Last time Interprocedural analysis Dimensions of precision (flow- and context-sensitivity) Flow-Sensitive Pointer Analysis

Size: px
Start display at page:

Download "Last time Interprocedural analysis Dimensions of precision (flow- and context-sensitivity) Flow-Sensitive Pointer Analysis"

Transcription

1 Flow-Insnsitiv Pointr Anlysis Lst tim Intrprocurl nlysis Dimnsions of prcision (flow- n contxt-snsitivity) Flow-Snsitiv Pointr Anlysis Toy Flow-Insnsitiv Pointr Anlysis CIS 570 Lctur 12 Flow-Insnsitiv Pointr Anlysis 2 Flow-Insnsitiv Pointr Anlysis Th fining chrctristics Ignor th control-flow grph, n ssum tht sttmnts cn xcut in ny orr Rthr thn proucing solution for ch progrm point, prouc singl solution tht is vli for th whol progrm Flow-insnsitiv pointr nlyss Anrsn-styl nlysis: th slowst n most prcis Stnsgr nlysis: th fstst n lst prcis All othr flow-insnsitiv pointr nlyss r hybris of ths two CIS 570 Lctur 12 Flow-Insnsitiv Pointr Anlysis 3

2 Anrsn-Styl Pointr Anlysis [1994] Bsic i Viw pointr ssignmnts s constrints Us ths constrints to propgt points-to informtion CIS 570 Lctur 12 Flow-Insnsitiv Pointr Anlysis 4 Anrsn-styl Pointr Anlysis Exmpl 1 Progrm := &b c := := & := Flow-Snsitiv Solution { b } c { b } { } { } CIS 570 Lctur 12 Flow-Insnsitiv Pointr Anlysis 5

3 Anrsn-styl Pointr Anlysis Exmpl 1 Progrm Constrints Points-to Rltions := &b c := := & := { b, } c { b, } c { } b, } { } b, } W v rch fix point Trminology Bs constrints: Us to initiliz th points-to sts Ex: := &b Not n ftr initiliztion Simpl constrints: Involv vribl nms only Ex: c := Complx constrints: Involv pointr rfrncs Ex: * := c CIS 570 Lctur 12 Flow-Insnsitiv Pointr Anlysis 6 Anrsn-styl Pointr Anlysis Exmpl 2 Progrm := &b c := & := & f := * := c Constrints { b } c { } { } f * c c Points-to Rltions { b,} } c { } { } f { } b,} } Notic tht w crt th constrint grph ynmiclly CIS 570 Lctur 12 Flow-Insnsitiv Pointr Anlysis 7

4 Anrsn-Styl Pointr Anlysis Bsic i Viw pointr ssignmnts using constrint grph Propgt points-to rltions long th gs of th constrint grph, ing nw gs s inirct constrints r rsolv Constrint grph On no for ch vribl On irct g for ch constrint Anrsn-styl nlysis Cn b ruc to computing th trnsitiv closur of ynmic grph A wll-stui problm for which th bst known complxity is O(n 3 ) CIS 570 Lctur 12 Flow-Insnsitiv Pointr Anlysis 8 Anrsn-styl Pointr Anlysis Th Constrint Grph Exmpl 1 c {b,} {b,} {b,} CIS 570 Lctur 12 Flow-Insnsitiv Pointr Anlysis 9

5 Anrsn-styl Pointr Anlysis Th Constrint Grph Exmpl 2 f c [* c] {b,} {b} {b,} {b} {} {} CIS 570 Lctur 12 Flow-Insnsitiv Pointr Anlysis 10 Anrsn-styl Pointr Anlysis Cycl Elimintion Cycl Elimintion Th most importnt optimiztion for Anrsn-styl nlysis Dtct strongly-connct componnts in th constrint grph Collps thm into singl no Th rtionl All nos in th sm SCC r gurnt to hv th sm points-to rltions t th n of th nlysis Compliction Most SCCs r crt ynmiclly uring th nlysis Cycl limintion must b prform ynmiclly for grtst ffct CIS 570 Lctur 12 Flow-Insnsitiv Pointr Anlysis 11

6 Anrsn-styl Pointr Anlysis Cycl Elimintion {w,x,y,z} {} {w,x,y,z} {w,x} {w} b {w,x,y,z} {x} c {w,x,y,z} {w,x,z} {z} {w,x,y,z} {y} CIS 570 Lctur 12 Flow-Insnsitiv Pointr Anlysis 12 Anrsn-styl Pointr Anlysis Cycl Elimintion,b,c, {w,x,y,z} {} {w,x,y,z} CIS 570 Lctur 12 Flow-Insnsitiv Pointr Anlysis 13

