Summary: Semantic Analysis

Size: px
Start display at page:

Download "Summary: Semantic Analysis"

Transcription

1 Summary: Smantic Analysis Chck rrors not dtctd by lxical or syntax analysis Intrmdiat Cod Scop rrors: Variabls not dfind Multipl dclarations Typ rrors: Assignmnt of valus of diffrnt typs Invocation of functions with diffrnt numbr of paramtrs or paramtrs of incorrct typ Incorrct us of rturn statmnts 1 CS 412/413 Spring 2008 Introduction to Compilrs 2 Smantic Analysis Typ chcking Us typ chcking ruls Static smantics = formal framwork to spcify typchcking ruls Thr ar also control flow rrors: Must vrify that a brak or continu statmnt is always nclosd by a whil (or for) statmnt Java: must vrify that a brak X statmnt is nclosd by a for loop with labl X Can asily chck control-flow rrors by rcursivly travrsing th AST Sourc cod (charactr stram) Tokn stram Abstract syntax tr Abstract syntax tr + symbol tabls, typs Whr W Ar Lxical analysis Syntactic Analysis Smantic Analysis Intrmdiat Cod Gnration rgular xprssions grammars static smantics Intrmdiat Cod CS 412/413 Spring 2008 Introduction to Compilrs 3 CS 412/413 Spring 2008 Introduction to Compilrs 4

2 Usually two IRs: High-lvl IR Languag-indpndnt (but closr to languag) C Fortran Pascal Intrmdiat Cod HIR Low-lvl IR Machin indpndnt (but closr to machin) LIR Pntium Java bytcod PowrPC High-lvl IR Tr nod structur, ssntially ASTs High-lvl constructs common to many languags Exprssion nods Statmnt nods Exprssion nods for: Intgrs and program variabls Binary oprations: 1 OP 2 Arithmtic oprations Logic oprations Comparisons Unary oprations: OP Array accsss: 1[2] CS 412/413 Spring 2008 Introduction to Compilrs 5 CS 412/413 Spring 2008 Introduction to Compilrs 6 High-lvl IR Statmnt nods: Block statmnts (statmnt squncs): (s1,, sn) Variabl assignmnts: v = Array assignmnts: 1[2] = 3 If-thn-ls statmnts: if c thn s1 ls s2 If-thn statmnts: if c thn s Whil loops: whil (c) s Function call statmnts: f(1,, N) Rturn statmnts: rturn or rturn May also contain: For loop statmnts: for(v = 1 to 2) s Brak and continu statmnts Switch statmnts: switch() { v1: s1,, vn: sn } Low-Lvl IR Low-lvl rprsntation is ssntially an instruction st for an abstract machin Altrnativs for low-lvl IR: Thr-addrss cod or quadrupls (Dragon Book): a = b OP c Tr rprsntation (Tigr Book) Stack machin (lik Java bytcod) CS 412/413 Spring 2008 Introduction to Compilrs 7 CS 412/413 Spring 2008 Introduction to Compilrs 8

3 Thr-Addrss Cod In this class: thr-addrss cod a = b OP c Has at most thr addrsss (may hav fwr) Also namd quadrupls bcaus can b rprsntd as: (a, b, c, OP) Exampl: a = (b+c)*(-); t1 = b + c t2 = a = t1 * t2 Low IR Instructions Assignmnt instructions: Binary oprations: a = b OP c arithmtic: ADD, SUB, MUL, DIV, MOD logic: AND, OR, XOR comparisons: EQ, NEQ, LT, GT, LEQ, GEQ Unary opration a = OP b Arithmtic MINUS or logic NEG Copy instruction: a = b Load /stor: a = *b, *a = b Othr data movmnt instructions CS 412/413 Spring 2008 Introduction to Compilrs 9 CS 412/413 Spring 2008 Introduction to Compilrs 10 Low IR Instructions, cont. Flow of control instructions: labl L: labl instruction jump L: Unconditional jump cjump a L: conditional jump Function call call f(a 1,., a n ) a = call f(a 1,., a n ) Is an xtnsion to quads IR dscribs th Instruction St of an abstract machin m = 0; if (c == 0) { m = m+ n*n; } ls { m = m + n; } Exampl m = 0 t1 = (c == 0) fjump t1 falsb t2 = n * n m = m + t2 jump nd labl falsb m = m+n labl nd CS 412/413 Spring 2008 Introduction to Compilrs 11 CS 412/413 Spring 2008 Introduction to Compilrs 12

