gas production system demonstrates the applicability of the proposed process.
-
incorporating Software Failure in risk analysis part 1 Software functional Failure mode classification
Reliability Engineering & System Safety, 2020Co-Authors: Christoph Alexander Thieme, Ali Mosleh, Ingrid Bouwer Utne, Jeevith HegdeAbstract:Abstract Advanced technological systems consist of a combination of hardware and Software, and they are often operated or supervised by a human operator. Failures in Software-intensive systems may be difficult to identify, analyze, and mitigate, owing to system complexity, system interactions, and cascading effects. Risk analysis of such systems is necessary to ensure safe operation. The traditional approach to risk analysis focuses on hardware Failures and, to some extent, on human and organizational factors. Software Failures are often overlooked, or it is assumed that the system's Software does not fail. Research and industry efforts are directed toward Software reliability and safety. However, the effect of Software Failures on the level of risk of advanced technological systems has so far received little attention. Most analytical methods focus on selected Software Failures and tend to be inconsistent with respect to the level of analysis. There is a need for risk analysis methods that are able to sufficiently take hardware, Software, and human and organizational risk factors into account. Hence, this article presents a foundation that enables Software Failure to be included in the general framework of risk analysis. This article is the first of two articles addressing the challenges of analyzing Software Failures and including their potential risk contribution to a system or operation. Hence, the focus is on risks resulting from Software Failures, and not on Software reliability, because risk and reliability are two different aspects of a system. Using a functional perspective on Software, this article distinguishes between Failure mode, Failure cause, and Failure effects. Accordingly, 29 Failure modes are identified to form a taxonomy and are demonstrated in a case study. The taxonomy assists in identifying Software Failure modes, which provide input to the risk analysis of Software-intensive systems, presented in a subsequent article (Part 2 of 1) (Thieme et al.).
-
Incorporating Software Failure in risk analysis––Part 2: Risk modeling process and case study
Reliability Engineering & System Safety, 2020Co-Authors: Christoph Alexander Thieme, Ali Mosleh, Ingrid Bouwer Utne, Jeevith HegdeAbstract:Abstract The advent of autonomous cars, drones, and ships, the complexity of these systems is increasing, challenging risk analysis and risk mitigation, since the incorporation of Software Failures intro traditional risk analysis currently is difficult. Current methods that attempt Software risk analysis, consider the interaction with hardware and Software only superficially. These methods are often inconsistent regarding the level of analysis and cover often only selected Software Failures. This paper is a follow-up article of Thieme et al. [1] and presents a process for the analysis of functional Software Failures, their propagation, and incorporation of the results in traditional risk analysis methods, such as fault trees, and event trees. A functional view on Software is taken, that allows for integration of Software Failure modes into risk analysis of the events and effects, and a common foundation for communication between risk analysts and domain experts. The proposed process can be applied during system development and operation in order to analyses the risk level and identify measures for system improvement. A case study focusing on a decision support system for an autonomous remotely operated vehicle working on a subsea oil and gas production system demonstrates the applicability of the proposed process.
-
Incorporating Software Failure in risk analysis – Part 1: Software functional Failure mode classification
Reliability Engineering & System Safety, 2020Co-Authors: Christoph Alexander Thieme, Ali Mosleh, Ingrid Bouwer Utne, Jeevith HegdeAbstract:Abstract Advanced technological systems consist of a combination of hardware and Software, and they are often operated or supervised by a human operator. Failures in Software-intensive systems may be difficult to identify, analyze, and mitigate, owing to system complexity, system interactions, and cascading effects. Risk analysis of such systems is necessary to ensure safe operation. The traditional approach to risk analysis focuses on hardware Failures and, to some extent, on human and organizational factors. Software Failures are often overlooked, or it is assumed that the system's Software does not fail. Research and industry efforts are directed toward Software reliability and safety. However, the effect of Software Failures on the level of risk of advanced technological systems has so far received little attention. Most analytical methods focus on selected Software Failures and tend to be inconsistent with respect to the level of analysis. There is a need for risk analysis methods that are able to sufficiently take hardware, Software, and human and organizational risk factors into account. Hence, this article presents a foundation that enables Software Failure to be included in the general framework of risk analysis. This article is the first of two articles addressing the challenges of analyzing Software Failures and including their potential risk contribution to a system or operation. Hence, the focus is on risks resulting from Software Failures, and not on Software reliability, because risk and reliability are two different aspects of a system. Using a functional perspective on Software, this article distinguishes between Failure mode, Failure cause, and Failure effects. Accordingly, 29 Failure modes are identified to form a taxonomy and are demonstrated in a case study. The taxonomy assists in identifying Software Failure modes, which provide input to the risk analysis of Software-intensive systems, presented in a subsequent article (Part 2 of 2) [1] .