7 Anrsn-styl Pointr Anlysis Procur Clls Progrm foo(int* x){... rturn x; } Constrints x { b } x := foo(&b) How o w hnl procur clls? Insrt constrints for copying ctul prmtrs to forml prmtrs Insrt constrints for copying rturn vlus CIS 570 Lctur 12 Flow-Insnsitiv Pointr Anlysis 14 Stnsgr Pointr Anlysis Bsic i Furthr ruc prcision by using qulity constrints Tht is, informtion flows both wys, rthr thn from th right-hn si to th lft-hn si of th constrint. Troffs Imprcis A systm of qulity constrints cn b solv in nr-linr tim Running tim is O(n α(n)), whr α(n) is th invrs Ackrmnn s function. α(2 132 ) < 4 Ky i Th ky to this lgorithm is th UNION-FIND t structur. CIS 570 Lctur 12 Flow-Insnsitiv Pointr Anlysis 15

8 Stnsgr Pointr Anlysis UNION-FIND Th UNION-FIND t structur Mintins st of isjoint sts n supports two oprtions: FIND(x) : rturn th st contining x. UNION(x,y) : union th two sts contining x n y. St Rprsnttion Sts r rprsnt by istinguish lmnt cll th st rprsnttiv Ech st is n invrt tr, with nos pointing to thir prnts n th st rprsnttiv s th root CIS 570 Lctur 12 Flow-Insnsitiv Pointr Anlysis 16 Stnsgr Pointr Anlysis UNION-FIND UNION (, b) - FIND(b) b c CIS 570 Lctur 12 Flow-Insnsitiv Pointr Anlysis 17

9 Stnsgr Pointr Anlysis UNION-FIND UNION (, c) - FIND(c) b c CIS 570 Lctur 12 Flow-Insnsitiv Pointr Anlysis 18 Stnsgr Pointr Anlysis UNION-FIND UNION (, ) - FIND() b c CIS 570 Lctur 12 Flow-Insnsitiv Pointr Anlysis 19

10 UNION-FIND Optimiztions Two ky optimiztions Pth comprssion Union-by-rnk Togthr ths optimiztions yil nr-linr tim oprtions Pth comprssion Avoi runnt srchs for th st rprsnttiv Union-by-rnk Whn prforming th UNION oprtion, choos th st rprsnttiv bs on th sizs of th two sts CIS 570 Lctur 12 Flow-Insnsitiv Pointr Anlysis 20 Stnsgr Pointr Anlysis Pth Comprssion UNION (, b) - FIND(b) b c CIS 570 Lctur 12 Flow-Insnsitiv Pointr Anlysis 21

11 Stnsgr Pointr Anlysis Pth Comprssion UNION (, c) - FIND(c) b c CIS 570 Lctur 12 Flow-Insnsitiv Pointr Anlysis 22 Stnsgr Pointr Anlysis Pth Comprssion UNION (, ) - FIND() b c CIS 570 Lctur 12 Flow-Insnsitiv Pointr Anlysis 23

12 Stnsgr Pointr Anlysis Union-by-Rnk UNION (, b) - FIND(b) b c CIS 570 Lctur 12 Flow-Insnsitiv Pointr Anlysis 24 Stnsgr Pointr Anlysis Union-by-Rnk UNION (, c) - FIND(c) b c CIS 570 Lctur 12 Flow-Insnsitiv Pointr Anlysis 25

13 Stnsgr Pointr Anlysis Union-by-Rnk UNION (, ) - FIND() b c Wht is th bnfit of union-by-rnk? It nsurs tht w follow s fw prnt pointrs s possibl Consir th cost of slcting s th nw st rprsnttiv in this lst union oprtion CIS 570 Lctur 12 Flow-Insnsitiv Pointr Anlysis 26 Stnsgr Pointr Anlysis th Algorithm mrg(x, y) { x = FIND(x); y = FIND(y); if (x == y) thn rturn; UNION(x,y); mrg(points-to(x),points-to(y)); } for ch constrint LHS = RHS mrg(lhs,rhs) CIS 570 Lctur 12 Flow-Insnsitiv Pointr Anlysis 27