4 How To Translat? May hav nstd languag constructs Nstd if and whil statmnts Nd an algorithmic way to translat Solution: Start from th AST rprsntation Dfin translation for ach nod in th AST in trms of a (rcursiv) translation of its constitunts Notation Us th notation T[] = low-lvl IR of high-lvl IR construct T[] is squnc of low-lvl IR instructions If is xprssion (or statmnt xprssion), T[] rprsnts a valu Dnot by t = T[] th low-lvl IR of, whos rsult valu is stord in t For variabl v, dfin T[v] to b v, i.., t = T[v] is copy instruction t = v CS 412/413 Spring 2008 Introduction to Compilrs 13 CS 412/413 Spring 2008 Introduction to Compilrs 14 Translating Exprssions Binary oprations: t = T[ 1 OP 2 ] (arithmtic oprations and comparisons) t1 = T[ 1 ] t2 = T[ 2 ] t = t1 OP t2 Unary oprations: t = T[ OP ] t1 = T[ ] t = OP t1 1 OP OP 2 Translating Boolan Exprssions t = T[ 1 OR 2 ] t1 = T[ 1 ] t2 = T[ 2 ] t = t1 OR t2 but how about short-circuit OR, for which w should comput 2 only if 1 valuats to fals 1 OR 2 CS 412/413 Spring 2008 Introduction to Compilrs 15 CS 412/413 Spring 2008 Introduction to Compilrs 16

5 Translating Short-Circuit OR Short-circuit OR: t = T[ 1 SC-OR 2 ] t = T[ 1 ] tjump t Lnd t = T[ 2 ] SC-OR 1 2 Translating Short-Circuit AND Short-circuit AND: t = T[ 1 SC-AND 2 ] t = T[ 1 ] fjump t Lnd t = T[ 2 ] SC-AND 1 2 how about short-circuit AND? CS 412/413 Spring 2008 Introduction to Compilrs 17 CS 412/413 Spring 2008 Introduction to Compilrs 18 Array and Fild Accsss Nstd Exprssions Array accss: t = T[ v[] ] t1 = T[ ] t = v[t1] Fild accss: t = T[ 1.f ] t1 = T[ 1 ] t = t1.f array v. 1 2 In ths translations, xprssions may b nstd; Translation rcurss on th xprssion structur Exampl: t = T[ (a - b) * (c + d) ] t1 = a t2 = b T[ (a - b) ] t3 = t1 t2 t4 = b t5 = c T[ (c + d) ] t5 = t4 + t5 t = t3 * t5 T[ (a - b) * (c + d) ] CS 412/413 Spring 2008 Introduction to Compilrs 19 CS 412/413 Spring 2008 Introduction to Compilrs 20

6 Translating Statmnts Statmnt squnc: T[ s1; s2; ; sn ] T[ s1 ] T[ s2 ] T[ sn ] sq s1 s2 sn IR instructions of a statmnt squnc = concatnation of IR instructions of statmnts Assignmnt Statmnts Variabl assignmnt: T[ v = ] t = T[ ] v = t [altrnativly] v = T[ ] var-assign Array assignmnt: T[ v[1] = 2 ] t1 = T[ 1 ] array-assign t2 = T[ 2 ] v[t1] = t2 v 1 2 v CS 412/413 Spring 2008 Introduction to Compilrs 21 CS 412/413 Spring 2008 Introduction to Compilrs 22 Translating If-Thn-Els Translating If-Thn T[ if () thn s1 ls s2 ] T[ if () thn s ] t1 = T[ ] fjump t1 Lfals T[ s1 ] jump Lnd labl Lfals T[ s2 ] if-thn-ls s1 s2 t1 = T[ ] fjump t1 Lnd T[ s ] if-thn s CS 412/413 Spring 2008 Introduction to Compilrs 23 CS 412/413 Spring 2008 Introduction to Compilrs 24