Ali Mosleh - One of the best experts on this subject based on the ideXlab platform.
-
incorporating Software Failure in risk analysis part 2 risk modeling process and case study
Reliability Engineering & System Safety, 2020Co-Authors: Christoph Alexander Thieme, Ali Mosleh, Ingrid Bouwer Utne, Jeevith HegdeAbstract:Abstract The advent of autonomous cars, drones, and ships, the complexity of these systems is increasing, challenging risk analysis and risk mitigation, since the incorporation of Software Failures intro traditional risk analysis currently is difficult. Current methods that attempt Software risk analysis, consider the interaction with hardware and Software only superficially. These methods are often inconsistent regarding the level of analysis and cover often only selected Software Failures. This paper is a follow-up article of Thieme et al. [1] and presents a process for the analysis of functional Software Failures, their propagation, and incorporation of the results in traditional risk analysis methods, such as fault trees, and event trees. A functional view on Software is taken, that allows for integration of Software Failure modes into risk analysis of the events and effects, and a common foundation for communication between risk analysts and domain experts. The proposed process can be applied during system development and operation in order to analyses the risk level and identify measures for system improvement. A case study focusing on a decision support system for an autonomous remotely operated vehicle working on a subsea oil and gas production system demonstrates the applicability of the proposed process.
-
incorporating Software Failure in risk analysis part 1 Software functional Failure mode classification
Reliability Engineering & System Safety, 2020Co-Authors: Christoph Alexander Thieme, Ali Mosleh, Ingrid Bouwer Utne, Jeevith HegdeAbstract:Abstract Advanced technological systems consist of a combination of hardware and Software, and they are often operated or supervised by a human operator. Failures in Software-intensive systems may be difficult to identify, analyze, and mitigate, owing to system complexity, system interactions, and cascading effects. Risk analysis of such systems is necessary to ensure safe operation. The traditional approach to risk analysis focuses on hardware Failures and, to some extent, on human and organizational factors. Software Failures are often overlooked, or it is assumed that the system's Software does not fail. Research and industry efforts are directed toward Software reliability and safety. However, the effect of Software Failures on the level of risk of advanced technological systems has so far received little attention. Most analytical methods focus on selected Software Failures and tend to be inconsistent with respect to the level of analysis. There is a need for risk analysis methods that are able to sufficiently take hardware, Software, and human and organizational risk factors into account. Hence, this article presents a foundation that enables Software Failure to be included in the general framework of risk analysis. This article is the first of two articles addressing the challenges of analyzing Software Failures and including their potential risk contribution to a system or operation. Hence, the focus is on risks resulting from Software Failures, and not on Software reliability, because risk and reliability are two different aspects of a system. Using a functional perspective on Software, this article distinguishes between Failure mode, Failure cause, and Failure effects. Accordingly, 29 Failure modes are identified to form a taxonomy and are demonstrated in a case study. The taxonomy assists in identifying Software Failure modes, which provide input to the risk analysis of Software-intensive systems, presented in a subsequent article (Part 2 of 1) (Thieme et al.).
-
Incorporating Software Failure in risk analysis––Part 2: Risk modeling process and case study
Reliability Engineering & System Safety, 2020Co-Authors: Christoph Alexander Thieme, Ali Mosleh, Ingrid Bouwer Utne, Jeevith HegdeAbstract:Abstract The advent of autonomous cars, drones, and ships, the complexity of these systems is increasing, challenging risk analysis and risk mitigation, since the incorporation of Software Failures intro traditional risk analysis currently is difficult. Current methods that attempt Software risk analysis, consider the interaction with hardware and Software only superficially. These methods are often inconsistent regarding the level of analysis and cover often only selected Software Failures. This paper is a follow-up article of Thieme et al. [1] and presents a process for the analysis of functional Software Failures, their propagation, and incorporation of the results in traditional risk analysis methods, such as fault trees, and event trees. A functional view on Software is taken, that allows for integration of Software Failure modes into risk analysis of the events and effects, and a common foundation for communication between risk analysts and domain experts. The proposed process can be applied during system development and operation in order to analyses the risk level and identify measures for system improvement. A case study focusing on a decision support system for an autonomous remotely operated vehicle working on a subsea oil and gas production system demonstrates the applicability of the proposed process.
