Scalable Analysis of Fault Trees with Dynamic Features
|
|
|
- Kristina Dorsey
- 6 years ago
- Views:
Transcription
1 Scalable Analysis of Fault Trees with Dynamic Features Jan Krčál 1, Pavel Krčál 2,3 1 Saarland University Computer Science, Saarbrücken, Germany 2 Lloyd's Register Consulting, Stockholm, Sweden 3 Uppsala University, Sweden DSN 2015 (IEEE/IFIP Conference on Dependable Systems and Networks) TUM, December 11, 2015
2 Probability of an incident?
3 Probability of an incident? There are some incidents you cannot avoid. For everything else there is
4 Probability of an incident? There are some incidents you cannot avoid. For everything else there is fault tree analysis!
5 (Static) Fault Trees: The Model
6 (Static) Fault Trees: The Model 9x10-4 5x10-3 8x10-3 5x10-3 8x10-3
7 (Static) Fault Trees: The Model How to obtain the numbers? 1) Time-independent failure Average number of starts before failure: 200 Failure probability x10-4 5x10-3 8x10-3 5x10-3 8x10-3
8 (Static) Fault Trees: The Model 2) Time-dependent failure: 9x10-4 5x10-3 8x10-3 5x10-3 8x10-3 How to obtain the numbers? 1) Time-independent failure Average number of starts before failure: 200 Failure probability On average once per 4700 h Mission time: 24h Probability to fail in 24 hours: 1 e
9 (Static) Fault Trees: The Model How to obtain the numbers? 1) Time-independent failure Average number of starts before failure: 200 Failure probability ) Time-dependent failure: 9x10-4 On average once per 4700 h Mission time: 24h Probability to fail in 24 hours: 1 e x10-3 8x10-3 5x10-3 8x10... and from -3 further models
10 Fault Trees: The Application Assessing & managing risk Nuclear power plants Nuclear Submarines Aviation & Aerospace Transportation systems
11 Fault Trees: The Application Assessing & managing risk Nuclear power plants Nuclear Submarines Aviation & Aerospace Transportation systems licensed at > 55% of nuclear PP
12 Fault Trees: The Application Assessing & managing risk Nuclear power plants Nuclear Submarines Aviation & Aerospace Transportation systems licensed at > 55% of nuclear PP fault trees with 50,000+ nodes
13 Fault Trees: The Application Assessing & managing risk Nuclear power plants Nuclear Submarines Aviation & Aerospace Transportation systems licensed at > 55% of nuclear PP fault trees with 50,000+ nodes model maintenance costs of millions of every year per nuclear PP
14 Theme of this work: The Tradeoff Expressiveness vs. Scalability
15 Theme of this work: The Tradeoff Expressiveness vs. Scalability
16 Theme of this work: The Tradeoff Expressiveness vs. Scalability
17 The tradeoff: Static not expressive Example: a redundant pump system: survives for 24h?
18 The tradeoff: Static not expressive Example: a redundant pump system: survives for 24h? 5x10-2 5x10-2 5x10-2 5x10-2 5x10-2 Failure probabilities obtained from a CTMC disregarding repairs:
19 The tradeoff: Static not expressive Example: a redundant pump system: survives for 24h? 5x10-2 5x10-2 5x10-2 5x10-2 5x10-2 Failure probabilities obtained from a CTMC disregarding repairs: Probability of failure: (0.05) 5 = unrealistically high!
20 The tradeoff: Dynamic not scale
21 The tradeoff: Dynamic not scale Analysis with timing scales to: 100 basic events and 200 gates
22 The tradeoff: Dynamic not scale Analysis with timing scales to: We need to analyze: 100 basic events and 200 gates basic events and gates
23 The tradeoff: Dynamic not scale Analysis with timing scales to: We need to analyze: 100 basic events and 200 gates states! basic events and gates a great achievement!
24 The tradeoff: Dynamic not scale Analysis with timing scales to: We need to analyze: 100 basic events and 200 gates states! a great achievement! basic events and gates states! can you handle it?
25 The tradeoff: Dynamic not scale Analysis with timing scales to: We need to analyze: 100 basic events and 200 gates states! a great achievement! basic events and gates states! can you handle it?
26 Outline: 1) The formalism: static and dynamic fault trees 2) The algorithm: minimal cut set list decomposition 3) Experiments: on toy & real-sized models
27 The Formalism: SD Fault Trees
28 The Formalism: SD Fault Trees
29 The Formalism: SD Fault Trees
30 The Formalism: SD Fault Trees
31 The Formalism: SD Fault Trees 9x10-4 5x10-3 8x10-3
32 Outline: 1) The formalism: static and dynamic fault trees 2) The algorithm: minimal cut set list decomposition 3) Experiments: on toy & real-sized models
33 The Algorithm: Static Fault Trees
34 The Algorithm: Static Fault Trees
35 The Algorithm: Static Fault Trees 9x10-4 Algorithm: 5x10-3 8x10-3 5x10-3 8x10-3
36 The Algorithm: Static Fault Trees 5x10-3 8x10-3 5x10-3 8x10-3 9x10-4 MCS: ac bd ad bc e Algorithm: 1. Find relevant minimal cut sets (MCS)
37 The Algorithm: Static Fault Trees 5x10-3 8x10-3 5x10-3 8x10-3 9x10-4 MCS: ac 2.5x10-5 bd 6.4x10-5 ad 4x10-5 bc 4x10-5 e 9x10-4 Algorithm: 1. Find relevant minimal cut sets (MCS) 2. Quantify the MCS
38 The Algorithm: Static Fault Trees 5x10-3 8x10-3 5x10-3 8x10-3 9x10-4 MCS: ac 2.5x10-5 bd 6.4x10-5 ad 4x10-5 bc 4x10-5 e 9x10-4 ALL: 1.069x10-3 Algorithm: 1. Find relevant minimal cut sets (MCS) 2. Quantify the MCS 3. Compute the overall probability of failure.