7 Whil Statmnts Switch Statmnts T[ whil () { s } ] labl Ltst t1 = T[ ] fjump t1 Lnd T[ s ] jump Ltst whil s T[ switch () { cas v1: s1,, cas vn: sn } ] t = T[ ] c = t!= v1 tjump c L2 T[ s1 ] jump Lnd labl L2 c = t!= v2 tjump c L3 T[ s2 ] jump Lnd labl LN c = t!= vn tjump c Lnd T[ sn ] v1 switch s1 vn sn CS 412/413 Spring 2008 Introduction to Compilrs 25 CS 412/413 Spring 2008 Introduction to Compilrs 26 Call and Rturn Statmnts Nstd Statmnts T[ call f(1, 2,, N) ] t1 = T[ 1 ] t2 = T[ 2 ] tn = T[ N ] call f(t1, t2,, tn) T[ rturn ] t = T[ ] rturn t call f 1 2 N rturn Sam for statmnts as xprssions: rcursiv translation Exampl: T[ if c thn if d thn a = b ] t1 = c fjump t1 Lnd1 t2 = d fjump t2 Lnd2 t3 = b T[ a = b ] a = t3 2 1 T[ if d ] T[ if c thn ] CS 412/413 Spring 2008 Introduction to Compilrs 27 CS 412/413 Spring 2008 Introduction to Compilrs 28

8 t1 = c fjump t1 Lnd1 t2 = d fjump t2 Lnd2 t3 = b a = t3 2 1 IR Lowring Efficincy c if-thn if-thn d a = b fjump c Lnd fjump d Lnd a = b Labl Lnd CS 412/413 Spring 2008 Introduction to Compilrs 29

Principles of Programming Languages Topic: Formal Languages II

Principles of Programming Languages Topic: Formal Languages II Principls of Programming Languags Topic: Formal Languags II CS 34,LS, LTM, BR: Formal Languags II Rviw A grammar can b ambiguous i.. mor than on pars tr for sam string of trminals in a PL w want to bas

More information

Midterm 2 - Solutions 1

Midterm 2 - Solutions 1 COS 26 Gnral Computr Scinc Spring 999 Midtrm 2 - Solutions. Writ a C function int count(char s[ ]) that taks as input a \ trminatd string and outputs th numbr of charactrs in th string (not including th

More information

Building a Scanner, Part I

Building a Scanner, Part I COMP 506 Ric Univrsity Spring 2018 Building a Scannr, Part I sourc cod IR Front End Optimizr Back End IR targt cod Copyright 2018, Kith D. Coopr & Linda Torczon, all rights rsrvd. Studnts nrolld in Comp

More information

Where we are. What makes a good IR? Intermediate Code. CS 4120 Introduction to Compilers

Where we are. What makes a good IR? Intermediate Code. CS 4120 Introduction to Compilers Where we are CS 4120 Introduction to Compilers Andrew Myers Cornell University Lecture 13: Intermediate Code 25 Sep 09 Source code (character stream) Token stream Abstract syntax tree Abstract syntax tree

More information

Objectives. Two Ways to Implement Lists. Lists. Chapter 24 Implementing Lists, Stacks, Queues, and Priority Queues

Objectives. Two Ways to Implement Lists. Lists. Chapter 24 Implementing Lists, Stacks, Queues, and Priority Queues Chaptr 24 Implmnting Lists, Stacks, Quus, and Priority Quus CS2: Data Structurs and Algorithms Colorado Stat Univrsity Original slids by Danil Liang Modifid slids by Chris Wilcox Objctivs q To dsign common

More information

Shift. Reduce. Review: Shift-Reduce Parsing. Bottom-up parsing uses two actions: Bottom-Up Parsing II. ABC xyz ABCx yz. Lecture 8.

