Here I am. Modeling and Verification of Real Time and Embedded Systems. TIMES: UPPAAL: Main Goal of the tutorial

Size: px
Start display at page:

Download "Here I am. Modeling and Verification of Real Time and Embedded Systems. TIMES: UPPAAL: Main Goal of the tutorial"

Transcription

1 Here I m Uppsl (university city) Stockholm Modeling nd Verifiction of Rel Time nd Emedded Systems A tutoril on UPPAAL Wng Yi Uppsl University, Sweden, 2005 UPPAAL: A model checker for rel time systems developed jointly y Uppsl university nd Alorg university since 199 UPPsl + AALorg = UPPAAL SWEDEN + DENMARK = SWEDEN SWEDEN + DENMARK = DENMARK TIMES: Extended version of UPPAAL, towrds tool environment for the complete system development process: from design to implementtion TIMES = Tool for Modeling nd Implemention of Emedded Systems Min Gol of the tutoril Wht is inside the tools UPPAAL TIMES Trditionl softwre development Prolem Are Anlysis REVIEWS The Wterfll Model Design Errors re detected lte or never: 0-50% of time for testing Errors detected: the lte the more expensive Implementtion Testing REVIEWS Running System

2 Introducing, Detecting nd Correcting errors Finding errors s erly s possile! HOW? A simplified version of fieled us protocol Rechle? Exmple: Fischer s Protocol 8 V Criticil Section V:=1 V=1 A1 B1 CS1 V:=2 V=2 A2 B2 CS2 Exmple: Fischer s Protocol Exmple: Petersson s lgorithm Init x=y=0 8 V Criticil Section X<100 X:=0 X>100 V:=1 V=1 A1 B1 CS1 Y<100 Y:=0 Y>100 V:=2 V=2 A2 B2 CS2 turn, flg1, flg2: shred vriles Process 1 Process 2 Loop Loop flg1:=1; turn:=2 flg2:=1; turn:=1 While (flg2 nd turn=2) wit While (flg1 nd turn=1) wit CS1 CS2 flg1:=0 flg2:=0 End loop End loop Question: no more thn one process run in CS?

3 Exmple: the Soldiers Prolem Rel time scheduling UPPAAL = UPPsl + AALorg A tool set for modelling nd verifiction of rel-time systems developed jointly y Uppsl nd Alorg University UNSAFE At At most 2 crossing t t time time Torch Need torch SAFE Mines Wht Cn Wht is Cn they is the the shortest they mke shortesttime time for for getting getting ll ll soldiers soldiers on on the the it it within sfe minutes? sfe side side? System Model A network of timed utomt Question Q (Requirement) UPPAAL No! Deugging Informtion Yes Deugging Informtion Prototypes Executle Code TIMES will do this for you! Model Checking in Nutshell MODELING How to construct Model? Modeling = progrmming+strction Progrm s Stte Mchine! Construction of Models: Concurrency Plnt Continuous sensors Controller Progrm Discrete Input ports y!?? X! Control sttes x y Output ports Model of environment (user-supplied) c c ctutors Tsk Tsk Tsk Tsk UPPAAL Model c Model of tsks (utomtic)

4 Modeling in UPPAAL: Exmple P1 P1 :: :: while True do do T1 T1 : wit(turn=1) C1 C1 : CS1; turn:=0 P2 P2 :: :: while True do do T2 T2 : wit(turn=0) C2 C2 : CS2; turn:=1 Mutul Exclusion Progrm Specifiction=Requirement, Lmport 1977 SPECIFICATION How to sk questions: Specs? Sfety Something (d) will not hppen Liveness Something (good) must hppen Relizility (Schedulility) Specifiction=Requirement, Lmport 1977 Sfety Something (d) will not hppen Liveness Something (good) must hppen Relizility (Schedulility etc) Cn we implement the specs with given resources? Specifiction: Exmples AG not (CS1 nd CS2) never CS1 nd CS2 Sfety property AG ( <=10 ) if then within 10 Bounded liveness property EF p.test Useful for deugging EF flse Generte the whole stte spce Report dedlocks etc. AG (try => AF criticl-section) (liveness)

5 Verifiction VERIFICATION Model meets Specs? Semntics of system = ll sttes + stte trnsitions (ll possile executions) Verifiction = stte spce explortion + exmintion Verifictioin = Serching Two sic verifiction lgorithms A Stte-Spce of Progrm Rechility nlysis Checking sfety properties Loop detection Checking liveness properties B : : : : (1) Is it possile to fire the oms? (2) Is it possile to go from A to B within 10 sec? Modelling in UPPAAL: exmple Verifiction: exmple P1 P1 :: :: while True do do T1 T1 : wit(turn=1) C1 C1 : CS1; turn:=0 P2 P2 :: :: while True do do T2 T2 : wit(turn=0) C2 C2 : CS2; turn:=1 T1 I2 I1 I2 T1 T2 I1 T2 I1 C2 C1 I2 T1 I2 I1 I2 T1 T2 I1 T2 Mutul Exclusion Progrm Is it possile tht P1 nd P2 rech C1 nd C2 simultneously? T1 C2 (C1 C2) is never rechle! C1 T2