39 The Algorithm: SD Fault Trees
40 The Algorithm: SD Fault Trees
41 The Algorithm: SD FT 9x10-4 MCS: ac ad bc bd e 5x10-3 8x10-3 Algorithm: 1. Find relevant minimal cut sets (MCS)
42 The Algorithm: SD FT 9x10-4 MCS: ac 2.5x10-5 ad 5x10-3. mc(d) = 2.37x10-2 bc 8x10-3. mc(b) = 2.37x10-2 bd mc(b,d) = 2.828x10-4 e 9x10-4 5x10-3 8x10-3 Algorithm: 1. Find relevant minimal cut sets (MCS) 2. Quantify the MCS
43 The Algorithm: SD FT 9x10-4 MCS: ac 2.5x10-5 ad 5x10-3. mc(d) = 2.37x10-2 bc 8x10-3. mc(b) = 2.37x10-2 bd mc(b,d) = 2.828x10-4 e 9x10-4 ALL: 1.516x10-3 5x10-3 8x10-3 Algorithm: 1. Find relevant minimal cut sets (MCS) 2. Quantify the MCS 3. Compute the overall probability of failure.
44 The Algorithm: SD FT 9x10-4 MCS: ac 2.5x10-5 ad 5x10-3. mc(d) = 2.37x10-2 bc 8x10-3. mc(b) = 2.37x10-2 bd mc(b,d) = 2.828x10-4 e 9x10-4 ALL: 1.516x10-3 5x10-3 8x10-3 Algorithm: 1. Find relevant minimal cut sets (MCS) 2. Quantify the MCS 3. Compute the overall probability of failure.
45 The Algorithm: SD FT 9x10-4 MCS: ac 2.5x10-5 ad 5x10-3. mc(d) = 2.37x10-2 bc 8x10-3. mc(b) = 2.37x10-2 bd mc(b,d) = 2.828x10-4 e 9x10-4 ALL: 1.516x10-3 5x10-3 8x10-3 Algorithm: 1. Find relevant minimal cut sets (MCS) 2. Quantify the MCS 3. Compute the overall probability of failure.
46 The Algorithm: MCS Quantification Quantifying mc(b,d): 9x10-4 5x10-3 8x10-3
47 The Algorithm: MCS Quantification Quantifying mc(b,d): 1. Build a SD fault tree of the MCS 9x10-4 5x10-3 8x10-3
48 The Algorithm: MCS Quantification Quantifying mc(b,d): 1. Build a SD fault tree of the MCS 9x10-4 5x10-3 8x10-3
49 The Algorithm: MCS Quantification Quantifying mc(b,d): 1. Build a SD fault tree of the MCS 9x Translate the SD fault tree to its semantical CTMC II 5x10-3 8x10-3
50 The Algorithm: MCS Quantification Quantifying mc(b,d): 1. Build a SD fault tree of the MCS 9x Translate the SD fault tree to its semantical CTMC II 5x10-3 8x x Quantify the probability by transient analysis of the semantical CTMC
51 The Algorithm: MCS Quantification General model of a triggering gate g: 1. includes only dynamic BE from the MCS if g has static branching
52 The Algorithm: MCS Quantification General model of a triggering gate g: 1. includes only dynamic BE from the MCS if g has static branching 2. includes only dynamic BE below g if g has static joins
53 The Algorithm: MCS Quantification General model of a triggering gate g: 1. includes only dynamic BE from the MCS if g has static branching 2. includes only dynamic BE below g if g has static joins 3. includes the all BE below g otherwise.
54 The Algorithm: MCS Quantification Static branching: at most one child of any OR gate is dynamic Static joins: no child of any AND gate is dynamic A component has static branching for, e.g., 1. single dynamic BE; 2. arbitrarily many additional static BE; 3. redundant subcomponents; 4. nested triggering. A component has static joins for, e.g., 1. arbitrarily many dynamic subcomponents 2. as well as static; 3. can be combined into a sequence of redundant components.