14 Stnsgr Pointr Anlysis Exmpl 1 Progrm := &b c := := & := Constrints = { b, } c = = Points-to Rltions,c, b, CIS 570 Lctur 12 Flow-Insnsitiv Pointr Anlysis 28 Stnsgr Pointr Anlysis Exmpl 2 Progrm Constrints Points-to Rltions := &b c := & := & f := * := c = { b } c = { } = { } f = * = c,f,c c b, b CIS 570 Lctur 12 Flow-Insnsitiv Pointr Anlysis 29

15 Anrsn vs. Stnsgr Anrsn-styl nlysis int **, *b, c, *, ; 1: = &b; 2: b = &c; 3: = &; 4: = &; b c u to sttmnt 4 b c Stnsgr nlysis b c u to sttmnt 4 b c CIS 570 Lctur 12 Flow-Insnsitiv Pointr Anlysis 30 Concpts Flow-insnsitiv pointr nlysis Anrsn-styl nlysis Inclusion-bs, subst-bs Comput trnsitiv closur of ynmic grph Constrint grph Cycl limintion optimiztion Stnsgr-styl nlysis Unifiction-bs, qulity-bs Union-fin t structur CIS 570 Lctur 12 Flow-Insnsitiv Pointr Anlysis 31

16 Nxt Tim Lctur Contxt-Snsitiv Pointr Anlysis CIS 570 Lctur 12 Flow-Insnsitiv Pointr Anlysis 32

Uses for Binary Trees -- Binary Search Trees

Uses for Binary Trees -- Binary Search Trees CS122 Algorithms n Dt Struturs MW 11:00 m 12:15 pm, MSEC 101 Instrutor: Xio Qin Ltur 10: Binry Srh Trs n Binry Exprssion Trs Uss or Binry Trs Binry Srh Trs n Us or storing n rtriving inormtion n Insrt,

More information

Fundamentals of Tensor Analysis

Fundamentals of Tensor Analysis MCEN 503/ASEN 50 Chptr Fundmntls of Tnsor Anlysis Fll, 006 Fundmntls of Tnsor Anlysis Concpts of Sclr, Vctor, nd Tnsor Sclr α Vctor A physicl quntity tht cn compltly dscrid y rl numr. Exmpl: Tmprtur; Mss;

More information

Reading. Minimum Spanning Trees. Outline. A File Sharing Problem. A Kevin Bacon Problem. Spanning Trees. Section 9.6

Reading. Minimum Spanning Trees. Outline. A File Sharing Problem. A Kevin Bacon Problem. Spanning Trees. Section 9.6 Rin Stion 9.6 Minimum Spnnin Trs Outlin Minimum Spnnin Trs Prim s Alorithm Kruskl s Alorithm Extr:Distriut Shortst-Pth Alorithms A Fil Shrin Prolm Sy unh o usrs wnt to istriut il monst thmslvs. Btwn h

More information

Important result on the first passage time and its integral functional for a certain diffusion process

Important result on the first passage time and its integral functional for a certain diffusion process Lcturs Mtmátics Volumn 22 (21), págins 5 9 Importnt rsult on th first pssg tim nd its intgrl functionl for crtin diffusion procss Yousf AL-Zlzlh nd Bsl M. AL-Eidh Kuwit Univrsity, Kuwit Abstrct. In this

More information

December Homework- Week 1

December Homework- Week 1 Dcmbr Hmwrk- Wk 1 Mth Cmmn Cr Stndrds: K.CC.A.1 - Cunt t 100 by ns nd by tns. K.CC.A.2 - Cunt frwrd bginning frm givn numbr within th knwn squnc (instd f hving t bgin t 1). K.CC.B.4.A - Whn cunting bjcts,

More information

Chapter 3 Chemical Equations and Stoichiometry

Chapter 3 Chemical Equations and Stoichiometry Chptr Chmicl Equtions nd Stoichiomtry Homwork (This is VERY importnt chptr) Chptr 27, 29, 1, 9, 5, 7, 9, 55, 57, 65, 71, 75, 77, 81, 87, 91, 95, 99, 101, 111, 117, 121 1 2 Introduction Up until now w hv

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

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

Quality and Pricing for Outsourcing Service: Optimal Contract Design

Quality and Pricing for Outsourcing Service: Optimal Contract Design Qulity nd Pricing for Outsourcing Srvic: Optiml Contrct Dsign Smr K. Mukhopdhyy Univrsity of Wisconsin-Milwuk Co-uthor: Xiowi Zhu, Wst Chstr Univrsity of PA Third nnul confrnc, POMS Collg of Srvic Oprtions