6 Prolem with verifiction: Stte Explosion EXAMPLE M1 1 2 M2 10 components nd ech with10 sttes M1 x M2 1,,,, c 1, 2,,, All comintions = exponentil in no. of components 1,c 2,c,c,c Provly theoreticl intrctle # of control sttes = 10,000,000,000 =10 G Ech stte needs *(10 x 10) = 00 B Worst cse memory usge >> 000 GB Solutions Symolic Techniques: Compute Sets of Sttes insted of one-y-one Theorem provers Symolic Techniques e.g. BDD [Brynt 86] Astrction techniques [Cosot nd Cosot] Approximtion methods [Holzmn, Wng-Toi...] On-the-fly verifiction [Holzmn] Prtil order reduction [Wolper et l] Compositionl verifiction [too mny] Comining theorem provers nd model checkers Use formuls to represent sets of sttes Compute the fixed point Strt Initil set... Overlp with d sttes or Converge (fixed point)... Converge! Or fire the oms A Protocol y Philips for Audio Products -6 months for mnul proof in hours for Hytech in sec for Uppl in sec for Uppl now! Every 9 month 10 times etter performnce! End of INTRODUCTION Dec 96 Sep 98

7 OUTLINE Introduction Lecture 1: Motivtion, exmples, prolems to solve Modeling nd Veriction of Timed Systems Lecture 2: Timed utomt, nd timed utomt in UPPAAL Lecture : Symolic verifiction: the core of UPPAAL Lecture : Verifiction Options in UPPAAL nd/or Demo Towrds Unified Frmework Lecture 5: Modeling, verifiction, rel time scheduling, code synthesis From UPPAAL to TIMES

One Minute To Learn Programming: Finite Automata

One Minute To Learn Programming: Finite Automata Gret Theoreticl Ides In Computer Science Steven Rudich CS 15-251 Spring 2005 Lecture 9 Fe 8 2005 Crnegie Mellon University One Minute To Lern Progrmming: Finite Automt Let me tech you progrmming lnguge

More information

Homework 3 Solutions

Homework 3 Solutions CS 341: Foundtions of Computer Science II Prof. Mrvin Nkym Homework 3 Solutions 1. Give NFAs with the specified numer of sttes recognizing ech of the following lnguges. In ll cses, the lphet is Σ = {,1}.

More information

Outline of the Lecture. Software Testing. Unit & Integration Testing. Components. Lecture Notes 3 (of 4)

Outline of the Lecture. Software Testing. Unit & Integration Testing. Components. Lecture Notes 3 (of 4) Outline of the Lecture Softwre Testing Lecture Notes 3 (of 4) Integrtion Testing Top-down ottom-up ig-ng Sndwich System Testing cceptnce Testing istriution of ults in lrge Industril Softwre System (ISST

More information

Reasoning to Solve Equations and Inequalities

Reasoning to Solve Equations and Inequalities Lesson4 Resoning to Solve Equtions nd Inequlities In erlier work in this unit, you modeled situtions with severl vriles nd equtions. For exmple, suppose you were given usiness plns for concert showing

More information

Model Checking for Software Architectures

Model Checking for Software Architectures Model Checking for Softwre Architectures position pper Rdu Mteescu INRIA Rhône-Alpes / VASY 655, venue de l Europe F-38330 Montbonnot Sint Mrtin http://www.inrilpes.fr/vsy 1 Outline Introduction Constructing

More information

Engineer-to-Engineer Note

Engineer-to-Engineer Note Engineer-to-Engineer Note EE-265 Technicl notes on using Anlog Devices DSPs, processors nd development tools Contct our technicl support t dsp.support@nlog.com nd t dsptools.support@nlog.com Or visit our

More information

Bypassing Space Explosion in Regular Expression Matching for Network Intrusion Detection and Prevention Systems

Bypassing Space Explosion in Regular Expression Matching for Network Intrusion Detection and Prevention Systems Bypssing Spce Explosion in Regulr Expression Mtching for Network Intrusion Detection n Prevention Systems Jignesh Ptel, Alex Liu n Eric Torng Dept. of Computer Science n Engineering Michign Stte University

More information

Assumption Generation for Software Component Verification

Assumption Generation for Software Component Verification Assumption Genertion for Softwre Component Verifiction Dimitr Ginnkopoulou Corin S. Păsărenu RIACS/USRA Kestrel Technologies LLC NASA Ames Reserch Center Moffett Field, CA 94035-1000, USA {dimitr, pcorin}@emil.rc.ns.gov

More information

Welch Allyn CardioPerfect Workstation Installation Guide

Welch Allyn CardioPerfect Workstation Installation Guide Welch Allyn CrdioPerfect Worksttion Instlltion Guide INSTALLING CARDIOPERFECT WORKSTATION SOFTWARE & ACCESSORIES ON A SINGLE PC For softwre version 1.6.5 or lter For network instlltion, plese refer to

More information

Appendix D: Completing the Square and the Quadratic Formula. In Appendix A, two special cases of expanding brackets were considered:

Appendix D: Completing the Square and the Quadratic Formula. In Appendix A, two special cases of expanding brackets were considered: Appendi D: Completing the Squre nd the Qudrtic Formul Fctoring qudrtic epressions such s: + 6 + 8 ws one of the topics introduced in Appendi C. Fctoring qudrtic epressions is useful skill tht cn help you

More information

Protocol Analysis. 17-654/17-764 Analysis of Software Artifacts Kevin Bierhoff

Protocol Analysis. 17-654/17-764 Analysis of Software Artifacts Kevin Bierhoff Protocol Anlysis 17-654/17-764 Anlysis of Softwre Artifcts Kevin Bierhoff Tke-Awys Protocols define temporl ordering of events Cn often be cptured with stte mchines Protocol nlysis needs to py ttention

More information

Polynomial Functions. Polynomial functions in one variable can be written in expanded form as ( )

Polynomial Functions. Polynomial functions in one variable can be written in expanded form as ( ) Polynomil Functions Polynomil functions in one vrible cn be written in expnded form s n n 1 n 2 2 f x = x + x + x + + x + x+ n n 1 n 2 2 1 0 Exmples of polynomils in expnded form re nd 3 8 7 4 = 5 4 +