55 Outline: 1) The formalism: static and dynamic fault trees 2) The algorithm: minimal cut set list decomposition 3) Experiments: on toy & real-sized models
56 Experiments: Can we really handle it? Experiments: 1. small realistically annotated tree only with static joins 2. industrial randomly annotated tree with static branching # # basic e. # gates # MCS
57 Experiments: Can we really handle it? Experiments: 1. small realistically annotated tree only with static joins 2. industrial randomly annotated tree with static branching RiskSpectrum (for finding MCSs) + PRISM (for analyzing MCS) # # basic e. # gates # MCS RiskSpectrum PRISM
58 Experiments: Can we really handle it? Experiments: 1. small realistically annotated tree only with static joins 2. industrial randomly annotated tree with static branching RiskSpectrum (for finding MCSs) + PRISM (for analyzing MCS) # # basic e. # gates # MCS RiskSpectrum PRISM < 1 s h 11min
59 Experiments: Can we really handle it? Experiments: 1. small realistically annotated tree only with static joins 2. industrial randomly annotated tree with static branching RiskSpectrum (for finding MCSs) + PRISM (for analyzing MCS) # # basic e. # gates # MCS RiskSpectrum PRISM < 1 s < 10 s h 11min 2m 12s
60 Experiments: Can we really handle it? Experiments: 1. small realistically annotated tree only with static joins 2. industrial randomly annotated tree with static branching RiskSpectrum (for finding MCSs) + PRISM (for analyzing MCS) # # basic e. # gates # MCS RiskSpectrum PRISM < 1 s < 10 s h 11min 2m 12s MCS sizes: Analysis time per size:
61 Summary
62 Summary 1. We allow timing for very large fault trees
63 Summary 1. We allow timing for very large fault trees 2. We show the boundaries of MCS decomposition
64 Summary 1. We allow timing for very large fault trees 2. We show the boundaries of MCS decomposition Future work Go beyond the restrictions of static branching/joins using analysis of incomplete Markov Chains Experiments with real large models (needs quite some effort)
65 Summary 1. We allow timing for very large fault trees 2. We show the boundaries of MCS decomposition Future work Go beyond the restrictions of static branching/joins using analysis of incomplete Markov Chains Experiments with real large models (needs quite some effort)
66 Current work beyond static-* Trigger in the SD fault tree of a MCS:
67 Current work beyond static-* Trigger in the SD fault tree of a MCS: Approximations: assume BEs with least impact fail at non-deterministic time (failure - a message in an open Interactive MC) Over: max over all schedulers Under: min over all schedulers
68 Current work beyond static-* Trigger in the SD fault tree of a MCS: Approximations: assume BEs with least impact fail at non-deterministic time (failure - a message in an open Interactive MC) Over: max over all schedulers Under: min over all schedulers
69 Current work beyond static-* Trigger in the SD fault tree of a MCS: Approximations: assume BEs with least impact fail at non-deterministic time (failure - a message in an open Interactive MC) Over: max over all schedulers Under: min over all schedulers Preliminary experiments: a small model hand-annotated without static joins/branching approximation: two significant digits in ca. 10 s; the full algorithm: never terminates
70 Summary 1. We allow timing for very large fault trees 2. We show the boundaries of MCS decomposition Future work Go beyond the restrictions of static branching/joins using analysis of incomplete Markov Chains Experiments with real large models (needs quite some effort) Thank you!
DEVELOPMENT OF AN ADVANCED FAULT TREE QUANTIFICATION ENGINE BASED ON BDD/ZBDD ALGORITHM
DEVELOPMENT OF AN ADVANCED FAULT TREE QUANTIFICATION ENGINE BASED ON BDD/ZBDD ALGORITHM Wei GAO 1, Qinfang ZHANG 1, Guofeng TANG 1 1 Shanghai Nuclear Engineering Research & Design Institute, Shanghai,
Approaches to the SoC IP- Blocks Design With Errors Mitigation
Approaches to the SoC IP- Blocks Design With Errors Mitigation Valentin Rozanov, Elena Suvorova Saint-Petersburg of Aerospace Instrumentation Errors on different stages of IP-block lifetime Design of SoC
TIMED-FAULT TREE GENERATION FROM DYNAMIC FLOWGRAPH METHOD
TIMED-FAULT TREE GENERATION FROM DYNAMIC FLOWGRAPH METHOD Chireuding Zeliang Graduate Research Assistant Faculty of Energy Systems and Nuclear Science University of Ontario Institute of Technology Oshawa,
Fault Tree Linking versus Event Tree Linking Approaches: A Mathematical and Algorithmic Reconciliation
Fault Tree Linking versus Event Tree Linking Approaches: A Mathematical and Algorithmic Reconciliation Dr. O. Nusbaumer, Switzerland Prof. Dr. A. Rauzy, France Fault Tree Linking (FTL) vs. Event Tree Linking
ExCuSe A Method for the Model-Based Safety Assessment of Simulink and Stateflow Models
ExCuSe A Method for the Model-Based Safety Assessment of Simulink and Stateflow Models MATLAB Expo 2018 2018-06-26 München Julian Rhein 1 Outline Introduction Property Proving Application to Safety Assessment
Stochastic Petri nets
Stochastic Petri nets 1 Stochastic Petri nets Markov Chain grows very fast with the dimension of the system Petri nets: High-level specification formalism Markovian Stochastic Petri nets adding temporal
New Logic Modeling Paradigms for Complex System Reliability and Risk Analysis
