DICE fault injection tool

Sheridan, Craig; Whigham, Darren; Artač, Matej

doi:10.1145/2945408.2945415

Cited by 5 publications

(2 citation statements)

References 4 publications

(2 reference statements)

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“…This methodology has been extended to more failure types both at Netflix [17] and other companies [25]. An example of cloud oriented tool is by Sheridan et al [30], who presented a fault injection tool for cloud applications, where faults are resource stress or service outage. While those tools conduct chaos experiments between services at the OS level or the network level, CHAOSMACHINE is, to the best of our knowledge, the first to perform chaos experiments in a white-box fashion.…”

Section: Related Workmentioning

confidence: 99%

A Chaos Engineering System for Live Analysis and Falsification of Exception-Handling in the JVM

Zhang

Morin

Haller

et al. 2021

IIEEE Trans. Software Eng.

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Software systems contain resilience code to handle those failures and unexpected events happening in production. It is essential for developers to understand and assess the resilience of their systems. Chaos engineering is a technology that aims at assessing resilience and uncovering weaknesses by actively injecting perturbations in production. In this paper, we propose a novel design and implementation of a chaos engineering system in Java called CHAOSMACHINE. It provides a unique and actionable analysis on exception-handling capabilities in production, at the level of try-catch blocks. To evaluate our approach, we have deployed CHAOSMACHINE on top of 3 large-scale and well-known Java applications totaling 630k lines of code. Our results show that CHAOSMACHINE reveals both strengths and weaknesses of the resilience code of a software system at the level of exception handling.• An empirical evaluation of CHAOSMACHINE on 3 realworld Java systems totaling 630k line of codes, containing 339 try-catch blocks executed by the considered production traffic. It shows the effectiveness of CHAOS-MACHINE to reveal both strengths and weaknesses of a software system's resilience at the exception-handling

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Section: Related Workmentioning

confidence: 99%

A Chaos Engineering System for Live Analysis and Falsification of Exception-Handling in the JVM

Zhang

Morin

Haller

et al. 2021

IIEEE Trans. Software Eng.

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“…For example, in the combination method of TFI and fault diagnosis for distributed systems, fault injection part has the shortcoms of too coarse granularity, inaccuracy and low coverage [20]. The tools developed by industry for OS fault injection include FailViz [26], DICE [27], ZOFI [5] and so on. However, ZOFI has some problems, such as inaccurate fault injection, narrow application scope and only supports fault coverage analysis [5].…”

Section: Introductionmentioning

confidence: 99%

Fault Injection based Failure Analysis of CentOS, Anolis OS and OpenEuler

Xu¹,

Hu²,

Tan³

et al. 2022

Preprint

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The reliability of operating system (OS) has always been a major concern in the academia and industry. This paper studies how to perform OS failure analysis by fault injection based on the fault mode library. Firstly, we use the fault mode generation method based on Linux abstract hierarchy structure analysis to systematically define the Linux-like fault modes, construct a Linux fault mode library and develop a fault injection tool based on the fault mode library (FIFML). Then, fault injection experiments are carried out on three commercial Linux distributions, CentOS, Anolis OS and openEuler, to identify their reliability problems and give improvement suggestions. We also use the virtual file systems of these three OSs as experimental objects, to perform fault injection at levels of Light and Normal, measure the performance of 13 common file operations before and after fault injection.

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