More information

Regular Sets and Expressions

Regular Sets and Expressions Regulr Sets nd Expressions Finite utomt re importnt in science, mthemtics, nd engineering. Engineers like them ecuse they re super models for circuits (And, since the dvent of VLSI systems sometimes finite

More information

Modular Generic Verification of LTL Properties for Aspects

Modular Generic Verification of LTL Properties for Aspects Modulr Generic Verifiction of LTL Properties for Aspects Mx Goldmn Shmuel Ktz Computer Science Deprtment Technion Isrel Institute of Technology {mgoldmn, ktz}@cs.technion.c.il ABSTRACT Aspects re seprte

More information

Firm Objectives. The Theory of the Firm II. Cost Minimization Mathematical Approach. First order conditions. Cost Minimization Graphical Approach

Firm Objectives. The Theory of the Firm II. Cost Minimization Mathematical Approach. First order conditions. Cost Minimization Graphical Approach Pro. Jy Bhttchry Spring 200 The Theory o the Firm II st lecture we covered: production unctions Tody: Cost minimiztion Firm s supply under cost minimiztion Short vs. long run cost curves Firm Ojectives

More information

Generating In-Line Monitors For Rabin Automata

Generating In-Line Monitors For Rabin Automata Generting In-Line Monitors For Rin Automt Hugues Chot, Rphel Khoury, nd Ndi Twi Lvl University, Deprtment of Computer Science nd Softwre Engineering, Pvillon Adrien-Pouliot, 1065, venue de l Medecine Queec

More information

Binary Representation of Numbers Autar Kaw

Binary Representation of Numbers Autar Kaw Binry Representtion of Numbers Autr Kw After reding this chpter, you should be ble to: 1. convert bse- rel number to its binry representtion,. convert binry number to n equivlent bse- number. In everydy

More information

Bayesian Updating with Continuous Priors Class 13, 18.05, Spring 2014 Jeremy Orloff and Jonathan Bloom

Bayesian Updating with Continuous Priors Class 13, 18.05, Spring 2014 Jeremy Orloff and Jonathan Bloom Byesin Updting with Continuous Priors Clss 3, 8.05, Spring 04 Jeremy Orloff nd Jonthn Bloom Lerning Gols. Understnd prmeterized fmily of distriutions s representing continuous rnge of hypotheses for the

More information

Enterprise Risk Management Software Buyer s Guide

Enterprise Risk Management Software Buyer s Guide Enterprise Risk Mngement Softwre Buyer s Guide 1. Wht is Enterprise Risk Mngement? 2. Gols of n ERM Progrm 3. Why Implement ERM 4. Steps to Implementing Successful ERM Progrm 5. Key Performnce Indictors

More information

flex Regular Expressions and Lexical Scanning Regular Expressions and flex Examples on Alphabet A = {a,b} (Standard) Regular Expressions on Alphabet A

flex Regular Expressions and Lexical Scanning Regular Expressions and flex Examples on Alphabet A = {a,b} (Standard) Regular Expressions on Alphabet A flex Regulr Expressions nd Lexicl Scnning Using flex to Build Scnner flex genertes lexicl scnners: progrms tht discover tokens. Tokens re the smllest meningful units of progrm (or other string). flex is

More information

Automated Grading of DFA Constructions

Automated Grading of DFA Constructions Automted Grding of DFA Constructions Rjeev Alur nd Loris D Antoni Sumit Gulwni Dileep Kini nd Mhesh Viswnthn Deprtment of Computer Science Microsoft Reserch Deprtment of Computer Science University of

More information

Lecture 5. Inner Product

Lecture 5. Inner Product Lecture 5 Inner Product Let us strt with the following problem. Given point P R nd line L R, how cn we find the point on the line closest to P? Answer: Drw line segment from P meeting the line in right

More information

FAULT TREES AND RELIABILITY BLOCK DIAGRAMS. Harry G. Kwatny. Department of Mechanical Engineering & Mechanics Drexel University

FAULT TREES AND RELIABILITY BLOCK DIAGRAMS. Harry G. Kwatny. Department of Mechanical Engineering & Mechanics Drexel University SYSTEM FAULT AND Hrry G. Kwtny Deprtment of Mechnicl Engineering & Mechnics Drexel University OUTLINE SYSTEM RBD Definition RBDs nd Fult Trees System Structure Structure Functions Pths nd Cutsets Reliility

More information

Example A rectangular box without lid is to be made from a square cardboard of sides 18 cm by cutting equal squares from each corner and then folding

Example A rectangular box without lid is to be made from a square cardboard of sides 18 cm by cutting equal squares from each corner and then folding 1 Exmple A rectngulr box without lid is to be mde from squre crdbord of sides 18 cm by cutting equl squres from ech corner nd then folding up the sides. 1 Exmple A rectngulr box without lid is to be mde

More information

Example 27.1 Draw a Venn diagram to show the relationship between counting numbers, whole numbers, integers, and rational numbers.