New Logic Modeling Paradigms for Complex System Reliability and Risk Analysis Antoine Rauzy Chair Blériot-Fabre* - Ecole Centrale de Paris Ecole Polytechnique FRANCE Antoine.Rauzy@ecp.fr http://www.lgi.ecp.fr/pmwiki.php/pagesperso/arauzy
Dependable and Secure Systems Dependability Master of Science in Embedded Computing Systems
Dependable and Secure Systems Dependability Master of Science in Embedded Computing Systems Quantitative Dependability Analysis with Stochastic Activity Networks: the Möbius Tool April 2016 Andrea Domenici
Dependable and Secure Systems Dependability
Dependable and Secure Systems Dependability Master of Science in Embedded Computing Systems Quantitative Dependability Analysis with Stochastic Activity Networks: the Möbius Tool Andrea Domenici DII, Università
Precise and Efficient FIFO-Replacement Analysis Based on Static Phase Detection
Precise and Efficient FIFO-Replacement Analysis Based on Static Phase Detection Daniel Grund 1 Jan Reineke 2 1 Saarland University, Saarbrücken, Germany 2 University of California, Berkeley, USA Euromicro
SELF-HEALING NETWORKS: REDUNDANCY AND STRUCTURE
SELF-HEALING NETWORKS: REDUNDANCY AND STRUCTURE Guido Caldarelli IMT, CNR-ISC and LIMS, London UK DTRA Grant HDTRA1-11-1-0048 INTRODUCTION The robustness and the shape Baran, P. On distributed Communications
Dependability studies, focus on fault trees and Figaro language
February 3, workshop Dependability studies, focus on fault trees and Figaro language Marc Bouissou ECP, Laboratoire Génie Industriel & EDF R&D, dépt Management des Risques Industriels Lena Buffoni PELAB,
DATABASE DESIGN II - 1DL400
DATABASE DESIGN II - 1DL400 Fall 2016 A second course in database systems http://www.it.uu.se/research/group/udbl/kurser/dbii_ht16 Kjell Orsborn Uppsala Database Laboratory Department of Information Technology,
Module 4: Stochastic Activity Networks
Module 4: Stochastic Activity Networks Module 4, Slide 1 Stochastic Petri nets Session Outline Places, tokens, input / output arcs, transitions Readers / Writers example Stochastic activity networks Input
Scalable Distributed Control of Network of DERs
Scalable Distributed Control of Network of DERs Steven Low Computing + Math Sciences Electrical Engineering Caltech December 2012 Large active network of DERs DER: PVs, wind turbines, batteries, EVs, DR
Clustering. k-mean clustering. Genome 559: Introduction to Statistical and Computational Genomics Elhanan Borenstein
Clustering k-mean clustering Genome 559: Introduction to Statistical and Computational Genomics Elhanan Borenstein A quick review The clustering problem: homogeneity vs. separation Different representations
Software Engineering of Robots
Software Engineering of Robots Ana Cavalcanti Jon Timmis, Jim Woodcock Wei Li, Alvaro Miyazawa, Pedro Ribeiro University of York December 2015 Overview One of UK eight great technologies: robotics and
Automatic Implementation of the KKL seismic PSA
Automatic Implementation of the KKL seismic PSA Yann Stempfel Automatic Implementation of the KKL seismic PSA, Y. Stempfel Folie 1 Contents Goal and processes of the KKL seismic PSA The challenges of the
Reliable Distributed System Approaches
Reliable Distributed System Approaches Manuel Graber Seminar of Distributed Computing WS 03/04 The Papers The Process Group Approach to Reliable Distributed Computing K. Birman; Communications of the ACM,
Defence services. Independent systems and technology advice that delivers real value. Systems and Engineering Technology
Defence services Independent systems and technology advice that delivers real value Systems and Engineering Technology Frazer-Nash Consultancy Working in the UK and internationally, Frazer-Nash is making
Service-now training For IT-UDS group
Service-now training for UDS Service-now training For IT-UDS group Belinda Chan, Nicole Crémel Service-Now UDS training [Jan 2011] - 1 Agenda Improving Service Management CERN Service Catalogue UDS services
Case Study: Social Network Analysis. Part II
Case Study: Social Network Analysis Part II https://sites.google.com/site/kdd2017iot/ Outline IoT Fundamentals and IoT Stream Mining Algorithms Predictive Learning Descriptive Learning Frequent Pattern
Resilient IP Backbones. Debanjan Saha Tellium, Inc.
Resilient IP Backbones Debanjan Saha Tellium, Inc. dsaha@tellium.com 1 Outline Industry overview IP backbone alternatives IP-over-DWDM IP-over-OTN Traffic routing & planning Network case studies Research
Dynamic Fault Tree analysis using Input/Output Interactive Markov Chains
Dynamic Fault Tree analysis using Input/Output Interactive Markov Chains Hichem Boudali hboudali@cs.utwente.nl Pepijn Crouzen, crouzen@alan.cs.uni-sb.de University of Twente, Department of Computer Science,
CSE 127 Computer Security
CSE 127 Computer Security Alex Gantman, Spring 2018, Lecture 19 SDLC: Secure Development Lifecycle Defining Security Security is not a functionality feature Most of computer science is about providing
High Availability and Disaster Recovery Solutions for Perforce
High Availability and Disaster Recovery Solutions for Perforce This paper provides strategies for achieving high Perforce server availability and minimizing data loss in the event of a disaster. Perforce
Chapter 8 Fault Tolerance
DISTRIBUTED SYSTEMS Principles and Paradigms Second Edition ANDREW S. TANENBAUM MAARTEN VAN STEEN Chapter 8 Fault Tolerance 1 Fault Tolerance Basic Concepts Being fault tolerant is strongly related to
l Some materials from various sources! n Current course textbook! Soma 1! Soma 3!