More information

Oracle PL/SQL Programming Advanced

Oracle PL/SQL Programming Advanced Orl PL/SQL Progrmming Avn In orr to lrn whih qustions hv n nswr orrtly: 1. Print ths pgs. 2. Answr th qustions. 3. Sn this ssssmnt with th nswrs vi:. FAX to (212) 967-3498. Or. Mil th nswrs to th following

More information

Distributed Systems Principles and Paradigms. Chapter 11: Distributed File Systems. Distributed File Systems. Example: NFS Architecture

Distributed Systems Principles and Paradigms. Chapter 11: Distributed File Systems. Distributed File Systems. Example: NFS Architecture Distriut Systms Prinipls n Prigms Mrtn vn Stn VU mstrm, Dpt. Computr Sin [email protected] Chptr 11: Vrsion: Dmr 10, 2012 1 / 14 Gnrl gol Try to mk fil systm trnsprntly vill to rmot lints. 1. Fil mov to lint

More information

Change Your History How Can Soccer Knowledge Improve Your Business Processes?

Change Your History How Can Soccer Knowledge Improve Your Business Processes? Symposium Inuurl Lctur o Hjo Rijrs, VU, 26-6-2015 Chn Your History How Cn Soccr Knowl Improv Your Businss Procsss? Wil vn r Alst TU/ n DSC/ 1970 born Oostrbk 1988-1992 CS TU/ 1992-1994 TS TU/ 1994-1996

More information

AC Circuits Three-Phase Circuits

AC Circuits Three-Phase Circuits AC Circuits Thr-Phs Circuits Contnts Wht is Thr-Phs Circuit? Blnc Thr-Phs oltgs Blnc Thr-Phs Connction Powr in Blncd Systm Unblncd Thr-Phs Systms Aliction Rsidntil Wiring Sinusoidl voltg sourcs A siml

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

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

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

Basically, logarithmic transformations ask, a number, to what power equals another number?

Basically, logarithmic transformations ask, a number, to what power equals another number? Wht i logrithm? To nwer thi, firt try to nwer the following: wht i x in thi eqution? 9 = 3 x wht i x in thi eqution? 8 = 2 x Biclly, logrithmic trnformtion k, number, to wht power equl nother number? In

More information

Schedule C. Notice in terms of Rule 5(10) of the Capital Gains Rules, 1993

Schedule C. Notice in terms of Rule 5(10) of the Capital Gains Rules, 1993 (Rul 5(10)) Shul C Noti in trms o Rul 5(10) o th Cpitl Gins Ruls, 1993 Sttmnt to sumitt y trnsror o shrs whr thr is trnsr o ontrolling intrst Prt 1 - Dtils o Trnsror Nm Arss ROC No (ompnis only) Inom Tx

More information

Algorithmic Aspects of Access Networks Design in B3G/4G Cellular Networks

Algorithmic Aspects of Access Networks Design in B3G/4G Cellular Networks Algorithmi Aspts o Ass Ntworks Dsign in BG/G Cllulr Ntworks Dvi Amzllg, Josph (Si) Nor,DnnyRz Computr Sin Dprtmnt Thnion, Hi 000, Isrl {mzllg,nny}@s.thnion..il Mirosot Rsrh On Mirosot Wy, Rmon, WA 980

More information

Hospitals. Internal Revenue Service Information about Schedule H (Form 990) and its instructions is at www.irs.gov/form990.

Hospitals. Internal Revenue Service Information about Schedule H (Form 990) and its instructions is at www.irs.gov/form990. SCHEDULE H Hospitls OMB No. 1545-0047 (Form 990) Complt if th orgniztion nswr "Ys" to Form 990, Prt IV, qustion 20. Atth to Form 990. Opn to Puli Dprtmnt of th Trsury Intrnl Rvnu Srvi Informtion out Shul

More information

How To Set Up A Network For Your Business

How To Set Up A Network For Your Business Why Network is n Essentil Productivity Tool for Any Smll Business TechAdvisory.org SME Reports sponsored by Effective technology is essentil for smll businesses looking to increse their productivity. Computer

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

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

Link-Disjoint Paths for Reliable QoS Routing

Link-Disjoint Paths for Reliable QoS Routing Link-Disjoint Pths or Rlil QoS Routing Yuhun Guo, Frnno Kuiprs n Pit Vn Mighm # Shool o Eltril n Inormtion Enginring, Northrn Jiotong Univrsity, Bijing, 000, P.R. Chin Fulty o Inormtion Thnology n Systms,