Shift. Reduce. Review: Shift-Reduce Parsing. Bottom-up parsing uses two actions: Bottom-Up Parsing II. ABC xyz ABCx yz. Lecture 8. Rviw: Shift-Rduc Parsing Bottom-up parsing uss two actions: Bottom-Up Parsing II Lctur 8 Shift ABC xyz ABCx yz Rduc Cbxy ijk CbA ijk Prof. Aikn CS 13 Lctur 8 1 Prof. Aikn CS 13 Lctur 8 2 Rcall: h Stack

More information

Presentation for use with the textbook, Algorithm Design and Applications, by M. T. Goodrich and R. Tamassia, Wiley, Directed Graphs BOS SFO

Presentation for use with the textbook, Algorithm Design and Applications, by M. T. Goodrich and R. Tamassia, Wiley, Directed Graphs BOS SFO Prsntation for us with th txtbook, Algorithm Dsign and Applications, by M. T. Goodrich and R. Tamassia, Wily, 2015 Dirctd Graphs BOS ORD JFK SFO LAX DFW MIA 2015 Goodrich and Tamassia Dirctd Graphs 1 Digraphs

More information

The semantic WEB Roles of XML & RDF

The semantic WEB Roles of XML & RDF Th smantic WEB Rols of XML & RDF STEFAN DECKER AND SERGEY MELNIK FRANK VAN HARMELEN, DIETER FENSEL, AND MICHEL KLEIN JEEN BROEKSTRA MICHAEL ERDMANN IAN HORROCKS Prsntd by: Iniyai Thiruvalluvan CSCI586

More information

Recorder Variables. Defining Variables

Recorder Variables. Defining Variables Rcordr Variabls Dfining Variabls Simpl Typs Complx Typs List of Rsrvd Words Using Variabls Stting Action Paramtrs Parsing Lists and Tabls Gtting Valu from Lists and Tabls Using Indxs with Lists Using Indxs

More information

Register Allocation. Register Allocation

Register Allocation. Register Allocation Rgistr Allocation Jingk Li Portlan Stat Univrsity Jingk Li (Portlan Stat Univrsity) CS322 Rgistr Allocation 1 / 28 Rgistr Allocation Assign an unboun numbr of tmporaris to a fix numbr of rgistrs. Exampl:

More information

1. Trace the array for Bubble sort 34, 8, 64, 51, 32, 21. And fill in the following table

1. Trace the array for Bubble sort 34, 8, 64, 51, 32, 21. And fill in the following table 1. Trac th array for Bubbl sort 34, 8, 64, 51, 3, 1. And fill in th following tabl bubbl(intgr Array x, Intgr n) Stp 1: Intgr hold, j, pass; Stp : Boolan switchd = TRUE; Stp 3: for pass = 0 to (n - 1 &&

More information

IR Lowering. Notation. Lowering Methodology. Nested Expressions. Nested Statements CS412/CS413. Introduction to Compilers Tim Teitelbaum

IR Lowering. Notation. Lowering Methodology. Nested Expressions. Nested Statements CS412/CS413. Introduction to Compilers Tim Teitelbaum IR Lowering CS412/CS413 Introduction to Compilers Tim Teitelbaum Lecture 19: Efficient IL Lowering 7 March 07 Use temporary variables for the translation Temporary variables in the Low IR store intermediate

More information

CS412/CS413. Introduction to Compilers Tim Teitelbaum. Lecture 19: Efficient IL Lowering 5 March 08

CS412/CS413. Introduction to Compilers Tim Teitelbaum. Lecture 19: Efficient IL Lowering 5 March 08 CS412/CS413 Introduction to Compilers Tim Teitelbaum Lecture 19: Efficient IL Lowering 5 March 08 CS 412/413 Spring 2008 Introduction to Compilers 1 IR Lowering Use temporary variables for the translation

More information

Systems in Three Variables. No solution No point lies in all three planes. One solution The planes intersect at one point.

Systems in Three Variables. No solution No point lies in all three planes. One solution The planes intersect at one point. 3-5 Systms in Thr Variabls TEKS FOCUS VOCABULARY TEKS (3)(B) Solv systms of thr linar quations in thr variabls by using Gaussian limination, tchnology with matrics, and substitution. Rprsntation a way

More information

Problem Set 1 (Due: Friday, Sept. 29, 2017)

Problem Set 1 (Due: Friday, Sept. 29, 2017) Elctrical and Computr Enginring Mmorial Univrsity of Nwfoundland ENGI 9876 - Advancd Data Ntworks Fall 2017 Problm St 1 (Du: Friday, Spt. 29, 2017) Qustion 1 Considr a communications path through a packt

