Automatic failure-path inference: a generic introspection technique for Internet applications

Candea, George; Delgado, M. Kit; Chen, Mike Y.; Fox, Armando

doi:10.1109/wiapp.2003.1210298

Cited by 48 publications

(55 citation statements)

References 13 publications

(23 reference statements)

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“…The authors targeted Linux file system implementations at the source-code level and used block-level fault injection to confirm several categories of bugs. Tools for analyzing the propagation of Java exceptions have also been described by Candea et al [2003], Fu et al [2004], as well as Weimer and Necula [2008]. These tools use functional specifications that are known a priori.…”

Section: Related Workmentioning

confidence: 99%

Efficient Testing of Recovery Code Using Fault Injection

Marinescu

Candea

2011

ACM Trans. Comput. Syst.

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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.

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Section: Related Workmentioning

confidence: 99%

Efficient Testing of Recovery Code Using Fault Injection

Marinescu

Candea

2011

ACM Trans. Comput. Syst.

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“…The monitoring data we collect primarily includes the number of procedure invocations per minute of various Java modules (Java beans) in the application server while the Web service is in operation. We employ a failure-injection tool [5] to systematically inject failures into Rubis and JBoss. The types of failures injected in our experiments include Java exceptions, message drops, deadlocks, JNDI corruptions, data corruptions, memory leaks, and infinite loops.…”

Section: Methodsmentioning

confidence: 99%

Guided Problem Diagnosis through Active Learning

Duan

Babu

2008

2008 International Conference on Autonomic Computing

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“…Candea et al [7] used exception injection to capture the error-related dependencies between artifacts of an application. They inject checked exceptions as well as 6 runtime, unchecked exceptions.…”

Section: Related Workmentioning

confidence: 99%

Exception handling analysis and transformation using fault injection: Study of resilience against unanticipated exceptions

Cornu¹,

Seinturier²,

Monperrus³

2015

Information and Software Technology

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Context: In software, there are the error cases that are anticipated at specification and design time, those encountered at development and testing time, and those that were never anticipated before happening in production. Is it possible to learn from the anticipated errors during design to analyze and improve the resilience against the unanticipated ones in production?Objective: In this paper, we aim at analyzing and improving how software handles unanticipated exceptions. The first objective is to set up contracts about exception handling and a way to assess them automatically. The second one is to improve the resilience capabilities of software by transforming the source code. Method:We devise an algorithm, called short-circuit testing, which injects exceptions during test suite execution so as to simulate unanticipated errors. It is a kind of fault-injection techniques dedicated to exceptionhandling. This algorithm collects data that is used for verifying two formal contracts that capture two resilience properties w.r.t. exceptions: the source-independence and pure-resilience contracts. Then we propose a code modification technique, called "catch-stretching" which allows error-recovery code (of the form of catch blocks) to be more resilient. Results:Our evaluation is performed on 9 open-source software applications and consists in analyzing 241 catch blocks executed during test suite execution. Our results show that 101/214 of them (47%) expose resilience properties as defined by our exception contracts and that 84/214 of them (39%) can be transformed to be more resilient. Conclusion:Our work shows that it is possible to reason on software resilience by injecting exceptions during test suite execution. The collected information allows us to apply one source code transformation that improves the resilience against unanticipated exceptions. This works best if the test suite exercises the exceptional programming language constructs in many different scenarios.

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Automatic failure-path inference: a generic introspection technique for Internet applications

Cited by 48 publications

References 13 publications

Efficient Testing of Recovery Code Using Fault Injection

Efficient Testing of Recovery Code Using Fault Injection

Guided Problem Diagnosis through Active Learning

Exception handling analysis and transformation using fault injection: Study of resilience against unanticipated exceptions

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