Example 27.1 Draw a Venn diagram to show the relationship between counting numbers, whole numbers, integers, and rational numbers. 2 Rtionl Numbers Integers such s 5 were importnt when solving the eqution x+5 = 0. In similr wy, frctions re importnt for solving equtions like 2x = 1. Wht bout equtions like 2x + 1 = 0? Equtions of this

More information

Java CUP. Java CUP Specifications. User Code Additions You may define Java code to be included within the generated parser:

Java CUP. Java CUP Specifications. User Code Additions You may define Java code to be included within the generated parser: Jv CUP Jv CUP is prser-genertion tool, similr to Ycc. CUP uilds Jv prser for LALR(1) grmmrs from production rules nd ssocited Jv code frgments. When prticulr production is recognized, its ssocited code

More information

Vectors 2. 1. Recap of vectors

Vectors 2. 1. Recap of vectors Vectors 2. Recp of vectors Vectors re directed line segments - they cn be represented in component form or by direction nd mgnitude. We cn use trigonometry nd Pythgors theorem to switch between the forms

More information

Test Management using Telelogic DOORS. Francisco López Telelogic DOORS Specialist

Test Management using Telelogic DOORS. Francisco López Telelogic DOORS Specialist Test Mngement using Telelogic DOORS Frncisco López Telelogic DOORS Specilist Introduction Telelogic solution for Requirements Mngement DOORS Requirements mngement nd trcebility pltform for complex systems

More information

Pointed Regular Expressions

Pointed Regular Expressions Pointed Regulr Expressions Andre Asperti 1, Cludio Scerdoti Coen 1, nd Enrico Tssi 2 1 Deprtment of Computer Science, University of Bologn sperti@cs.unio.it scerdot@cs.unio.it 2 INRIA-Micorsoft tssi@cs.unio.it

More information

CS99S Laboratory 2 Preparation Copyright W. J. Dally 2001 October 1, 2001

CS99S Laboratory 2 Preparation Copyright W. J. Dally 2001 October 1, 2001 CS99S Lortory 2 Preprtion Copyright W. J. Dlly 2 Octoer, 2 Ojectives:. Understnd the principle of sttic CMOS gte circuits 2. Build simple logic gtes from MOS trnsistors 3. Evlute these gtes to oserve logic

More information

. At first sight a! b seems an unwieldy formula but use of the following mnemonic will possibly help. a 1 a 2 a 3 a 1 a 2

. At first sight a! b seems an unwieldy formula but use of the following mnemonic will possibly help. a 1 a 2 a 3 a 1 a 2 7 CHAPTER THREE. Cross Product Given two vectors = (,, nd = (,, in R, the cross product of nd written! is defined to e: " = (!,!,! Note! clled cross is VECTOR (unlike which is sclr. Exmple (,, " (4,5,6

More information

Two hours UNIVERSITY OF MANCHESTER SCHOOL OF COMPUTER SCIENCE. Date: Friday 16 th May 2008. Time: 14:00 16:00

Two hours UNIVERSITY OF MANCHESTER SCHOOL OF COMPUTER SCIENCE. Date: Friday 16 th May 2008. Time: 14:00 16:00 COMP20212 Two hours UNIVERSITY OF MANCHESTER SCHOOL OF COMPUTER SCIENCE Digitl Design Techniques Dte: Fridy 16 th My 2008 Time: 14:00 16:00 Plese nswer ny THREE Questions from the FOUR questions provided

More information

ASG Techniques of Adaptivity

ASG Techniques of Adaptivity ASG Techniques of Adptivity Hrld Meyer nd Dominik Kuropk nd Peter Tröger Hsso-Plttner-Institute for IT-Systems-Engineering t the University of Potsdm Prof.-Dr.-Helmert-Strsse 2-3, 14482 Potsdm, Germny

More information

Source Code verification Using Logiscope and CodeReducer. Christophe Peron Principal Consultant Kalimetrix

Source Code verification Using Logiscope and CodeReducer. Christophe Peron Principal Consultant Kalimetrix Source Code verifiction Using Logiscope nd CodeReducer Christophe Peron Principl Consultnt Klimetrix Agend Introducing Logiscope: Improving confidence nd developer s productivity Bsed on stte-of-the-rt

More information

Learning to Search Better than Your Teacher

Learning to Search Better than Your Teacher Ki-Wei Chng University of Illinois t Urbn Chmpign, IL Akshy Krishnmurthy Crnegie Mellon University, Pittsburgh, PA Alekh Agrwl Microsoft Reserch, New York, NY Hl Dumé III University of Mrylnd, College

More information

Techniques for Requirements Gathering and Definition. Kristian Persson Principal Product Specialist

Techniques for Requirements Gathering and Definition. Kristian Persson Principal Product Specialist Techniques for Requirements Gthering nd Definition Kristin Persson Principl Product Specilist Requirements Lifecycle Mngement Elicit nd define business/user requirements Vlidte requirements Anlyze requirements

More information

APPLICATION NOTE Revision 3.0 MTD/PS-0534 August 13, 2008 KODAK IMAGE SENDORS COLOR CORRECTION FOR IMAGE SENSORS

APPLICATION NOTE Revision 3.0 MTD/PS-0534 August 13, 2008 KODAK IMAGE SENDORS COLOR CORRECTION FOR IMAGE SENSORS APPLICATION NOTE Revision 3.0 MTD/PS-0534 August 13, 2008 KODAK IMAGE SENDORS COLOR CORRECTION FOR IMAGE SENSORS TABLE OF FIGURES Figure 1: Spectrl Response of CMOS Imge Sensor...3 Figure 2: Byer CFA Ptterns...4

More information

Concept Formation Using Graph Grammars

Concept Formation Using Graph Grammars Concept Formtion Using Grph Grmmrs Istvn Jonyer, Lwrence B. Holder nd Dine J. Cook Deprtment of Computer Science nd Engineering University of Texs t Arlington Box 19015 (416 Ytes St.), Arlington, TX 76019-0015

More information

How fast can we sort? Sorting. Decision-tree model. Decision-tree for insertion sort Sort a 1, a 2, a 3. CS 3343 -- Spring 2009

How fast can we sort? Sorting. Decision-tree model. Decision-tree for insertion sort Sort a 1, a 2, a 3. CS 3343 -- Spring 2009 CS 4 -- Spring 2009 Sorting Crol Wenk Slides courtesy of Chrles Leiserson with smll chnges by Crol Wenk CS 4 Anlysis of Algorithms 1 How fst cn we sort? All the sorting lgorithms we hve seen so fr re comprison