Ackwledgements! Test generation algorithms! Mani Soma! l Some materials from various sources! n r. Phil Nigh, IBM! n Principles of Testing Electronic Systems by S. Mourad & Y. Zorian! n Essentials of Electronic
Michigan Department of Education
Michigan Department of Education NEW REQUIREMENTS IN ESSA AND PEER REVIEW AND STATES RESPONSES ON TEST INTEGRITY AND SECURITY NATIONAL CONFERENCE ON STUDENT ASSESSMENT 2017 Pietro Semifero Online Assessment
Model-based Architectural Verification & Validation
Model-based Architectural Verification & Validation Software Engineering Institute Carnegie Mellon University Pittsburgh, PA 15213 Peter H Feiler Feb. 2009 2006 Carnegie Mellon University Outline Architecture-Centric
Formal Methods and their role in Software and System Development. Riccardo Sisto, Politecnico di Torino
Formal Methods and their role in Software and System Development Riccardo Sisto, Politecnico di Torino What are Formal Methods? Rigorous (mathematical) methods for modelling and analysing (computer-based)
UML for Real-Time Overview
Abstract UML for Real-Time Overview Andrew Lyons April 1998 This paper explains how the Unified Modeling Language (UML), and powerful modeling constructs originally developed for the modeling of complex
COMPASS: FORMAL METHODS FOR SYSTEM-SOFTWARE CO-ENGINEERING
COMPASS: FORMAL METHODS FOR SYSTEM-SOFTWARE CO-ENGINEERING Viet Yen Nguyen Lehrstuhl für Informatik 2, RWTH Aachen University nguyen@cs.rwth-aachen.de Technology Innovation Days, ESA/ESTEC, 2011 ABOUT
Safety and Reliability of Embedded Systems. (Sicherheit und Zuverlässigkeit eingebetteter Systeme) Safety and Reliability Analysis Models: Overview
(Sicherheit und Zuverlässigkeit eingebetteter Systeme) Safety and Reliability Analysis Models: Overview Content Classification Hazard and Operability Study (HAZOP) Preliminary Hazard Analysis (PHA) Event
SCALABLE CONSISTENCY AND TRANSACTION MODELS
Data Management in the Cloud SCALABLE CONSISTENCY AND TRANSACTION MODELS 69 Brewer s Conjecture Three properties that are desirable and expected from realworld shared-data systems C: data consistency A:
Consistency in Distributed Storage Systems. Mihir Nanavati March 4 th, 2016
Consistency in Distributed Storage Systems Mihir Nanavati March 4 th, 2016 Today Overview of distributed storage systems CAP Theorem About Me Virtualization/Containers, CPU microarchitectures/caches, Network
What To Ask Your SD-WAN Vendor
#FutureWAN What To Ask Your SD-WAN Vendor Ramesh Prabagaran, VP of Product Management Twitter: @ramsba Motivation & Rationale Marketing vs Reality Network auto provisions, auto corrects, auto everything
Internal Flooding According to EPRI Guidelines Detailed Electrical Mapping at Ringhals
Internal Flooding According to EPRI Guidelines Detailed Electrical Mapping at Ringhals Per Nyström a, Carl Sunde a, and Cilla Andersson b a Risk Pilot, Gothenburg, Sweden b Ringhals AB, Varberg, Sweden
Aerospace Software Engineering
16.35 Aerospace Software Engineering Verification & Validation Prof. Kristina Lundqvist Dept. of Aero/Astro, MIT Would You...... trust a completely-automated nuclear power plant?... trust a completely-automated
CMPE223/CMSE222 Digital Logic
CMPE223/CMSE222 Digital Logic Optimized Implementation of Logic Functions: Strategy for Minimization, Minimum Product-of-Sums Forms, Incompletely Specified Functions Terminology For a given term, each
GNUnet Distributed Data Storage
GNUnet Distributed Data Storage DHT and Distance Vector Transport Nathan S. Evans 1 1 Technische Universität München Department of Computer Science Network Architectures and Services July, 24 2010 Overview
T500 DUALTACH. JAQUET T500 DualTach. 2 channel measurement & monitoring instrument 2 CHANNEL TACHOMETER I N C H A R G E O F S P E E D.
1-08 T500 DUALTACH 2 CHANNEL TACHOMETER JAQUET T500 DualTach 2 channel measurement & monitoring instrument JAQUET T500 DualTach 2 channel measurement and monitoring instrument for demanding machine protection
All you need is fun. Cons T Åhs Keeper of The Code
All you need is fun Cons T Åhs Keeper of The Code cons@klarna.com Cons T Åhs Keeper of The Code at klarna Architecture - The Big Picture Development - getting ideas to work Code Quality - care about the
Quantitative Analysis of Domain Testing Effectiveness.