-
Incorporating Software Failure in risk analysis – Part 1: Software functional Failure mode classification
Reliability Engineering & System Safety, 2020Co-Authors: Christoph Alexander Thieme, Ali Mosleh, Ingrid Bouwer Utne, Jeevith HegdeAbstract:Abstract Advanced technological systems consist of a combination of hardware and Software, and they are often operated or supervised by a human operator. Failures in Software-intensive systems may be difficult to identify, analyze, and mitigate, owing to system complexity, system interactions, and cascading effects. Risk analysis of such systems is necessary to ensure safe operation. The traditional approach to risk analysis focuses on hardware Failures and, to some extent, on human and organizational factors. Software Failures are often overlooked, or it is assumed that the system's Software does not fail. Research and industry efforts are directed toward Software reliability and safety. However, the effect of Software Failures on the level of risk of advanced technological systems has so far received little attention. Most analytical methods focus on selected Software Failures and tend to be inconsistent with respect to the level of analysis. There is a need for risk analysis methods that are able to sufficiently take hardware, Software, and human and organizational risk factors into account. Hence, this article presents a foundation that enables Software Failure to be included in the general framework of risk analysis. This article is the first of two articles addressing the challenges of analyzing Software Failures and including their potential risk contribution to a system or operation. Hence, the focus is on risks resulting from Software Failures, and not on Software reliability, because risk and reliability are two different aspects of a system. Using a functional perspective on Software, this article distinguishes between Failure mode, Failure cause, and Failure effects. Accordingly, 29 Failure modes are identified to form a taxonomy and are demonstrated in a case study. The taxonomy assists in identifying Software Failure modes, which provide input to the risk analysis of Software-intensive systems, presented in a subsequent article (Part 2 of 2) [1] .
Christoph Alexander Thieme - One of the best experts on this subject based on the ideXlab platform.
-
incorporating Software Failure in risk analysis part 2 risk modeling process and case study
Reliability Engineering & System Safety, 2020Co-Authors: Christoph Alexander Thieme, Ali Mosleh, Ingrid Bouwer Utne, Jeevith HegdeAbstract:Abstract The advent of autonomous cars, drones, and ships, the complexity of these systems is increasing, challenging risk analysis and risk mitigation, since the incorporation of Software Failures intro traditional risk analysis currently is difficult. Current methods that attempt Software risk analysis, consider the interaction with hardware and Software only superficially. These methods are often inconsistent regarding the level of analysis and cover often only selected Software Failures. This paper is a follow-up article of Thieme et al. [1] and presents a process for the analysis of functional Software Failures, their propagation, and incorporation of the results in traditional risk analysis methods, such as fault trees, and event trees. A functional view on Software is taken, that allows for integration of Software Failure modes into risk analysis of the events and effects, and a common foundation for communication between risk analysts and domain experts. The proposed process can be applied during system development and operation in order to analyses the risk level and identify measures for system improvement. A case study focusing on a decision support system for an autonomous remotely operated vehicle working on a subsea oil and gas production system demonstrates the applicability of the proposed process.
-
incorporating Software Failure in risk analysis part 1 Software functional Failure mode classification
Reliability Engineering & System Safety, 2020Co-Authors: Christoph Alexander Thieme, Ali Mosleh, Ingrid Bouwer Utne, Jeevith HegdeAbstract:Abstract Advanced technological systems consist of a combination of hardware and Software, and they are often operated or supervised by a human operator. Failures in Software-intensive systems may be difficult to identify, analyze, and mitigate, owing to system complexity, system interactions, and cascading effects. Risk analysis of such systems is necessary to ensure safe operation. The traditional approach to risk analysis focuses on hardware Failures and, to some extent, on human and organizational factors. Software Failures are often overlooked, or it is assumed that the system's Software does not fail. Research and industry efforts are directed toward Software reliability and safety. However, the effect of Software Failures on the level of risk of advanced technological systems has so far received little attention. Most analytical methods focus on selected Software Failures and tend to be inconsistent with respect to the level of analysis. There is a need for risk analysis methods that are able to sufficiently take hardware, Software, and human and organizational risk factors into account. Hence, this article presents a foundation that enables Software Failure to be included in the general framework of risk analysis. This article is the first of two articles addressing the challenges of analyzing Software Failures and including their potential risk contribution to a system or operation. Hence, the focus is on risks resulting from Software Failures, and not on Software reliability, because risk and reliability are two different aspects of a system. Using a functional perspective on Software, this article distinguishes between Failure mode, Failure cause, and Failure effects. Accordingly, 29 Failure modes are identified to form a taxonomy and are demonstrated in a case study. The taxonomy assists in identifying Software Failure modes, which provide input to the risk analysis of Software-intensive systems, presented in a subsequent article (Part 2 of 1) (Thieme et al.).