More information

PROF. BOYAN KOSTADINOV NEW YORK CITY COLLEGE OF TECHNOLOGY, CUNY

PROF. BOYAN KOSTADINOV NEW YORK CITY COLLEGE OF TECHNOLOGY, CUNY MAT 0630 INTERNET RESOURCES, REVIEW OF CONCEPTS AND COMMON MISTAKES PROF. BOYAN KOSTADINOV NEW YORK CITY COLLEGE OF TECHNOLOGY, CUNY Contents 1. ACT Compss Prctice Tests 1 2. Common Mistkes 2 3. Distributive

More information

EQUATIONS OF LINES AND PLANES

EQUATIONS OF LINES AND PLANES EQUATIONS OF LINES AND PLANES MATH 195, SECTION 59 (VIPUL NAIK) Corresponding mteril in the ook: Section 12.5. Wht students should definitely get: Prmetric eqution of line given in point-direction nd twopoint

More information

License Manager Installation and Setup

License Manager Installation and Setup The Network License (concurrent-user) version of e-dpp hs hrdwre key plugged to the computer running the License Mnger softwre. In the e-dpp terminology, this computer is clled the License Mnger Server.

More information

MA 15800 Lesson 16 Notes Summer 2016 Properties of Logarithms. Remember: A logarithm is an exponent! It behaves like an exponent!

MA 15800 Lesson 16 Notes Summer 2016 Properties of Logarithms. Remember: A logarithm is an exponent! It behaves like an exponent! MA 5800 Lesson 6 otes Summer 06 Rememer: A logrithm is n eponent! It ehves like n eponent! In the lst lesson, we discussed four properties of logrithms. ) log 0 ) log ) log log 4) This lesson covers more

More information

Vendor Rating for Service Desk Selection

Vendor Rating for Service Desk Selection Vendor Presented By DATE Using the scores of 0, 1, 2, or 3, plese rte the vendor's presenttion on how well they demonstrted the functionl requirements in the res below. Also consider how efficient nd functionl

More information

Virtual Machine. Part II: Program Control. Building a Modern Computer From First Principles. www.nand2tetris.org

Virtual Machine. Part II: Program Control. Building a Modern Computer From First Principles. www.nand2tetris.org Virtul Mchine Prt II: Progrm Control Building Modern Computer From First Principles www.nnd2tetris.org Elements of Computing Systems, Nisn & Schocken, MIT Press, www.nnd2tetris.org, Chpter 8: Virtul Mchine,

More information

Lec 2: Gates and Logic

Lec 2: Gates and Logic Lec 2: Gtes nd Logic Kvit Bl CS 34, Fll 28 Computer Science Cornell University Announcements Clss newsgroup creted Posted on we-pge Use it for prtner finding First ssignment is to find prtners Due this

More information

Verifying Business Processes using SPIN

Verifying Business Processes using SPIN Verifying Business Proesses using SPIN Wil Jnssen Telemtis Institute (Enshede, The Netherlnds) Rdu Mteesu INRIA Rhône-Alpes / VASY (Montonnot, Frne) Sjouke Muw Eindhoven University of Tehnology (Eindhoven,

More information

Solenoid Operated Proportional Directional Control Valve (with Pressure Compensation, Multiple Valve Series)

Solenoid Operated Proportional Directional Control Valve (with Pressure Compensation, Multiple Valve Series) Solenoid Operted Proportionl Directionl Control Vlve (with Pressure Compenstion, Multiple Vlve Series) Hydrulic circuit (Exmple) v Fetures hese stcking type control vlves show pressure compensted type

More information

Revisions published in the University of Innsbruck Bulletin of 18 June 2014, Issue 31, No. 509

Revisions published in the University of Innsbruck Bulletin of 18 June 2014, Issue 31, No. 509 Plese note: The following curriculum is for informtion purposes only nd not leglly inding. The leglly inding version is pulished in the pertinent University of Innsruck Bulletins. Originl version pulished

More information

In-circuit temporal monitors for runtime verification of reconfigurable designs

In-circuit temporal monitors for runtime verification of reconfigurable designs In-circuit temporl monitors for runtime verifiction of reconfigurble designs Tim Todmn Deprtment of Computing Imperil College London tephn tilkerich Airbus Group Innovtions Willy-Messerschmitt tr., Wyne

More information

How To Network A Smll Business

How To Network A Smll Business Why network is n essentil productivity tool for ny smll business Effective technology is essentil for smll businesses looking to increse the productivity of their people nd processes. Introducing technology

More information

FORMAL LANGUAGES, AUTOMATA AND THEORY OF COMPUTATION EXERCISES ON REGULAR LANGUAGES

FORMAL LANGUAGES, AUTOMATA AND THEORY OF COMPUTATION EXERCISES ON REGULAR LANGUAGES FORMAL LANGUAGES, AUTOMATA AND THEORY OF COMPUTATION EXERCISES ON REGULAR LANGUAGES Introduction This compendium contins exercises out regulr lnguges for the course Forml Lnguges, Automt nd Theory of Computtion

More information

Engineer-to-Engineer Note

Engineer-to-Engineer Note Engineer-to-Engineer Note EE-280 Technicl notes on using Anlog Devices DSPs, processors nd development tools Visit our Web resources http://www.nlog.com/ee-notes nd http://www.nlog.com/processors or e-mil

More information

A Visual and Interactive Input abb Automata. Theory Course with JFLAP 4.0

A Visual and Interactive Input abb Automata. Theory Course with JFLAP 4.0 Strt Puse Step Noninverted Tree A Visul nd Interctive Input Automt String ccepted! 5 nodes generted. Theory Course with JFLAP 4.0 q0 even 's, even 's q2 even 's, odd 's q1 odd 's, even 's q3 odd 's, odd