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

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

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 [email protected]

More information

A Note on Approximating. the Normal Distribution Function

A Note on Approximating. the Normal Distribution Function Applid Mathmatical Scincs, Vol, 00, no 9, 45-49 A Not on Approimating th Normal Distribution Function K M Aludaat and M T Alodat Dpartmnt of Statistics Yarmouk Univrsity, Jordan Aludaatkm@hotmailcom and

More information

LINEAR TRANSFORMATIONS AND THEIR REPRESENTING MATRICES

LINEAR TRANSFORMATIONS AND THEIR REPRESENTING MATRICES LINEAR TRANSFORMATIONS AND THEIR REPRESENTING MATRICES DAVID WEBB CONTENTS Liner trnsformtions 2 The representing mtrix of liner trnsformtion 3 3 An ppliction: reflections in the plne 6 4 The lgebr of

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

Revised Conditions (January 2009) LLOYDS BANKING GROUP SHARE ISA CONDITIONS

Revised Conditions (January 2009) LLOYDS BANKING GROUP SHARE ISA CONDITIONS Rvis Conitions (Jnury 2009) LLOYDS BANKING GROUP SHARE ISA CONDITIONS Contnts 1 Who r th prtis?... 2 Wht o wors n phrss in ol typ mn?... 3 Whn i my pln strt?... 4 How o I invst in my pln?... 5 Who owns

More information

MANAGEMENT OF INFORMATION SECURITY AND FORENSICS

MANAGEMENT OF INFORMATION SECURITY AND FORENSICS MANAGEMENT OF INFORMATION SECURITY AND FORENSICS CS 307 Ctlog Dsription PREREQUISITE: CS 0. Stuy of informtion surity n igitl fornsis using prtil s stuis. Emphsis is on vloping surity poliis, surity mngmnt

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

Outside Cut 1 of fabric Cut 1 of interfacing

Outside Cut 1 of fabric Cut 1 of interfacing a a Outsi Cut o abric Cut o intracing a a b b Outsi Cut o abric Cut o intracing Placmnt lin or Mony Pockts Dix Not: F. Cut Fol b. Pin t /8 in 5. Nx bottom pics sw th 6. For t Prss, 7. Lay togth on th 8.

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

Lecture 20: Emitter Follower and Differential Amplifiers

Lecture 20: Emitter Follower and Differential Amplifiers Whits, EE 3 Lctur 0 Pag of 8 Lctur 0: Emittr Followr and Diffrntial Amplifirs Th nxt two amplifir circuits w will discuss ar ry important to lctrical nginring in gnral, and to th NorCal 40A spcifically.

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

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

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

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

Cloud and Big Data Summer School, Stockholm, Aug., 2015 Jeffrey D. Ullman

Cloud and Big Data Summer School, Stockholm, Aug., 2015 Jeffrey D. Ullman Cloud and Big Data Summr Scool, Stockolm, Aug., 2015 Jffry D. Ullman Givn a st of points, wit a notion of distanc btwn points, group t points into som numbr of clustrs, so tat mmbrs of a clustr ar clos

More information

Motivation Suppose we have a database of people We want to gure out who is related to whom Initially, we only have a list of people, and information a

Motivation Suppose we have a database of people We want to gure out who is related to whom Initially, we only have a list of people, and information a CSE 220: Handout 29 Disjoint Sets 1 Motivation Suppose we have a database of people We want to gure out who is related to whom Initially, we only have a list of people, and information about relations

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

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

Review guide for the final exam in Math 233

Review guide for the final exam in Math 233 Review guide for the finl exm in Mth 33 1 Bsic mteril. This review includes the reminder of the mteril for mth 33. The finl exm will be cumultive exm with mny of the problems coming from the mteril covered

More information

Lectures 8 and 9 1 Rectangular waveguides

Lectures 8 and 9 1 Rectangular waveguides 1 Lectures 8 nd 9 1 Rectngulr wveguides y b x z Consider rectngulr wveguide with 0 < x b. There re two types of wves in hollow wveguide with only one conductor; Trnsverse electric wves

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

CHAPTER 11 Numerical Differentiation and Integration

CHAPTER 11 Numerical Differentiation and Integration CHAPTER 11 Numericl Differentition nd Integrtion Differentition nd integrtion re bsic mthemticl opertions with wide rnge of pplictions in mny res of science. It is therefore importnt to hve good methods

