Fault Injection Techniques - A Brief Review

Lenka, Rakesh Kumar; Padhi, Sarthak; Nayak, Kabita Manjari

doi:10.1109/icacccn.2018.8748585

Cited by 8 publications

(5 citation statements)

References 4 publications

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“…Fault injection techniques have been extensively researched in the particular field of software and computer systems, e.g., [12]. However, fault injection in physics-based models of hydraulic systems and components is still rarely addressed.…”

Section: Model-based Approachmentioning

confidence: 99%

Methodology for Model Architecting and Failure Simulation Supported by Bond-Graphs—Application to Helicopter Axial Piston Pump

2021

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This paper reports work performed to support the development of condition monitoring strategies through extensive use of simulation. The aim is to define and implement a methodology that makes the development of lumped-parameter models more efficient and straightforward. This is achieved by considering the model architecting and the approach adopted for fault injection early in the process. Various options are proposed and compared for both these activities. The Bond-Graph formalism is extensively used for its ability to focus on the model structure and interfaces, the nature of the phenomena considered, and potential causality issues. The interest of the proposed methodology is illustrated with the example of a pressure-compensated axial piston pump that supplies the flight control actuators in helicopters. The pump model architecting and the fault injection are presented, with special attention to jamming and erosion of the pump compensator valve. From these examples, it is shown that the proposed methodologies provide an efficient model-based means of identifying fault signatures and implementing low-cost condition monitoring features in an industrial context.

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Section: Model-based Approachmentioning

confidence: 99%

Methodology for Model Architecting and Failure Simulation Supported by Bond-Graphs—Application to Helicopter Axial Piston Pump

2021

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“…Then, backward snowballing was performed [21], meaning that the references of the found pieces of literature were screened in hopes of discovering additional publications. The literature search process identified six peer-reviewed papers [3,4,10,12,14,16].…”

Section: Literature Studymentioning

confidence: 99%

“…The point of this is to ensure the authenticity and relevance of the experiments. The alternative, to run Chaos Experiments in testing environments, can be inferior since a testing environment does not always capture all aspects of a complete system running in production [10]. For instance, behavior of real users and synthetic users may differ [3].…”

Section: Chaos Engineering Overviewmentioning

confidence: 99%

Getting Started with Chaos Engineering - design of an implementation framework in practice

Jernberg

Runeson

Engström

2020

Proceedings of the 14th ACM / IEEE International Symposium on Empirical Software Engineering and Measurement (ESEM)

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Background. Chaos Engineering is proposed as a practice to verify a system's resilience under real, operational conditions. It employs fault injection, is originally developed at Netflix, and supported by several tools from there and other sources. Aims. We aim to introduce Chaos Engineering at ICA Gruppen AB, a group of companies whose core business is grocery retail, to improve their systems' resilience, and to capture our knowledge gained from literature and interviews in a process framework for the introduction of Chaos Engineering. Method. The research is conducted under the design science paradigm, where the problem is conceptualized through a literature study of Chaos Engineering and exploratory interviews in the company. The solution framework is designed based on the literature and a tool survey, and validated by letting software engineers at ICA apply parts of it to the software systems of ica.se website, including its e-shop. Results. The main contributions are a synthesis of Chaos Engineering literature and tools, in depth understanding of the needs of the case company, and guidelines for introducing Chaos Engineering. Conclusions. The applied parts were concluded to be feasible and they successfully discovered a set of initial improvement opportunities for the system's resilience, as well as a suitable Chaos Engineering practice for future resilience testing of the system. We recommend companies using the framework as a guide for the implementation of Chaos Engineering.

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“…In a simulation framework, faults can be injected using a set of input patterns via an automated FI code or FI dashboard in hardware or software. Several surveys studied FI methodologies [3,[6][7][8][9]. Briefly, FI techniques can be categorized into four methodologies: (1) physical fault injections, including hardware-based fault injection (HaFI) and software-based fault injection (SoFI) methods; (2) simulation-based fault injection (SiFI) methods; (3) emulation-based fault injection (EmFI) methods; and (4) hybrid fault injection (HyFI) methods [4,6,8,10].…”

Section: Introduction and Literature Reviewmentioning

confidence: 99%

“…SiFI supports the adaptation of tests to a variety of traffic scenarios and avoids costly or dangerous physical FI in the real world [11]. SiFI has a low cost, high controllability, high safety, and high fault coverage [9]. SiFI is categorized into three different subcategories in the literature: the simulation command technique, simulation code modification technique, and simulation modification technique with different levels of abstraction [5].…”

Section: Introduction and Literature Reviewmentioning

confidence: 99%

Realistic Simulation of Sensor/Actuator Faults for a Dependability Evaluation of Demand-Controlled Ventilation and Heating Systems

2022

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In the development of fault-tolerant systems, simulation is a common technique used to obtain insights into performance and dependability because it saves time and avoids the risks of testing the behavior of real-world systems in the presence of faults. Fault injection in a simulation offers a high controllability and observability, and thus is ideal for an early dependability analysis and fault-tolerance evaluation. Heating, ventilation, and air conditioning (HVAC) systems in critical infrastructures, such as airports and hospitals, are safety-relevant systems, which not only determine energy consumption, system efficiency, and occupancy comfort but also play an essential role in emergency scenarios (e.g., fires, biological hazards). Hence, fault injection serves as a practical and essential solution to assess dependability in different fault scenarios of HVAC systems. Hence, in this paper, we present a simulation-based fault injection framework with a combination of two techniques, simulator command and simulation code modification, which are applied to fault injector blocks as saboteurs and an automated fault injector algorithm to automatically activate fault cases with certain fault attributes. The proposed fault injection framework supports a comprehensive range of faults and various fault attributes, including fault persistence, fault type, fault location, fault duration, and fault interarrival time. This framework considers noise in a demand-controlled ventilation (DCV) and heating system as a type of HVAC system since it has been demonstrated that any fault injection scenario is accompanied by some impacts on energy consumption, occupancy comfort, and a fire risk. It also supports the reproducibility for a set of specific fault scenarios or random fault injection scenarios. The system model was implemented and simulated in Matlab/Simulink, and fault injector blocks were developed by Stateflow diagrams. An experimental evaluation serves as the assessment of the presented fault injection framework with a defined example of fault scenarios. The results of the evaluation show the correctness, system behavior, accuracy, and other parameters of the system, such as the heater energy consumption and heater duty cycle of the fault injection framework in the presence of different fault cases. In conclusion, the present paper provides a novel simulation-based fault injection framework, which combines simulator command techniques and simulation code modifications for a realistic and automatic fault injection with comprehensive coverage of various fault types and a consideration of noise and uncertainty, allowing for reproducibility of the results. The outputs achieved from the fault injection framework can be applied to fault-tolerant studies in other application domains.

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Fault Injection Techniques - A Brief Review

Cited by 8 publications

References 4 publications

Methodology for Model Architecting and Failure Simulation Supported by Bond-Graphs—Application to Helicopter Axial Piston Pump

Methodology for Model Architecting and Failure Simulation Supported by Bond-Graphs—Application to Helicopter Axial Piston Pump

Getting Started with Chaos Engineering - design of an implementation framework in practice

Realistic Simulation of Sensor/Actuator Faults for a Dependability Evaluation of Demand-Controlled Ventilation and Heating Systems

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