East Tennessee State University Digital Commons @ East Tennessee State University Electronic Theses and Dissertations 5-200 Quantitative Analysis of Domain Testing Effectiveness. Narendra Koneru East Tennessee
Toward Architecture-based Reliability Estimation
Toward Architecture-based Estimation Roshanak Roshandel, Nenad Medvidovic Computer Science Department University of Southern California roshande@usc.edu ICSE Workshop on Architecting Dependable System
Software interoperability in consequence assessment: results of a feasibility study
Software interoperability in consequence assessment: results of a feasibility study Sergio Contini 1, Luciano Fabbri 1, Massimo Binda 2 1 European Commission, Joint Research Centre, 21027 Ispra (VA), Italy
Automated Reliability Prediction & Analysis of SwAs
Automated Reliability Prediction & Analysis of SwAs jmfranco [at] dei.uc.pt Postgraduate Colloquium Series 2012 Outline Motivation Main Goal Background Proposed Approach Experiments & Validation Conclusions
Wentworth Institute of Technology COMP2670 Databases Spring 2016 Derbinsky. Normalization. Lecture 9
Lecture 9 1 Outline 1. Context 2. Objectives 3. Functional Dependencies 4. Normal Forms 1NF 2NF 3NF 2 Database Design and Implementation Process 3 Theory and process by which to evaluate and improve relational
Using System Center 2012 Configuration Manager - Part 2. Install the primary server - P01
Using System Center 2012 Configuration Manager - Part 2. Install the primary server - P01 In Part 1 of this series we created our new LAB, we got the System Center 2012 Configuration Manager ISO and extracted
Practitioner Certificate in Business Continuity Management (PCBCM) Course Description. 10 th December, 2015 Version 2.0
Practitioner Certificate in Business Continuity Management (PCBCM) Course Description 10 th December, 2015 Version 2.0 Course The Practitioner Certificate in Business Continuity Management (PCBCM) course
Verification and Validation
Steven Zeil February 13, 2013 Contents 1 The Process 3 1 2 Non-Testing V&V 7 2.1 Code Review....... 8 2.2 Mathematically-based verification......................... 19 2.3 Static analysis tools... 23 2.4
Verification and Validation
Steven Zeil February 13, 2013 Contents 1 The Process 2 2 Non-Testing V&V 3 2.1 Code Review........... 4 2.2 Mathematically-based verification.................................. 8 2.3 Static analysis tools.......
Accelerating Data Center Virtualization with Cisco Services. Mark Milinkovich Director, WWTP Advanced Services, Data Center
Accelerating Data Center Virtualization with Cisco Services Mark Milinkovich Director, WWTP Advanced Services, Data Center 1 Data Center Services Capabilities Architecture Application Operations & Management
CS154, Lecture 18: 1
CS154, Lecture 18: 1 CS 154 Final Exam Wednesday December 13, 12:15-3:15 pm Skilling Auditorium You re allowed one double-sided sheet of notes Exam is comprehensive (but will emphasize post-midterm topics)
CIP-014. JEA Compliance Approach. FRCC Fall Compliance Workshop Presenter Daniel Mishra
CIP-014 JEA Compliance Approach FRCC Fall Compliance Workshop Presenter Daniel Mishra Acronyms & Terminologies DHS Department of Homeland Security JEA It s not an acronym JSO Jacksonville Sheriff's Office
DEVELOP YOUR TAILORED CYBERSECURITY ROADMAP
ARINC cybersecurity solutions DEVELOP YOUR TAILORED CYBERSECURITY ROADMAP Getting started is as simple as assessing your baseline THE RIGHT CYBERSECURITY SOLUTIONS FOR YOUR UNIQUE NEEDS Comprehensive threat
ECE380 Digital Logic
ECE38 Digital Logic Optimized Implementation of Logic Functions: Strategy for Minimization, Minimum Product-of-Sums Forms, Incompletely Specified Functions Dr. D. J. Jackson Lecture 8- Terminology For
Call for Papers GCC POWER 2011 GCC Cigre s Leading Electric Power Conference & Exhibition In the Gulf Region
Call for Papers GCC POWER 2011 GCC Cigre s Leading Electric Power Conference & Exhibition In the Gulf Region Kuwait - November 2011 GCC Cigre, is pleased to announce its 7 th International Conference GCC
Department of Electrical & Computer Engineering, University of Calgary. B.H. Far
SENG 421: Software Metrics Software Test Metrics (Chapter 10) Department of Electrical & Computer Engineering, University of Calgary B.H. Far (far@ucalgary.ca) http://www.enel.ucalgary.ca/people/far/lectures/seng421/10/
Developing MapReduce Programs
Cloud Computing Developing MapReduce Programs Dell Zhang Birkbeck, University of London 2017/18 MapReduce Algorithm Design MapReduce: Recap Programmers must specify two functions: map (k, v) * Takes
AADL Fault Modeling and Analysis Within an ARP4761 Safety Assessment
AADL Fault Modeling and Analysis Within an ARP4761 Safety Assessment Julien Delange Peter Feiler David P. Gluch John Hudak October 2014 TECHNICAL REPORT CMU/SEI-2014-TR-020 Software Solutions Division
Operations Research and Optimization: A Primer
Operations Research and Optimization: A Primer Ron Rardin, PhD NSF Program Director, Operations Research and Service Enterprise Engineering also Professor of Industrial Engineering, Purdue University Introduction
By V-cubed Solutions, Inc. Page1. All rights reserved by V-cubed Solutions, Inc.