-
Incorporating Software Failure in risk analysis––Part 2: Risk modeling process and case study
Reliability Engineering & System Safety, 2020Co-Authors: Christoph Alexander Thieme, Ali Mosleh, Ingrid Bouwer Utne, Jeevith HegdeAbstract:Abstract The advent of autonomous cars, drones, and ships, the complexity of these systems is increasing, challenging risk analysis and risk mitigation, since the incorporation of Software Failures intro traditional risk analysis currently is difficult. Current methods that attempt Software risk analysis, consider the interaction with hardware and Software only superficially. These methods are often inconsistent regarding the level of analysis and cover often only selected Software Failures. This paper is a follow-up article of Thieme et al. [1] and presents a process for the analysis of functional Software Failures, their propagation, and incorporation of the results in traditional risk analysis methods, such as fault trees, and event trees. A functional view on Software is taken, that allows for integration of Software Failure modes into risk analysis of the events and effects, and a common foundation for communication between risk analysts and domain experts. The proposed process can be applied during system development and operation in order to analyses the risk level and identify measures for system improvement. A case study focusing on a decision support system for an autonomous remotely operated vehicle working on a subsea oil and gas production system demonstrates the applicability of the proposed process.
-
Incorporating Software Failure in risk analysis – Part 1: Software functional Failure mode classification
Reliability Engineering & System Safety, 2020Co-Authors: Christoph Alexander Thieme, Ali Mosleh, Ingrid Bouwer Utne, Jeevith HegdeAbstract:Abstract Advanced technological systems consist of a combination of hardware and Software, and they are often operated or supervised by a human operator. Failures in Software-intensive systems may be difficult to identify, analyze, and mitigate, owing to system complexity, system interactions, and cascading effects. Risk analysis of such systems is necessary to ensure safe operation. The traditional approach to risk analysis focuses on hardware Failures and, to some extent, on human and organizational factors. Software Failures are often overlooked, or it is assumed that the system's Software does not fail. Research and industry efforts are directed toward Software reliability and safety. However, the effect of Software Failures on the level of risk of advanced technological systems has so far received little attention. Most analytical methods focus on selected Software Failures and tend to be inconsistent with respect to the level of analysis. There is a need for risk analysis methods that are able to sufficiently take hardware, Software, and human and organizational risk factors into account. Hence, this article presents a foundation that enables Software Failure to be included in the general framework of risk analysis. This article is the first of two articles addressing the challenges of analyzing Software Failures and including their potential risk contribution to a system or operation. Hence, the focus is on risks resulting from Software Failures, and not on Software reliability, because risk and reliability are two different aspects of a system. Using a functional perspective on Software, this article distinguishes between Failure mode, Failure cause, and Failure effects. Accordingly, 29 Failure modes are identified to form a taxonomy and are demonstrated in a case study. The taxonomy assists in identifying Software Failure modes, which provide input to the risk analysis of Software-intensive systems, presented in a subsequent article (Part 2 of 2) [1] .
Ingrid Bouwer Utne - One of the best experts on this subject based on the ideXlab platform.
-
incorporating Software Failure in risk analysis part 2 risk modeling process and case study
Reliability Engineering & System Safety, 2020Co-Authors: Christoph Alexander Thieme, Ali Mosleh, Ingrid Bouwer Utne, Jeevith HegdeAbstract:Abstract The advent of autonomous cars, drones, and ships, the complexity of these systems is increasing, challenging risk analysis and risk mitigation, since the incorporation of Software Failures intro traditional risk analysis currently is difficult. Current methods that attempt Software risk analysis, consider the interaction with hardware and Software only superficially. These methods are often inconsistent regarding the level of analysis and cover often only selected Software Failures. This paper is a follow-up article of Thieme et al. [1] and presents a process for the analysis of functional Software Failures, their propagation, and incorporation of the results in traditional risk analysis methods, such as fault trees, and event trees. A functional view on Software is taken, that allows for integration of Software Failure modes into risk analysis of the events and effects, and a common foundation for communication between risk analysts and domain experts. The proposed process can be applied during system development and operation in order to analyses the risk level and identify measures for system improvement. A case study focusing on a decision support system for an autonomous remotely operated vehicle working on a subsea oil and gas production system demonstrates the applicability of the proposed process.
