EPIC: profiling the propagation and effect of data errors in software

Hiller, Martin; Jhumka, Arshad; Suri, Neeraj

doi:10.1109/tc.2004.1275294

Cited by 48 publications

(37 citation statements)

References 33 publications

(34 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The methodology in [2] assumes a single failure mode and provides tools to analyze how sensible the system is with respect to both failure and error propagation probability of each of its components. In [3], the authors proposed a notion of error permeability for modules as a basic characterization of modules' attitude to propagate errors. Also in this case, a single, non-halting failure mode is considered.…”

Section: Related Workmentioning

confidence: 99%

Reliability Analysis of Component-Based Systems with Multiple Failure Modes

Filieri

Ghezzi

Grassi

et al. 2010

Component-Based Software Engineering

View full text Add to dashboard Cite

Abstract. This paper presents a novel approach to the reliability modeling and analysis of a component-based system that allows dealing with multiple failure modes and studying the error propagation among components. The proposed model permits to specify the components attitude to produce, propagate, transform or mask different failure modes. These component-level reliability specifications together with information about systems global structure allow precise estimation of reliability properties by means of analytical closed formulas, probabilistic modelchecking or simulation methods. To support the rapid identification of components that could heavily affect systems reliability, we also show how our modeling approach easily support the automated estimation of the system sensitivity to variations in the reliability properties of its components. The results of this analysis allow system designers and developers to identify critical components where it is worth spending additional improvement efforts.

show abstract

Section: Related Workmentioning

confidence: 99%

Reliability Analysis of Component-Based Systems with Multiple Failure Modes

Filieri

Ghezzi

Grassi

et al. 2010

Component-Based Software Engineering

View full text Add to dashboard Cite

show abstract

“…Since instrumentation is done on the source code of the target software, propagation can be studied down to individual signals (variables) of the components of the system. Together with the measures defined in the EPIC framework (Exposure, Permeability, Impact, Criticality), PROPANE was used to evaluate the propagation of errors in an aircraft arrestment system [Hiller et al, 2004;Hiller, 2002].…”

Section: Fault Injectionmentioning

confidence: 99%

“…Hiller developed an extensive propagation profiling framework for embedded control systems [Hiller et al, 2004;Hiller, 2002]. Based on a component model error propagation metrics similar to the ones developed in this thesis are presented.…”

Section: Related Workmentioning

confidence: 99%

Robustness Evaluation of Operating Systems

Johansson

2008

Information Assurance

View full text Add to dashboard Cite

SummaryThe premise behind this thesis is the observation that Operating Systems (OS), being the foundation behind operations of computing systems, are complex entities and also subject to failures. Consequently, when they do fail, the impact is the loss of system service and the applications running thereon. While a multitude of sources for OS failures exist, device drivers are often identified as a prominent cause behind failures.In order to characterize the impact of driver failures, at both the OS and application levels, this thesis develops a framework for error propagation-based robustness profiling for an OS. The framework is first developed conceptually and then experimentally validated on a real OS, namely Windows CE .Net. The choice of Windows CE is driven by its representativeness for a multitude of OS's, as well as the ability to customize the OS components for particular needs.For experimental validation, fault injection is a prominent technique that can be used to simulate faults (or errors) in the system by inserting synthetic ones and study their effect. Three key questions with such a technique are where, what and when to inject faults. This thesis shows how injecting errors at the interface between drivers and the OS can be very effective in evaluating the effects driver faults can have.To quantify the OS's robustness, this thesis defines a series of error propagation measures, specifically tailored for device drivers. These measures allow for quantifying and comparing both individual services and device drivers on their susceptibility and diffusing abilities.This thesis compares three contemporary error models on their suitability for robustness evaluation. The classical bit-flip model is found to identify a higher number of severe failures in the system. It also identifies failures for more services than both other models, data type and fuzzing. However, its main drawback is that it requires substantially more injections than the other two. Fuzzing, even though not giving rise to as many failures is able to find new additional services with severe failures.A careful study of the injections performed with the bit-flip model shows that only a few bits are generally useful for identifying new services with robustness weaknesses. Consequently, a new composite model is proposed, combining the most effective bits of the bit-flip model with the fuzzing model's ability to identify new services, giving rise to new model without loss of important information and at the same time incurring a moderate number of injections.To answer the question of when to inject an error this thesis proposes a novel model of a driver's usage profile, focusing on high-level operations being carried out. It guides the injection of errors to instances when the driver is carrying out specific operations. Results from extensive fault injection experiments show that more service vulnerabilities can be discovered. Furthermore, a priori profiling of the drivers can show how effective the proposed approach will be. vi

show abstract

“…Moreover, in the same paper the authors also stress the importance of considering the error propagation process among system components. Nonetheless, few modeling approaches deal with error propagation across a component-based system (e.g., [11,23,2]) and with multiple failure modes [13]. On the other hand, to get a complete view of the possible failure pathology of the whole system, it is important to take into account that components can experience a number of different failure modes and those failures can propagate in different ways across the execution flow, possibly spreading up to the application interface.…”

Section: Introduction and Motivationsmentioning

confidence: 99%

A compositional method for reliability analysis of workflows affected by multiple failure modes

Distefano

Filieri

Ghezzi

et al. 2011

Proceedings of the 14th International ACM Sigsoft Symposium on Component Based Software Engineering

View full text Add to dashboard Cite

We focus on reliability analysis for systems designed as workflowbased compositions of components. Components are characterized by their failure profiles, which take into account possible multiple failure modes. A compositional calculus is provided to evaluate the failure profile of a composite system, given failure profiles of the components. The calculus is described as a syntax-driven procedure that synthesizes a workflow's failure profile. The method is viewed as a design-time aid that can help software engineers reason about system's reliability in the early stage of development. A simple case study is presented to illustrate the proposed approach.

show abstract

EPIC: profiling the propagation and effect of data errors in software

Cited by 48 publications

References 33 publications

Reliability Analysis of Component-Based Systems with Multiple Failure Modes

Reliability Analysis of Component-Based Systems with Multiple Failure Modes

Robustness Evaluation of Operating Systems

A compositional method for reliability analysis of workflows affected by multiple failure modes

Contact Info

Product

Resources

About