By V-cubed Solutions, Inc. Page1 Purpose of Document This document will demonstrate the efficacy of CODESCROLL CODE INSPECTOR, CONTROLLER TESTER, and QUALITYSCROLL COVER, which has been developed by V-cubed
Network Analysis. Links, nodes, trees, graphs, paths and cycles what does it all mean? Minimal spanning tree shortest route maximum flow
Network Analysis Minimal spanning tree shortest route maximum flow Links, nodes, trees, graphs, paths and cycles what does it all mean? Real OR in action! 1 Network Terminology Graph - set of points (nodes)
O&M Service for Sustainable Social Infrastructure
O&M Service for Sustainable Social Infrastructure Hitachi Review Vol. 62 (2013), No. 7 370 Toshiyuki Moritsu, Ph. D. Takahiro Fujishiro, Ph. D. Katsuya Koda Tatsuya Kutsuna OVERVIEW: Hitachi is developing
Zero Recovery Silicon Carbide Schottky Diode
MSC010SDA070K Datasheet Zero Recovery Silicon Carbide Schottky Diode Final December 2017 Contents 1 Revision History... 1 1.1 Revision A... 1 2 Product Overview... 2 2.1 Features... 2 2.2 Benefits... 2
Workshop on Threat Assessment and Design Basis Threat (DBT) Session 6 Developing and Maintaining a DBT
Workshop on Threat Assessment and Design Basis Threat (DBT) Session 6 Developing and Maintaining a DBT Based on Chapter 6 of the IAEA Nuclear Security Series No.10 Implementing Guide Developing a DBT Learning
IO2654 Optical Networking. WDM network design. Lena Wosinska KTH/ICT. The aim of the next two lectures. To introduce some new definitions
IO2654 Optical Networking WDM network design Lena Wosinska KTH/ICT 1 The aim of the next two lectures To introduce some new definitions To make you aware about the trade-offs for WDM network design To
XML Query Processing. Announcements (March 31) Overview. CPS 216 Advanced Database Systems. Course project milestone 2 due today
XML Query Processing CPS 216 Advanced Database Systems Announcements (March 31) 2 Course project milestone 2 due today Hardcopy in class or otherwise email please I will be out of town next week No class
Monte Carlo Simulations
Monte Carlo Simulations DESCRIPTION AND APPLICATION Outline Introduction Description of Method Cost Estimating Example Other Considerations Introduction Most interesting things are probabilistic (opinion)
Top 10 ICS Cybersecurity Problems Observed in Critical Infrastructure
SESSION ID: SBX1-R07 Top 10 ICS Cybersecurity Problems Observed in Critical Infrastructure Bryan Hatton Cyber Security Researcher Idaho National Laboratory In support of DHS ICS-CERT @phaktor 16 Critical
(Refer Slide Time 04:53)
Programming and Data Structure Dr.P.P.Chakraborty Department of Computer Science and Engineering Indian Institute of Technology, Kharagpur Lecture 26 Algorithm Design -1 Having made a preliminary study
Contingency Planning and Disaster Recovery
Contingency Planning and Disaster Recovery Best Practices Version: 7.2.x Written by: Product Knowledge, R&D Date: April 2017 2017 Lexmark. All rights reserved. Lexmark is a trademark of Lexmark International
A new interfacing approach between level 1 and level 2 PSA
A new interfacing approach between level 1 and level 2 PSA Nicolas Duflot a, Nadia Rahni a, Thomas Durin a, Yves Guigueno a and Emmanuel Raimond a a IRSN, Fontenay aux Roses, France Abstract: IRSN (TSO
Rich Vehicle Routing Problems Challenges and Prospects in Exploring the Power of Parallelism. Andreas Reinholz. 1 st COLLAB Workshop
Collaborative Research Center SFB559 Modeling of Large Logistic Networks Project M8 - Optimization Rich Vehicle Routing Problems Challenges and Prospects in Exploring the Power of Parallelism Andreas Reinholz
HW/SW Codesign. WCET Analysis
HW/SW Codesign WCET Analysis 29 November 2017 Andres Gomez gomeza@tik.ee.ethz.ch 1 Outline Today s exercise is one long question with several parts: Basic blocks of a program Static value analysis WCET
Remote Procedure Call. Tom Anderson
Remote Procedure Call Tom Anderson Why Are Distributed Systems Hard? Asynchrony Different nodes run at different speeds Messages can be unpredictably, arbitrarily delayed Failures (partial and ambiguous)
Workstation Cluster. AVACS S3 Phase 2. July 28, 2011
Workstation Cluster AVACS S3 Phase 2 July 28, 2011 1 Description of the Model In this test case, we consider the dependability of a fault-tolerant workstation cluster [5]. Notably, we consider a finite-state
Software Maintenance. Maintenance is Inevitable. Types of Maintenance. Managing the processes of system change
Software Maintenance Managing the processes of system change Maintenance is Inevitable The system requirements are likely to change while the system is being developed because the environment is changing.