More information

CSE 272 Assignment 1

CSE 272 Assignment 1 CSE 7 Assignmnt 1 Kui-Chun Hsu Task 1: Comput th irradianc at A analytically (point light) For point light, first th nrgy rachd A was calculatd, thn th nrgy was rducd by a factor according to th angl btwn

More information

DO NOW Geometry Regents Lomac Date. due. Similar by Transformation 6.1 J'' J''' J'''

DO NOW Geometry Regents Lomac Date. due. Similar by Transformation 6.1 J'' J''' J''' DO NOW Gomtry Rgnts Lomac 2014-2015 Dat. du. Similar by Transformation 6.1 (DN) Nam th thr rigid transformations and sktch an xampl that illustrats ach on. Nam Pr LO: I can dscrib a similarity transformation,

More information

KENDRIYA VIDYALAYA SANGATHAN, CHENNAI REGION CLASS XII COMMON PRE-BOARD EXAMINATION

KENDRIYA VIDYALAYA SANGATHAN, CHENNAI REGION CLASS XII COMMON PRE-BOARD EXAMINATION KENDRIYA VIDYALAYA SANGATHAN, CHENNAI REGION CLASS XII COMMON PRE-BOARD EXAMINATION 03-4 Sub : Informatics Practics (065) Tim allowd : 3 hours Maximum Marks : 70 Instruction : (i) All qustions ar compulsory

More information

Greedy Algorithms. Interval Scheduling. Greedy Algorithm. Optimality. Greedy Algorithm (cntd) Greed is good. Greed is right. Greed works.

Greedy Algorithms. Interval Scheduling. Greedy Algorithm. Optimality. Greedy Algorithm (cntd) Greed is good. Greed is right. Greed works. Algorithm Grdy Algorithm 5- Grdy Algorithm Grd i good. Grd i right. Grd work. Wall Strt Data Structur and Algorithm Andri Bulatov Algorithm Grdy Algorithm 5- Algorithm Grdy Algorithm 5- Intrval Schduling

More information

I - Pre Board Examination

I - Pre Board Examination Cod No: S-080 () Total Pags: 06 KENDRIYA VIDYALAYA SANGATHAN,GUWHATI REGION I - Pr Board Examination - 04-5 Subjct Informatics Practics (Thory) Class - XII Tim: 3 hours Maximum Marks : 70 Instruction :

More information

" dx v(x) $ % You may also have seen this written in shorthand form as. & ' v(x) + u(x) '# % ! d

 dx v(x) $ % You may also have seen this written in shorthand form as. & ' v(x) + u(x) '# % ! d Calculus II MAT 146 Mthods of Intgration: Intgration by Parts Just as th mthod of substitution is an intgration tchniqu that rvrss th drivativ procss calld th chain rul, Intgration by parts is a mthod

More information

Comment (justification for change) by the MB

Comment (justification for change) by the MB Editor's disposition s CD2 19763-12 as at 2013-11-03 Srial Annx (.g. 3.1) Figur/ Tabl/t (.g. Tabl 1) 001 CA 00 All All - G Canada disapprovs th draft for th rasons blow. 002 GB 01 Gnral d numbring has

More information

Outline. Tasks for Exercise Six. Exercise Six Goals. Task One: Kinetic Energy Table. Nested for Loops. Laboratory VI Program Control Using Loops

Outline. Tasks for Exercise Six. Exercise Six Goals. Task One: Kinetic Energy Table. Nested for Loops. Laboratory VI Program Control Using Loops Ercis 6 -- Loopig March 9, 6 Laboratory VI Program Cotrol Usig Loops Larry Cartto Computr Scic 6 Computig i Egirig ad Scic Outli Ercis si goals Outli tasks for rcis si Itroduc ida of std loops ad tabl

More information

8.3 INTEGRATION BY PARTS

8.3 INTEGRATION BY PARTS 8.3 Intgration By Parts Contmporary Calculus 8.3 INTEGRATION BY PARTS Intgration by parts is an intgration mthod which nabls us to find antidrivativs of som nw functions such as ln(x) and arctan(x) as