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

Higher. Exponentials and Logarithms 160

Higher. Exponentials and Logarithms 160 hsn uknt Highr Mthmtics UNIT UTCME Eponntils nd Logrithms Contnts Eponntils nd Logrithms 6 Eponntils 6 Logrithms 6 Lws of Logrithms 6 Eponntils nd Logrithms to th Bs 65 5 Eponntil nd Logrithmic Equtions

More information

9 CONTINUOUS DISTRIBUTIONS

9 CONTINUOUS DISTRIBUTIONS 9 CONTINUOUS DISTIBUTIONS A rndom vrible whose vlue my fll nywhere in rnge of vlues is continuous rndom vrible nd will be ssocited with some continuous distribution. Continuous distributions re to discrete

More information

WORKERS' COMPENSATION ANALYST, 1774 SENIOR WORKERS' COMPENSATION ANALYST, 1769

WORKERS' COMPENSATION ANALYST, 1774 SENIOR WORKERS' COMPENSATION ANALYST, 1769 08-16-85 WORKERS' COMPENSATION ANALYST, 1774 SENIOR WORKERS' COMPENSATION ANALYST, 1769 Summary of Dutis : Dtrmins City accptanc of workrs' compnsation cass for injurd mploys; authorizs appropriat tratmnt

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

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

Corporate Compliance vs. Enterprise-Wide Risk Management

Corporate Compliance vs. Enterprise-Wide Risk Management Corporte Complince vs. Enterprise-Wide Risk Mngement Brent Sunders, Prtner (973) 236-4682 November 2002 Agend Corporte Complince Progrms? Wht is Enterprise-Wide Risk Mngement? Key Differences Why Will

More information

Factoring Polynomials

Factoring Polynomials Fctoring Polynomils Some definitions (not necessrily ll for secondry school mthemtics): A polynomil is the sum of one or more terms, in which ech term consists of product of constnt nd one or more vribles

More information

trademark and symbol guidelines FOR CORPORATE STATIONARY APPLICATIONS reviewed 01.02.2007

trademark and symbol guidelines FOR CORPORATE STATIONARY APPLICATIONS reviewed 01.02.2007 trdemrk nd symbol guidelines trdemrk guidelines The trdemrk Cn be plced in either of the two usul configurtions but horizontl usge is preferble. Wherever possible the trdemrk should be plced on blck bckground.

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

Architecture of the proposed standard

Architecture of the proposed standard Architctur of th proposd standard Introduction Th goal of th nw standardisation projct is th dvlopmnt of a standard dscribing building srvics (.g.hvac) product catalogus basd on th xprincs mad with th

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

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

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

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

Operational Procedure: ACNC Data Breach Response Plan

Operational Procedure: ACNC Data Breach Response Plan OP 2015/03 Oprtionl Prour: ACNC Dt Brh Rspons Pln This Oprtionl Prour is issu unr th uthority of th Assistnt Commissionr Gnrl Counsl n shoul r togthr with th ACNC Poliy Frmwork, whih sts out th sop, ontxt

More information

Section 7-4 Translation of Axes

Section 7-4 Translation of Axes 62 7 ADDITIONAL TOPICS IN ANALYTIC GEOMETRY Section 7-4 Trnsltion of Aes Trnsltion of Aes Stndrd Equtions of Trnslted Conics Grphing Equtions of the Form A 2 C 2 D E F 0 Finding Equtions of Conics In the

More information

Constrained Renewable Resource Allocation in Fuzzy Metagraphs via Min- Slack

Constrained Renewable Resource Allocation in Fuzzy Metagraphs via Min- Slack Intrntonl Journl of ppld Oprtonl Rsrch Vol 1, No 1, pp 7-17, Summr 011 Journl hompg: wwworlur Constrnd Rnwl Rsourc llocton n Fuzzy Mtgrphs v Mn- Slck S S Hshmn* Rcvd: Jnury 31, 011 ; ccptd: My 1, 011 strct

More information

A Project Management framework for Software Implementation Planning and Management

A Project Management framework for Software Implementation Planning and Management PPM02 A Projct Managmnt framwork for Softwar Implmntation Planning and Managmnt Kith Lancastr Lancastr Stratgis [email protected] Th goal of introducing nw tchnologis into your company

More information

Algebra Review. How well do you remember your algebra?