More information

Advanced Baseline and Release Management. Ed Taekema

Advanced Baseline and Release Management. Ed Taekema Advnced Bseline nd Relese Mngement Ed Tekem Introduction to Bselines Telelogic Synergy uses bselines to perform number of criticl configurtion mngement tsks. They record the stte of the evolving softwre

More information

Small Business Networking

Small Business Networking Why network is n essentil productivity tool for ny smll business Effective technology is essentil for smll businesses looking to increse the productivity of their people nd business. Introducing technology

More information

Graphs on Logarithmic and Semilogarithmic Paper

Graphs on Logarithmic and Semilogarithmic Paper 0CH_PHClter_TMSETE_ 3//00 :3 PM Pge Grphs on Logrithmic nd Semilogrithmic Pper OBJECTIVES When ou hve completed this chpter, ou should be ble to: Mke grphs on logrithmic nd semilogrithmic pper. Grph empiricl

More information

Quick Reference Guide: One-time Account Update

Quick Reference Guide: One-time Account Update Quick Reference Guide: One-time Account Updte How to complete The Quick Reference Guide shows wht existing SingPss users need to do when logging in to the enhnced SingPss service for the first time. 1)

More information

Small Business Networking

Small Business Networking Why network is n essentil productivity tool for ny smll business Effective technology is essentil for smll businesses looking to increse the productivity of their people nd business. Introducing technology

More information

MATH 150 HOMEWORK 4 SOLUTIONS

MATH 150 HOMEWORK 4 SOLUTIONS MATH 150 HOMEWORK 4 SOLUTIONS Section 1.8 Show tht the product of two of the numbers 65 1000 8 2001 + 3 177, 79 1212 9 2399 + 2 2001, nd 24 4493 5 8192 + 7 1777 is nonnegtive. Is your proof constructive

More information

Use Geometry Expressions to create a more complex locus of points. Find evidence for equivalence using Geometry Expressions.

Use Geometry Expressions to create a more complex locus of points. Find evidence for equivalence using Geometry Expressions. Lerning Objectives Loci nd Conics Lesson 3: The Ellipse Level: Preclculus Time required: 120 minutes In this lesson, students will generlize their knowledge of the circle to the ellipse. The prmetric nd

More information

P.3 Polynomials and Factoring. P.3 an 1. Polynomial STUDY TIP. Example 1 Writing Polynomials in Standard Form. What you should learn

P.3 Polynomials and Factoring. P.3 an 1. Polynomial STUDY TIP. Example 1 Writing Polynomials in Standard Form. What you should learn 33337_0P03.qp 2/27/06 24 9:3 AM Chpter P Pge 24 Prerequisites P.3 Polynomils nd Fctoring Wht you should lern Polynomils An lgeric epression is collection of vriles nd rel numers. The most common type of

More information

An Undergraduate Curriculum Evaluation with the Analytic Hierarchy Process

An Undergraduate Curriculum Evaluation with the Analytic Hierarchy Process An Undergrdute Curriculum Evlution with the Anlytic Hierrchy Process Les Frir Jessic O. Mtson Jck E. Mtson Deprtment of Industril Engineering P.O. Box 870288 University of Albm Tuscloos, AL. 35487 Abstrct

More information

Learning Workflow Petri Nets

Learning Workflow Petri Nets Lerning Workflow Petri Nets Jvier Esprz, Mrtin Leucker, nd Mximilin Schlund Technische Universität München, Boltzmnnstr. 3, 85748 Grching, Germny {esprz,leucker,schlund}@in.tum.de Abstrct. Workflow mining

More information

Lecture 3 Gaussian Probability Distribution

Lecture 3 Gaussian Probability Distribution Lecture 3 Gussin Probbility Distribution Introduction l Gussin probbility distribution is perhps the most used distribution in ll of science. u lso clled bell shped curve or norml distribution l Unlike

More information

Small Business Networking

Small Business Networking Why network is n essentil productivity tool for ny smll business Effective technology is essentil for smll businesses looking to increse the productivity of their people nd processes. Introducing technology

More information

Section 5.2, Commands for Configuring ISDN Protocols. Section 5.3, Configuring ISDN Signaling. Section 5.4, Configuring ISDN LAPD and Call Control

Section 5.2, Commands for Configuring ISDN Protocols. Section 5.3, Configuring ISDN Signaling. Section 5.4, Configuring ISDN LAPD and Call Control Chpter 5 Configurtion of ISDN Protocols This chpter provides instructions for configuring the ISDN protocols in the SP201 for signling conversion. Use the sections tht reflect the softwre you re configuring.

More information

Brillouin Zones. Physics 3P41 Chris Wiebe

Brillouin Zones. Physics 3P41 Chris Wiebe Brillouin Zones Physics 3P41 Chris Wiebe Direct spce to reciprocl spce * = 2 i j πδ ij Rel (direct) spce Reciprocl spce Note: The rel spce nd reciprocl spce vectors re not necessrily in the sme direction

More information

SINCLAIR COMMUNITY COLLEGE DAYTON, OHIO DEPARTMENT SYLLABUS FOR COURSE IN MAT 1470 - COLLEGE ALGEBRA (4 SEMESTER HOURS)

SINCLAIR COMMUNITY COLLEGE DAYTON, OHIO DEPARTMENT SYLLABUS FOR COURSE IN MAT 1470 - COLLEGE ALGEBRA (4 SEMESTER HOURS) SINCLAIR COMMUNITY COLLEGE DAYTON, OHIO DEPARTMENT SYLLABUS FOR COURSE IN MAT 470 - COLLEGE ALGEBRA (4 SEMESTER HOURS). COURSE DESCRIPTION: Polynomil, rdicl, rtionl, exponentil, nd logrithmic functions