More information

Gernot Hoffmann Sphere Tessellation by Icosahedron Subdivision. Contents

Gernot Hoffmann Sphere Tessellation by Icosahedron Subdivision. Contents Grnot Hoffmann Sphr Tssllation by Icosahdron Subdivision Contnts 1. Vrtx Coordinats. Edg Subdivision 3 3. Triangl Subdivision 4 4. Edg lngths 5 5. Normal Vctors 6 6. Subdividd Icosahdrons 7 7. Txtur Mapping

More information

The Network Layer: Routing Algorithms. The Network Layer: Routing & Addressing Outline

The Network Layer: Routing Algorithms. The Network Layer: Routing & Addressing Outline PS 6 Ntwork Programming Th Ntwork Layr: Routing lgorithms Michl Wigl partmnt of omputr Scinc lmson Univrsity mwigl@cs.clmson.du http://www.cs.clmson.du/~mwigl/courss/cpsc6 Th Ntwork Layr: Routing & ddrssing

More information

CPSC 826 Internetworking. The Network Layer: Routing & Addressing Outline. The Network Layer: Routing Algorithms. Routing Algorithms Taxonomy

CPSC 826 Internetworking. The Network Layer: Routing & Addressing Outline. The Network Layer: Routing Algorithms. Routing Algorithms Taxonomy PS Intrntworking Th Ntwork Layr: Routing & ddrssing Outlin Th Ntwork Layr: Routing lgorithms Michl Wigl partmnt of omputr Scinc lmson Univrsity mwigl@cs.clmson.du Novmbr, Ntwork layr functions Routr architctur

More information

Three-address code (TAC) TDT4205 Lecture 16

Three-address code (TAC) TDT4205 Lecture 16 1 Three-address code (TAC) TDT4205 Lecture 16 2 On our way toward the bottom We have a gap to bridge: Words Grammar Source program Semantics Program should do the same thing on all of these, but they re

More information

Polygonal Models. Overview. Simple Data Structures. David Carr Fundamentals of Computer Graphics Spring 2004 Based on Slides by E.

Polygonal Models. Overview. Simple Data Structures. David Carr Fundamentals of Computer Graphics Spring 2004 Based on Slides by E. INSTITUTIONEN FÖR SYSTEMTEKNIK LULEÅ TEKNISKA UNIVERSITET Polygonal Modls David Carr Fundamntals of Computr Graphics Spring 200 Basd on Slids by E. Angl Fb-3-0 SMD159, Polygonal Modls 1 L Ovrviw Simpl

More information

EE 231 Fall EE 231 Homework 10 Due November 5, 2010

EE 231 Fall EE 231 Homework 10 Due November 5, 2010 EE 23 Fall 2 EE 23 Homwork Du Novmbr 5, 2. Dsign a synhronous squntial iruit whih gnrats th following squn. (Th squn should rpat itslf.) (a) Draw a stat transition diagram for th iruit. This is a systm

More information

Chapter 6: Synthesis of Combinatorial and. Sequential Logic. What is synthesis?

Chapter 6: Synthesis of Combinatorial and. Sequential Logic. What is synthesis? Chaptr 6: Synthsis of Combinatorial and What is synthsis? Squntial Logic Synthsis is th mapping of your cod to a mixtur of logic gats and rgistrs. Th availabl logic gats and rgistrs ar dtrmind from th

More information

TypeCastor: Demystify Dynamic Typing of JavaScript Applications

TypeCastor: Demystify Dynamic Typing of JavaScript Applications TypCastor: Dmystify Dynamic Typing of JavaScript Applications Shishng Li China Runtim Tch Cntr Intl China Rsarch Cntr Bijing, China shishng.li@intl.com Buqi Chng China Runtim Tch Cntr Intl China Rsarch

More information

Intermediate Representations

Intermediate Representations Intermediate Representations A variety of intermediate representations are used in compilers Most common intermediate representations are: Abstract Syntax Tree Directed Acyclic Graph (DAG) Three-Address

More information

Interfacing the DP8420A 21A 22A to the AN-538

Interfacing the DP8420A 21A 22A to the AN-538 Intrfacing th DP8420A 21A 22A to th 68000 008 010 INTRODUCTION This application not xplains intrfacing th DP8420A 21A 22A DRAM controllr to th 68000 Thr diffrnt dsigns ar shown and xplaind It is assumd