Fault tolerance and Reliability
Fault tolerance and Reliability Reliability measures Fault tolerance in a switching system Modeling of fault tolerance and reliability Rka -k2002 Telecommunication Switching Technology 14-1 Summary of
Event-tree analysis using binary decision diagrams
Loughborough University Institutional Repository Event-tree analysis using binary decision diagrams This item was submitted to Loughborough University's Institutional Repository by the/an author. Citation:
DATA ITEM DESCRIPTION
DATA ITEM DESCRIPTION Title: RELIABILITY AND MAINTAINABILITY (R&M) BLOCK DIAGRAMS AND MATHEMATICAL MODELS REPORT Number: DI-SESS-81496A Approval Date: 20141219 AMSC Number: 9508 Limitation: No DTIC Applicable:
Software Testing and Maintenance 1
Combinatorial Testing!! Introduction!! Combinatorial Coverage Criteria!! Pairwise Test Generation!! Summary Software Testing and Maintenance 1 Motivation!! The behavior of a software application may be
ECE/CS 541: COMPUTER SYSTEMS ANALYSIS. Homework #4 Due Tuesday, October 6, 2009
ECE/CS 541: COMPUTER SYSTEMS ANALYSIS Homework #4 Due Tuesday, October 6, 2009 The goals of this exercise are for you to become familiar with the mechanics of modeling using Möbius and analysis of systems
Contract-based design, model checking, and model-based safety assessment
Contract-based design, model checking, and model-based safety assessment An integrated view Alessandro Cimatti Fondazione Bruno Kessler, Trento, Italy Take away message Beyond model checking: new generation
Mathematical Programming Formulations, Constraint Programming
Outline DM87 SCHEDULING, TIMETABLING AND ROUTING Lecture 3 Mathematical Programming Formulations, Constraint Programming 1. Special Purpose Algorithms 2. Constraint Programming Marco Chiarandini DM87 Scheduling,
Commissioning Mission Critical Facilities
Commissioning Mission Critical Facilities HH Angus and Associates Limited Consulting Engineers 1127 Leslie Street Toronto, ON M3C 2J6 416 443 8200 info@hhangus.com www.hhangus.com Commissioning Mission
Using Fuzzy Arithmetic in Containment Event Trees
Volver Using Fuzzy Arithmetic in Containment Event Trees Rivera, S.S. and Baron, J.H. Presentado en: nternational Conference on Probabilistic Safety Assessment- PSA 99, Washington, USA, 22-25 agosto 999
Chapter 14. Chapter 14 - Objectives. Purpose of Normalization. Purpose of Normalization
Chapter 14 - Objectives Chapter 14 Normalization The purpose of normalization. How normalization can be used when designing a relational database. The potential problems associated with redundant data
Transport Layer Congestion Control
Transport Layer Congestion Control Tom Kelliher, CS 325 Apr. 7, 2008 1 Administrivia Announcements Assignment Read 4.1 4.3. From Last Time TCP Reliability. Outline 1. Congestion control principles. 2.
ΕΠΛ323 - Θεωρία και Πρακτική Μεταγλωττιστών
ΕΠΛ323 - Θεωρία και Πρακτική Μεταγλωττιστών Lecture 5b Syntax Analysis Elias Athanasopoulos eliasathan@cs.ucy.ac.cy Regular Expressions vs Context-Free Grammars Grammar for the regular expression (a b)*abb
Network Survivability Performance Evaluation with Applications in WDM Networks with Wavelength Conversion
Network Survivability Performance Evaluation with Applications in WDM Networks with Wavelength Conversion Manijeh Keshtgary, Fahad A. Al-Zahrani, Anura P. Jayasumana Electrical and Computer Engineering
Aerospace Software Engineering
16.35 Aerospace Software Engineering Reliability, Availability, and Maintainability Software Fault Tolerance Prof. Kristina Lundqvist Dept. of Aero/Astro, MIT Definitions Software reliability The probability
PESIT Bangalore South Campus
PESIT Bangalore South Campus Hosur road, 1km before Electronic City, Bengaluru -100 Department of Information Science & Engineering SOLUTION MANUAL INTERNAL ASSESSMENT TEST 1 Subject & Code : Storage Area
CSE 544 Principles of Database Management Systems. Magdalena Balazinska Winter 2009 Lecture 4 - Schema Normalization
CSE 544 Principles of Database Management Systems Magdalena Balazinska Winter 2009 Lecture 4 - Schema Normalization References R&G Book. Chapter 19: Schema refinement and normal forms Also relevant to
Parnas Tables: A Practical Formalism. Joanne M. Atlee Department of Computer Science University of Waterloo
Parnas Tables: A Practical Formalism Joanne M. Atlee Department of Computer Science University of Waterloo Critical Software Medical Devices Transportation Telecommunications Automated Manufacturing Software
CSE 124: QUANTIFYING PERFORMANCE AT SCALE AND COURSE REVIEW. George Porter December 6, 2017
CSE 124: QUANTIFYING PERFORMANCE AT SCALE AND COURSE REVIEW George Porter December 6, 2017 ATTRIBUTION These slides are released under an Attribution-NonCommercial-ShareAlike 3.0 Unported (CC BY-NC-SA
Photo-realistic Renderings for Machines Seong-heum Kim
Photo-realistic Renderings for Machines 20105034 Seong-heum Kim CS580 Student Presentations 2016.04.28 Photo-realistic Renderings for Machines Scene radiances Model descriptions (Light, Shape, Material,
Navy Cyber Resilience
Unclassified Navy Cyber Resilience 20160614 Mr. Troy Johnson From cybersecurity to cyber resilience 2 Disconnected response through stove-piped assessments & initiatives across the enterprise: Operation
Checklist for Requirements Specification Reviews
Checklist for Requirements Specification Reviews Organization and Completeness o Are all internal cross-references to other requirements correct? o Are all requirements written at a consistent and appropriate