Algebra Review. How well do you remember your algebra? Algebr Review How well do you remember your lgebr? 1 The Order of Opertions Wht do we men when we write + 4? If we multiply we get 6 nd dding 4 gives 10. But, if we dd + 4 = 7 first, then multiply by then

More information

WIRELESS mesh networks (WMNs) provide cheap, reliable,

WIRELESS mesh networks (WMNs) provide cheap, reliable, ynmic nwith ontrol in Wirlss Msh Ntworks: Qulity o xprinc bs pproch Rstin Pris, vi Hock, Nico yr, Mtthis Sibrt, irk Sthl, Vslin Rkocvic, ngnn Xu, Phuoc Trn-Gi bstrct Wirlss Msh Ntworks (WMNs) r gining

More information

Lecture 3: Diffusion: Fick s first law

Lecture 3: Diffusion: Fick s first law Lctur 3: Diffusion: Fick s first law Today s topics What is diffusion? What drivs diffusion to occur? Undrstand why diffusion can surprisingly occur against th concntration gradint? Larn how to dduc th

More information

Econ 371: Answer Key for Problem Set 1 (Chapter 12-13)

Econ 371: Answer Key for Problem Set 1 (Chapter 12-13) con 37: Answr Ky for Problm St (Chaptr 2-3) Instructor: Kanda Naknoi Sptmbr 4, 2005. (2 points) Is it possibl for a country to hav a currnt account dficit at th sam tim and has a surplus in its balanc

More information

Geometry 7-1 Geometric Mean and the Pythagorean Theorem

Geometry 7-1 Geometric Mean and the Pythagorean Theorem Geometry 7-1 Geometric Men nd the Pythgoren Theorem. Geometric Men 1. Def: The geometric men etween two positive numers nd is the positive numer x where: = x. x Ex 1: Find the geometric men etween the

More information

Predicting Current User Intent with Contextual Markov Models

Predicting Current User Intent with Contextual Markov Models Priting Currnt Usr Intnt with Contxtul Mrkov Mols Juli Kislv, Hong Thnh Lm, Mykol Phnizkiy Dprtmnt of Computr Sin Einhovn Univrsity of Thnology P.O. Box 513, NL-5600MB, th Nthrlns {t.l.hong, j.kislv, m.phnizkiy}@tu.nl

More information

Probabilistic maintenance and asset management on moveable storm surge barriers

Probabilistic maintenance and asset management on moveable storm surge barriers Probabilistic maintnanc an asst managmnt on movabl storm surg barrirs Patrick Wbbrs Ministry of Transport, Public Works an Watr Managmnt Civil Enginring Division A n a l y s O n r h o u F a a l k a n s

More information

Free ACA SOLUTION (IRS 1094&1095 Reporting)

Free ACA SOLUTION (IRS 1094&1095 Reporting) Fr ACA SOLUTION (IRS 1094&1095 Rporting) Th Insuranc Exchang (301) 279-1062 ACA Srvics Transmit IRS Form 1094 -C for mployrs Print & mail IRS Form 1095-C to mploys HR Assist 360 will gnrat th 1095 s for

More information

Basic Analysis of Autarky and Free Trade Models

Basic Analysis of Autarky and Free Trade Models Bsic Anlysis of Autrky nd Free Trde Models AUTARKY Autrky condition in prticulr commodity mrket refers to sitution in which country does not engge in ny trde in tht commodity with other countries. Consequently

More information

Magic Message Maker Amaze your customers with this Gift of Caring communication piece

Magic Message Maker Amaze your customers with this Gift of Caring communication piece Magic Mssag Makr maz your customrs with this Gift of aring communication pic Girls larn th powr and impact of crativ markting with this attntion grabbing communication pic that will hlp thm o a World of

More information

Human Pedigrees. Independent Assortment. Mendel s Second Law. Independent Assortment Test Cross. 4 phenotypes. Pedigree analysis:

Human Pedigrees. Independent Assortment. Mendel s Second Law. Independent Assortment Test Cross. 4 phenotypes. Pedigree analysis: Biology 2250 rinciples of Genetics nnouncements B2250 edings nd roblems Lb 3 Informtion: B2250 (Innes) webpge downlod nd print before lb. Virtul fly: log in nd prctice http://biologylb.wlonline.com/ Ch.

More information

The example is taken from Sect. 1.2 of Vol. 1 of the CPN book.