More information

Lightweight Polymorphic Effects

Lightweight Polymorphic Effects Lightwight Polymorphic Effcts Lukas Rytz, Martin Odrsky, and Philipp Hallr EPFL, Switzrland, {first.last}@pfl.ch Abstract. Typ-and-ffct systms ar a wll-studid approach for rasoning about th computational

More information

Announcements. q This week s schedule. q Next week. q Grading. n Wednesday holiday. n Thursday class from am

Announcements. q This week s schedule. q Next week. q Grading. n Wednesday holiday. n Thursday class from am Announcmnts This wk s schdul n Wdnsday holiday n Thursday class from 9.00-0.30am Nxt wk n Monday and Tusday rgular class n Wdnsday Last uiz for th cours Grading n Quiz 5, 6 and Lab 6 ar du. Applications

More information

Combining Intra- and Multi-sentential Rhetorical Parsing for Document-level Discourse Analysis

Combining Intra- and Multi-sentential Rhetorical Parsing for Document-level Discourse Analysis Combining Intra- and Multi-sntntial htorical Parsing for Documnt-lvl Discours Analysis hafiq Joty Giuspp Carnini, aymond T. Ng, Yashar Mhdad sjoty@qf.org.qa {carnini, rng, mhdad}@cs.ubc.ca Qatar Computing

More information

Probabilistic inference

Probabilistic inference robabilistic infrnc Suppos th agnt has to mak a dcision about th valu of an unobsrvd qury variabl X givn som obsrvd vidnc E = artially obsrvabl, stochastic, pisodic nvironmnt Eampls: X = {spam, not spam},

More information

SPECIFIC CRITERIA FOR THE GENERAL MOTORS GLOBAL TRADING PARTNER LABEL TEMPLATE:

SPECIFIC CRITERIA FOR THE GENERAL MOTORS GLOBAL TRADING PARTNER LABEL TEMPLATE: SPCIFIC CRITRIA FOR TH GNRAL MOTORS GLOBAL TRADING PARTNR LABL TMPLAT: TH TMPLAT IDNTIFIS HOW AND WHR DATA IS TO B PLACD ON TH LABL WHN IT IS RQUIRD AS PART OF A GM BUSINSS RQUIRMNT FONT SIZS AR SPCIFID

More information

Vignette to package samplingdatacrt

Vignette to package samplingdatacrt Vigntt to packag samplingdatacrt Diana Trutschl Contnts 1 Introduction 1 11 Objctiv 1 1 Diffrnt study typs 1 Multivariat normal distributd data for multilvl data 1 Fixd ffcts part Random part 9 3 Manual

More information

September 19, Some formal bits. 1.2 Lambda notation. 1.1 Type theory. Instead of writing the following... f : for all x, f(x) = Φ

September 19, Some formal bits. 1.2 Lambda notation. 1.1 Type theory. Instead of writing the following... f : for all x, f(x) = Φ Sptmbr 19, 2014 1 Som formal bits 1.2 Lambda notation Instad of writing th following... f : for all x, f(x) = Φ 1.1 Typ thory An xprssion s typ tlls you a numbr of things: W will writ th following: λx.φ

More information

CMa simple C Abstract Machine

CMa simple C Abstract Machine CMa simple C Abstract Machine CMa architecture An abstract machine has set of instructions which can be executed in an abstract hardware. The abstract hardware may be seen as a collection of certain data

More information

SPECKLE NOISE REDUCTION IN SAR IMAGING USING 2-D LATTICE FILTERS BASED SUBBAND DECOMPOSITION

SPECKLE NOISE REDUCTION IN SAR IMAGING USING 2-D LATTICE FILTERS BASED SUBBAND DECOMPOSITION 7th Europan Signal Procssing Confrnc EUSIPCO 9 Glasgow Scotland August 4-8 9 SPECKLE REDUCTION IN SAR IMAGING USING -D LATTICE FILTERS ASED SUAND DECOMPOSITION Göhan Karasaal N.. Kaplan I. Err Informatics