-
incorporating Software Failure in risk analysis part 1 Software functional Failure mode classification
Reliability Engineering & System Safety, 2020Co-Authors: Christoph Alexander Thieme, Ali Mosleh, Ingrid Bouwer Utne, Jeevith HegdeAbstract:Abstract Advanced technological systems consist of a combination of hardware and Software, and they are often operated or supervised by a human operator. Failures in Software-intensive systems may be difficult to identify, analyze, and mitigate, owing to system complexity, system interactions, and cascading effects. Risk analysis of such systems is necessary to ensure safe operation. The traditional approach to risk analysis focuses on hardware Failures and, to some extent, on human and organizational factors. Software Failures are often overlooked, or it is assumed that the system's Software does not fail. Research and industry efforts are directed toward Software reliability and safety. However, the effect of Software Failures on the level of risk of advanced technological systems has so far received little attention. Most analytical methods focus on selected Software Failures and tend to be inconsistent with respect to the level of analysis. There is a need for risk analysis methods that are able to sufficiently take hardware, Software, and human and organizational risk factors into account. Hence, this article presents a foundation that enables Software Failure to be included in the general framework of risk analysis. This article is the first of two articles addressing the challenges of analyzing Software Failures and including their potential risk contribution to a system or operation. Hence, the focus is on risks resulting from Software Failures, and not on Software reliability, because risk and reliability are two different aspects of a system. Using a functional perspective on Software, this article distinguishes between Failure mode, Failure cause, and Failure effects. Accordingly, 29 Failure modes are identified to form a taxonomy and are demonstrated in a case study. The taxonomy assists in identifying Software Failure modes, which provide input to the risk analysis of Software-intensive systems, presented in a subsequent article (Part 2 of 1) (Thieme et al.).
-
Incorporating Software Failure in risk analysis––Part 2: Risk modeling process and case study
Reliability Engineering & System Safety, 2020Co-Authors: Christoph Alexander Thieme, Ali Mosleh, Ingrid Bouwer Utne, Jeevith HegdeAbstract:Abstract The advent of autonomous cars, drones, and ships, the complexity of these systems is increasing, challenging risk analysis and risk mitigation, since the incorporation of Software Failures intro traditional risk analysis currently is difficult. Current methods that attempt Software risk analysis, consider the interaction with hardware and Software only superficially. These methods are often inconsistent regarding the level of analysis and cover often only selected Software Failures. This paper is a follow-up article of Thieme et al. [1] and presents a process for the analysis of functional Software Failures, their propagation, and incorporation of the results in traditional risk analysis methods, such as fault trees, and event trees. A functional view on Software is taken, that allows for integration of Software Failure modes into risk analysis of the events and effects, and a common foundation for communication between risk analysts and domain experts. The proposed process can be applied during system development and operation in order to analyses the risk level and identify measures for system improvement. A case study focusing on a decision support system for an autonomous remotely operated vehicle working on a subsea oil and gas production system demonstrates the applicability of the proposed process.
-
Incorporating Software Failure in risk analysis – Part 1: Software functional Failure mode classification
Reliability Engineering & System Safety, 2020Co-Authors: Christoph Alexander Thieme, Ali Mosleh, Ingrid Bouwer Utne, Jeevith HegdeAbstract:Abstract Advanced technological systems consist of a combination of hardware and Software, and they are often operated or supervised by a human operator. Failures in Software-intensive systems may be difficult to identify, analyze, and mitigate, owing to system complexity, system interactions, and cascading effects. Risk analysis of such systems is necessary to ensure safe operation. The traditional approach to risk analysis focuses on hardware Failures and, to some extent, on human and organizational factors. Software Failures are often overlooked, or it is assumed that the system's Software does not fail. Research and industry efforts are directed toward Software reliability and safety. However, the effect of Software Failures on the level of risk of advanced technological systems has so far received little attention. Most analytical methods focus on selected Software Failures and tend to be inconsistent with respect to the level of analysis. There is a need for risk analysis methods that are able to sufficiently take hardware, Software, and human and organizational risk factors into account. Hence, this article presents a foundation that enables Software Failure to be included in the general framework of risk analysis. This article is the first of two articles addressing the challenges of analyzing Software Failures and including their potential risk contribution to a system or operation. Hence, the focus is on risks resulting from Software Failures, and not on Software reliability, because risk and reliability are two different aspects of a system. Using a functional perspective on Software, this article distinguishes between Failure mode, Failure cause, and Failure effects. Accordingly, 29 Failure modes are identified to form a taxonomy and are demonstrated in a case study. The taxonomy assists in identifying Software Failure modes, which provide input to the risk analysis of Software-intensive systems, presented in a subsequent article (Part 2 of 2) [1] .
