Dependability: Basic Concepts and Terminology

Laprie, Jean-Claude; Avižienis, A.; Kopetz, Hermann

doi:10.1007/978-3-7091-9170-5_1

Cited by 368 publications

(227 citation statements)

References 0 publications

Supporting

Mentioning

203

Contrasting

Unclassified

Order By: Relevance

“…• HAZOP [7], (Kletz 1983)-hazard and operability analysis, • FME(C)A (Department of Defense 1949 )-failure modes, effects, (and criticality) analysis, • FTA (Vesely et al 1981;Laprie 1992)-fault tree analysis.…”

Section: Risk Analysismentioning

confidence: 99%

How Good Is My Test Data? Introducing Safety Analysis for Computer Vision

et al. 2017

View full text Add to dashboard Cite

Good test data is crucial for driving new developments in computer vision (CV), but two questions remain unanswered: which situations should be covered by the test data, and how much testing is enough to reach a conclusion? In this paper we propose a new answer to these questions using a standard procedure devised by the safety community to validate complex systems: the hazard and operability analysis (HAZOP). It is designed to systematically identify possible causes of system failure or performance loss. We introduce a generic CV model that creates the basis for the hazard analysis and-for the first time-apply an extensive HAZOP to the CV domain. The result is a publicly available checklist with more than 900 identified individual hazards. This checklist can be utilized to evaluate existing test datasets by quantifying the covered hazards. We evaluate our approach by first analyzing and annotating the popular stereo vision test datasets Middlebury and KITTI. Second, we demonstrate a clearly negative influence of the hazards in the checklist on the performance of six popular stereo matching algorithms. The presented approach is a useful tool to evaluate and improve test datasets and creates a common basis for future dataset designs.

show abstract

Section: Risk Analysismentioning

confidence: 99%

How Good Is My Test Data? Introducing Safety Analysis for Computer Vision

et al. 2017

View full text Add to dashboard Cite

show abstract

“…An error is the manifestation of a fault and a failure occurs, when the component's behavior deviates from its specified behavior [1].…”

Section: Formal System Modelmentioning

confidence: 99%

Adaptive Error and Sensor Management for Autonomous Vehicles: Model-Based Approach and Run-Time System

Frtunikj

Rupanov

Armbruster

et al. 2014

Model-Based Safety and Assessment

View full text Add to dashboard Cite

Abstract. Over the past few years semi-autonomous driving functionality was introduced in the automotive market, and this trend continues towards fully autonomous cars. While in autonomous vehicles data from various types of sensors realize the new highly safety critical autonomous functionality, the already complex system architecture faces the challenge of designing highly reliable and safe autonomous driving system. Since sensors are prone to intermittent faults, using different sensors is better and more cost effective than duplicating the same sensor type because of diversity of reaction of different sensor typesto the same environmental condition. Specifying and validating sensors and providing technical means that enable usage of data from different sensors in case of failures is a challenging, time-consuming and error-prone task for engineers. Therefore, in this paper we present our model-based approach and a runtime system that improves the safety of autonomous driving systems by providing reusable framework managing different sensor setups in a vehicle in a case of a error. Moreover, the solution that we provide enables adaptive graceful degradation and reconfiguration by effective use of the system resources. At the end we explain in an example when and how the approach can be applied.

show abstract

“…There are presented four basic attributes (Availability, Reliability, Security, Safety) in [3] and in addition presents other three attributes (Maintainability, Integrity, Credibility). In summary there is one additional attribute (Safety).…”

Section: Definition Of Dependability Attributes and Parametersmentioning

confidence: 99%