More information

Hillsborough Township Public Schools Mathematics Department Computer Programming 1

Hillsborough Township Public Schools Mathematics Department Computer Programming 1 Essentil Unit 1 Introduction to Progrmming Pcing: 15 dys Common Unit Test Wht re the ethicl implictions for ming in tody s world? There re ethicl responsibilities to consider when writing computer s. Citizenship,

More information

Small Business Networking

Small Business Networking Why network is n essentil productivity tool for ny smll business Effective technology is essentil for smll businesses looking to increse the productivity of their people nd processes. Introducing technology

More information

Integration by Substitution

Integration by Substitution Integrtion by Substitution Dr. Philippe B. Lvl Kennesw Stte University August, 8 Abstrct This hndout contins mteril on very importnt integrtion method clled integrtion by substitution. Substitution is

More information

APPLYING FORMAL METHODS TO CRYPTOGRAPHIC PROTOCOL ANALYSIS: EMERGING ISSUES AND TRENDS

APPLYING FORMAL METHODS TO CRYPTOGRAPHIC PROTOCOL ANALYSIS: EMERGING ISSUES AND TRENDS PPLYING FORML METHODS TO CRYPTOGRPHIC PROTOCOL NLYSIS: EMERGING ISSUES ND TRENDS Catherine Meadows Code 5543 Center for High ssurance Computer Systems US Naval Research Laboratory Washington, DC 20375

More information

Project Recovery. . It Can Be Done

Project Recovery. . It Can Be Done Project Recovery. It Cn Be Done IPM Conference Wshington, D.C. Nov 4-7, 200 Wlt Lipke Oklhom City Air Logistics Center Tinker AFB, OK Overview Mngement Reserve Project Sttus Indictors Performnce Correction

More information

Regular Repair of Specifications

Regular Repair of Specifications Regulr Repir of Specifictions Michel Benedikt Oxford University michel.enedikt@coml.ox.c.uk Griele Puppis Oxford University griele.puppis@coml.ox.c.uk Cristin Riveros Oxford University cristin.riveros@coml.ox.c.uk

More information

and thus, they are similar. If k = 3 then the Jordan form of both matrices is

and thus, they are similar. If k = 3 then the Jordan form of both matrices is Homework ssignment 11 Section 7. pp. 249-25 Exercise 1. Let N 1 nd N 2 be nilpotent mtrices over the field F. Prove tht N 1 nd N 2 re similr if nd only if they hve the sme miniml polynomil. Solution: If

More information

Application for the Utah State Office of Education Secondary Science Endorsement

Application for the Utah State Office of Education Secondary Science Endorsement Appliction for the Uth Stte Office of Eduction Secondry Science Endorsement This endorsement is ttched to n Eductor License with secondry re of concentrtion. Cndidtes with n Eductor License who complete

More information

5 a LAN 6 a gateway 7 a modem

5 a LAN 6 a gateway 7 a modem STARTER With the help of this digrm, try to descrie the function of these components of typicl network system: 1 file server 2 ridge 3 router 4 ckone 5 LAN 6 gtewy 7 modem Another Novell LAN Router Internet

More information

MODULE 3. 0, y = 0 for all y

MODULE 3. 0, y = 0 for all y Topics: Inner products MOULE 3 The inner product of two vectors: The inner product of two vectors x, y V, denoted by x, y is (in generl) complex vlued function which hs the following four properties: i)

More information

Equivalence Checking. Sean Weaver

Equivalence Checking. Sean Weaver Equivlene Cheking Sen Wever Equivlene Cheking Given two Boolen funtions, prove whether or not two they re funtionlly equivlent This tlk fouses speifilly on the mehnis of heking the equivlene of pirs of

More information

Treatment Spring Late Summer Fall 0.10 5.56 3.85 0.61 6.97 3.01 1.91 3.01 2.13 2.99 5.33 2.50 1.06 3.53 6.10 Mean = 1.33 Mean = 4.88 Mean = 3.

Treatment Spring Late Summer Fall 0.10 5.56 3.85 0.61 6.97 3.01 1.91 3.01 2.13 2.99 5.33 2.50 1.06 3.53 6.10 Mean = 1.33 Mean = 4.88 Mean = 3. The nlysis of vrince (ANOVA) Although the t-test is one of the most commonly used sttisticl hypothesis tests, it hs limittions. The mjor limittion is tht the t-test cn be used to compre the mens of only

More information

The remaining two sides of the right triangle are called the legs of the right triangle.

The remaining two sides of the right triangle are called the legs of the right triangle. 10 MODULE 6. RADICAL EXPRESSIONS 6 Pythgoren Theorem The Pythgoren Theorem An ngle tht mesures 90 degrees is lled right ngle. If one of the ngles of tringle is right ngle, then the tringle is lled right

More information

, and the number of electrons is -19. e e 1.60 10 C. The negatively charged electrons move in the direction opposite to the conventional current flow.

