Fault injection

Résumé

In computer science, fault injection is a testing technique for understanding how computing systems behave when stressed in unusual ways. This can be achieved using physical- or software-based means, or using a hybrid approach. Widely studied physical fault injections include the application of high voltages, extreme temperatures and electromagnetic pulses on electronic components, such as computer memory and central processing units. By exposing components to conditions beyond their intended operating limits, computing systems can be coerced into mis-executing instructions and corrupting critical data. In software testing, fault injection is a technique for improving the coverage of a test by introducing faults to test code paths; in particular error handling code paths, that might otherwise rarely be followed. It is often used with stress testing and is widely considered to be an important part of developing robust software. Robustness testing (also known as syntax testing, fuzzi

Source officielle

https://en.wikipedia.org/wiki/Fault_injection

À propos de ce résultat

Cette page est générée automatiquement et peut contenir des informations qui ne sont pas correctes, complètes, à jour ou pertinentes par rapport à votre recherche. Il en va de même pour toutes les autres pages de ce site. Veillez à vérifier les informations auprès des sources officielles de l'EPFL.

Publications associées (12)

Publications associées

Chargement

Personnes associées (3)

Personnes associées

Chargement

Unités associées (2)

Unités associées

Chargement

Concepts associés (3)

Concepts associés

Chargement

Cours associés (1)

Cours associés

Chargement

Séances de cours associées (1)

Séances de cours associées

Chargement

LFI: A Practical and General Library-Level Fault Injector

George Candea, Paul Dan Marinescu

Fault injection, a critical aspect of testing robust systems, is often overlooked in the development of general-purpose software. We believe this is due to the absence of easy-to-use tools and to the extensive manual labor required to perform fault injection tests. This paper introduces LFI (Library Fault Injector), a tool that automates the preparation of fault scenarios and their injection at the boundary between shared libraries and applications. LFI extends prior work by automatically profiling fault behaviors of libraries via static analysis of their binaries, thus reducing the dependence on human labor and perfect documentation. We present techniques for automatically generating injection scenarios and we describe a simple language for expressing such scenarios. LFI does not require access to libraries' source code and works for Linux, Windows, and Solaris on x86 and SPARC platforms.

2009

Chargement

A critical part of developing a reliable software system is testing its recovery code. This code is traditionally difficult to test in the lab, and, in the field, it rarely gets to run; yet, when it does run, it must execute flawlessly in order to recover the system from failure. In this article, we present a library-level fault injection engine that enables the productive use of fault injection for software testing. We describe automated techniques for reliably identifying errors that applications may encounter when interacting with their environment, for automatically identifying high-value injection targets in program binaries, and for producing efficient injection test scenarios. We present a framework for writing precise triggers that inject desired faults, in the form of error return codes and corresponding side effects, at the boundary between applications and libraries. These techniques are embodied in LFI, a new fault injection engine we are distributing http://lfi.epfl.ch. This article includes a report of our initial experience using LFI. Most notably, LFI found 12 serious, previously unreported bugs in the MySQL database server, Git version control system, BIND name server, Pidgin IM client, and PBFT replication system with no developer assistance and no access to source code. LFI also increased recovery-code coverage from virtually zero up to 60% entirely automatically without requiring new tests or human involvement.

2011

Chargement

Techniques for Identifying Elusive Corner-Case Bugs in Systems Software

Radu Banabic

Modern software is plagued by elusive corner-case bugs (e.g., security bugs). Because there are no scalable, automated ways of finding them, such bugs can remain hidden until software is deployed in production. This thesis proposes approaches to solve this problem. First, we present black-box and white-box fault injection mechanisms, which allow developers to test the behavior of their own code in the presence of failures in external components, e.g., in libraries, in the kernel, or in remote nodes of a distributed system. We describe how to make black-box fault injection more efficient, by prioritizing tests based on their estimated impact. For white-box testing, we proposed and implemented a technique to find Trojan messages in distributed systems, i.e., messages that are accepted as valid by receiver nodes, yet cannot be sent by any correct sender node. We show that Trojan messages can lead to subtle semantic bugs. We used fault injection techniques to find new bugs in systems such as the MySQL database, the Apache HTTP server, the FSP file service protocol suite, and the PBFT Byzantine-fault-tolerant replication library. Testing can find bugs and build confidence in the correctness of a system. However, exhaustive testing is often unfeasible, and therefore testing may not discover all bugs before a system is deployed. In the second part of this thesis, we describe how to automatically harden production systems, reducing the impact of any corner-case bugs missed by testing. We present a framework that reduces the overhead cost of instrumentation tools such as memory error detectors. Lowering the cost enables system developers to use such tools in production to harden their systems, reducing the impact of any remaining corner-case bugs. We used our framework to generate a version of the Linux kernel hardened with Address Sanitizer. Our hardened kernel has most of the benefit of full instrumentation: it detects the same vulnerabilities as full instrumentation (7 out of 11 privilege escalation exploits from 2013-2014 can be detected using instrumentation tools). Yet, it obtains these benefits at only a quarter of the overhead.

EPFL2015

Chargement

Techniques for Identifying Elusive Corner-Case Bugs in Systems Software

Radu Banabic

EPFL2015