The example is taken from Sect. 1.2 of Vol. 1 of the CPN book. Rsourc Allocation Abstract This is a small toy xampl which is wll-suitd as a first introduction to Cnts. Th CN modl is dscribd in grat dtail, xplaining th basic concpts of C-nts. Hnc, it can b rad by popl

More information

DlNBVRGH + Sickness Absence Monitoring Report. Executive of the Council. Purpose of report

DlNBVRGH + Sickness Absence Monitoring Report. Executive of the Council. Purpose of report DlNBVRGH + + THE CITY OF EDINBURGH COUNCIL Sickness Absence Monitoring Report Executive of the Council 8fh My 4 I.I...3 Purpose of report This report quntifies the mount of working time lost s result of

More information

Portfolio approach to information technology security resource allocation decisions

Portfolio approach to information technology security resource allocation decisions Portfolio pproch to informtion technology security resource lloction decisions Shivrj Knungo Deprtment of Decision Sciences The George Wshington University Wshington DC 20052 [email protected] Abstrct This

More information

5.2. LINE INTEGRALS 265. Let us quickly review the kind of integrals we have studied so far before we introduce a new one.

5.2. LINE INTEGRALS 265. Let us quickly review the kind of integrals we have studied so far before we introduce a new one. 5.2. LINE INTEGRALS 265 5.2 Line Integrls 5.2.1 Introduction Let us quickly review the kind of integrls we hve studied so fr before we introduce new one. 1. Definite integrl. Given continuous rel-vlued

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

FEE-HELP INFORMATION SHEET FOR DOMESTIC FULL FEE STUDENTS

FEE-HELP INFORMATION SHEET FOR DOMESTIC FULL FEE STUDENTS FEE-HELP INFORMATION SHEET FOR DOMESTIC FULL FEE STUDENTS This is n infomtion sht poducd by th Monsh Lw Studnts Socity Juis Docto Potfolio to ssist full f pying studnts (domstic) in undstnding th issus

More information

Or more simply put, when adding or subtracting quantities, their uncertainties add.

Or more simply put, when adding or subtracting quantities, their uncertainties add. Propgtion of Uncertint through Mthemticl Opertions Since the untit of interest in n eperiment is rrel otined mesuring tht untit directl, we must understnd how error propgtes when mthemticl opertions re

More information

JaERM Software-as-a-Solution Package

JaERM Software-as-a-Solution Package JERM Softwre-s--Solution Pckge Enterprise Risk Mngement ( ERM ) Public listed compnies nd orgnistions providing finncil services re required by Monetry Authority of Singpore ( MAS ) nd/or Singpore Stock

More information

Network Decoupling for Secure Communications in Wireless Sensor Networks

Network Decoupling for Secure Communications in Wireless Sensor Networks Ntwork Doupling for Sur Communitions in Wirlss Snsor Ntworks Wnjun Gu, Xiol Bi, Srirm Chllppn n Dong Xun Dprtmnt of Computr Sin n Enginring Th Ohio-Stt Univrsity, Columus, Ohio 43210 1277 Emil: gu, ixi,

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

BUSINESS OWNERS PACKAGE INSURANCE APPLICATION

BUSINESS OWNERS PACKAGE INSURANCE APPLICATION BUSINESS OWNERS PACKAGE INSURANCE APPLICATION Progrm ville through: CAMICO Insurnce Services Tel: 800.652.1772 Prt 1: Generl Informtion 1. Firm Nme: 2. Contct Person: (Person designted nd uthorized y the

More information

CPS 220 Theory of Computation REGULAR LANGUAGES. Regular expressions

CPS 220 Theory of Computation REGULAR LANGUAGES. Regular expressions CPS 22 Thory of Computation REGULAR LANGUAGES Rgular xprssions Lik mathmatical xprssion (5+3) * 4. Rgular xprssion ar built using rgular oprations. (By th way, rgular xprssions show up in various languags:

More information

baby on the way, quit today

baby on the way, quit today for mums-to-be bby on the wy, quit tody WHAT YOU NEED TO KNOW bout smoking nd pregnncy uitting smoking is the best thing you cn do for your bby We know tht it cn be difficult to quit smoking. But we lso

More information

Experiment 6: Friction

Experiment 6: Friction Experiment 6: Friction In previous lbs we studied Newton s lws in n idel setting, tht is, one where friction nd ir resistnce were ignored. However, from our everydy experience with motion, we know tht

More information

STATEMENT OF INSOLVENCY PRACTICE 3.2

STATEMENT OF INSOLVENCY PRACTICE 3.2 STATEMENT OF INSOLVENCY PRACTICE 3.2 COMPANY VOLUNTARY ARRANGEMENTS INTRODUCTION 1 A Company Voluntary Arrangmnt (CVA) is a statutory contract twn a company and its crditors undr which an insolvncy practitionr

More information