, and the number of electrons is -19. e e 1.60 10 C. The negatively charged electrons move in the direction opposite to the conventional current flow. Prolem 1. f current of 80.0 ma exists in metl wire, how mny electrons flow pst given cross section of the wire in 10.0 min? Sketch the directions of the current nd the electrons motion. Solution: The chrge

More information

The LENA TM Language Environment Analysis System:

The LENA TM Language Environment Analysis System: FOUNDATION The LENA TM Lnguge Environment Anlysis System: Audio Specifictions of the DLP-0121 Michel Ford, Chrles T. Ber, Dongxin Xu, Umit Ypnel, Shrmi Gry LENA Foundtion, Boulder, CO LTR-03-2 September

More information

Regular Languages and Finite Automata

Regular Languages and Finite Automata N Lecture Notes on Regulr Lnguges nd Finite Automt for Prt IA of the Computer Science Tripos Mrcelo Fiore Cmbridge University Computer Lbortory First Edition 1998. Revised 1999, 2000, 2001, 2002, 2003,

More information

Math 135 Circles and Completing the Square Examples

Math 135 Circles and Completing the Square Examples Mth 135 Circles nd Completing the Squre Exmples A perfect squre is number such tht = b 2 for some rel number b. Some exmples of perfect squres re 4 = 2 2, 16 = 4 2, 169 = 13 2. We wish to hve method for

More information

String Searching. String Search. Spam Filtering. String Search

String Searching. String Search. Spam Filtering. String Search String Serch String Serching String serch: given pttern string p, find first mtch in text t. Model : cn't fford to preprocess the text. Krp-Rin Knuth-Morris-Prtt Boyer-Moore N = # chrcters in text M =

More information

Mathematics. Vectors. hsn.uk.net. Higher. Contents. Vectors 128 HSN23100

Mathematics. Vectors. hsn.uk.net. Higher. Contents. Vectors 128 HSN23100 hsn.uk.net Higher Mthemtics UNIT 3 OUTCOME 1 Vectors Contents Vectors 18 1 Vectors nd Sclrs 18 Components 18 3 Mgnitude 130 4 Equl Vectors 131 5 Addition nd Subtrction of Vectors 13 6 Multipliction by

More information

RTL Power Optimization with Gate-level Accuracy

RTL Power Optimization with Gate-level Accuracy RTL Power Optimiztion with Gte-level Accurcy Qi Wng Cdence Design Systems, Inc Sumit Roy Clypto Design Systems, Inc 555 River Oks Prkwy, Sn Jose 95125 2903 Bunker Hill Lne, Suite 208, SntClr 95054 qwng@cdence.com

More information

Multi-Scale Modeling of Nano Scale Phenomenon using CUDA based HPC Setup

Multi-Scale Modeling of Nano Scale Phenomenon using CUDA based HPC Setup Multi-Scle Modeling of Nno Scle Phenomenon using CUDA bsed HPC Setup Rohit Pthk nd Stydhr Joshi Acropolis Institute of Technology & Reserch, Indore, Mdhy Prdesh, Indi Shri Vishnv Institute of Technology

More information

1. In the Bohr model, compare the magnitudes of the electron s kinetic and potential energies in orbit. What does this imply?

1. In the Bohr model, compare the magnitudes of the electron s kinetic and potential energies in orbit. What does this imply? Assignment 3: Bohr s model nd lser fundmentls 1. In the Bohr model, compre the mgnitudes of the electron s kinetic nd potentil energies in orit. Wht does this imply? When n electron moves in n orit, the

More information

1.00/1.001 Introduction to Computers and Engineering Problem Solving Fall 2011 - Final Exam

1.00/1.001 Introduction to Computers and Engineering Problem Solving Fall 2011 - Final Exam 1./1.1 Introduction to Computers nd Engineering Problem Solving Fll 211 - Finl Exm Nme: MIT Emil: TA: Section: You hve 3 hours to complete this exm. In ll questions, you should ssume tht ll necessry pckges

More information

DATABASDESIGN FÖR INGENJÖRER - 1056F

DATABASDESIGN FÖR INGENJÖRER - 1056F DATABASDESIGN FÖR INGENJÖRER - 06F Sommr 00 En introuktionskurs i tssystem http://user.it.uu.se/~ul/t-sommr0/ lt. http://www.it.uu.se/eu/course/homepge/esign/st0/ Kjell Orsorn (Rusln Fomkin) Uppsl Dtse

More information

Words Symbols Diagram. abcde. a + b + c + d + e

Words Symbols Diagram. abcde. a + b + c + d + e Logi Gtes nd Properties We will e using logil opertions to uild mhines tht n do rithmeti lultions. It s useful to think of these opertions s si omponents tht n e hooked together into omplex networks. To

More information

0.1 Basic Set Theory and Interval Notation

0.1 Basic Set Theory and Interval Notation 0.1 Bsic Set Theory nd Intervl Nottion 3 0.1 Bsic Set Theory nd Intervl Nottion 0.1.1 Some Bsic Set Theory Notions Like ll good Mth ooks, we egin with definition. Definition 0.1. A set is well-defined

More information

GFI MilArchiver 6 vs C2C Archive One Policy Mnger GFI Softwre www.gfi.com GFI MilArchiver 6 vs C2C Archive One Policy Mnger GFI MilArchiver 6 C2C Archive One Policy Mnger Who we re Generl fetures Supports

More information

Unit 6: Exponents and Radicals

Unit 6: Exponents and Radicals Eponents nd Rdicls -: The Rel Numer Sstem Unit : Eponents nd Rdicls Pure Mth 0 Notes Nturl Numers (N): - counting numers. {,,,,, } Whole Numers (W): - counting numers with 0. {0,,,,,, } Integers (I): -

More information

Tool Support for Feature-Oriented Software Development

Tool Support for Feature-Oriented Software Development Tool Support for Feture-Oriented Softwre Development FetureIDE: An Eclipse-Bsed Approch Thoms Leich leich@iti.cs.unimgdeurg.de Sven Apel pel@iti.cs.unimgdeurg.de Lur Mrnitz mrnitz@cs.unimgdeurg.de ABSTRACT

More information

Warm-up for Differential Calculus

Warm-up for Differential Calculus Summer Assignment Wrm-up for Differentil Clculus Who should complete this pcket? Students who hve completed Functions or Honors Functions nd will be tking Differentil Clculus in the fll of 015. Due Dte:

More information