More information

Ray Tracing. Wen-Chieh (Steve) Lin National Chiao-Tung University

Ray Tracing. Wen-Chieh (Steve) Lin National Chiao-Tung University Ra Tracing Wn-Chih (Stv Lin National Chiao-Tung Univrsit Shirl, Funamntals of Computr Graphics, Chap 15 I-Chn Lin s CG slis, Doug Jams CG slis Can W Rnr Imags Lik Ths? Raiosit imag Pictur from http://www.graphics.cornll.u/onlin/ralistic/

More information

A New Algorithm for Solving Shortest Path Problem on a Network with Imprecise Edge Weight

A New Algorithm for Solving Shortest Path Problem on a Network with Imprecise Edge Weight Availabl at http://pvamudu/aam Appl Appl Math ISSN: 193-9466 Vol 6, Issu (Dcmbr 011), pp 60 619 Applications and Applid Mathmatics: An Intrnational Journal (AAM) A Nw Algorithm for Solving Shortst Path

More information

Workbook for Designing Distributed Control Applications using Rockwell Automation s HOLOBLOC Prototyping Software John Fischer and Thomas O.

Workbook for Designing Distributed Control Applications using Rockwell Automation s HOLOBLOC Prototyping Software John Fischer and Thomas O. Workbook for Dsigning Distributd Control Applications using Rockwll Automation s HOLOBLOC Prototyping Softwar John Fischr and Thomas O. Bouchr Working Papr No. 05-017 Introduction A nw paradigm for crating

More information

Design Methodologies and Tools

Design Methodologies and Tools Dsign Mthodologis and Tools Dsign styls Full-custom dsign Standard-cll dsign Programmabl logic Gat arrays and fild-programmabl gat arrays (FPGAs) Sa of gats Systm-on-a-chip (mbddd cors) Dsign tools 1 Full-Custom

More information

Nimsoft Monitor. ldap_response Guide. v1.3 series

Nimsoft Monitor. ldap_response Guide. v1.3 series Nimsoft Monitor ldap_rspons Guid v1.3 sris Lgal Notics Copyright 2012, Nimsoft Corporation Warranty Th matrial containd in this documnt is providd "as is," and is subjct to bing changd, without notic,

More information

2 Mega Pixel. HD-SDI Bullet Camera. User Manual

2 Mega Pixel. HD-SDI Bullet Camera. User Manual 2 Mga Pixl HD-SDI Bullt Camra Usr Manual Thank you for purchasing our product. This manual is only applicabl to SDI bullt camras. Thr may b svral tchnically incorrct placs or printing rrors in this manual.

More information

2018 How to Apply. Application Guide. BrandAdvantage

2018 How to Apply. Application Guide. BrandAdvantage 2018 How to Apply Application Guid BrandAdvantag Contnts Accssing th Grant Sit... 3 Wlcom pag... 3 Logging in To Pub Charity... 4 Rgistration for Nw Applicants ( rgistr now )... 5 Organisation Rgistration...

More information

LAB1: DMVPN Theory. DMVPN Theory. Disclaimer. Pag e

LAB1: DMVPN Theory. DMVPN Theory. Disclaimer. Pag e LAB1: DMVPN Thory Disclaimr This Configuration Guid is dsignd to assist mmbrs to nhanc thir skills in rspctiv tchnology ara. Whil vry ffort has bn mad to nsur that all matrial is as complt and accurat

More information

Languages and Compiler Design II IR Code Generation I

Languages and Compiler Design II IR Code Generation I Languages and Compiler Design II IR Code Generation I Material provided by Prof. Jingke Li Stolen with pride and modified by Herb Mayer PSU Spring 2010 rev.: 4/16/2010 PSU CS322 HM 1 Agenda Grammar G1

More information

A Decision Procedure for a Class of Set Constraints

A Decision Procedure for a Class of Set Constraints A Dcision Procdur for a Class of St Constraints (Extndd A bst rad) Nvin Hintz School of Conputr Scinc Carngi Mllon Univrsity Pittsburgh, PA 15213 (nch @cs.cmu.du) Joxan Jaffar IBM T. J. Watson Rsarch Cntr

More information

LAB 3: DMVPN EIGRP. EIGRP over DMVPN. Disclaimer. Pag e

LAB 3: DMVPN EIGRP. EIGRP over DMVPN. Disclaimer. Pag e LAB 3: DMVPN EIGRP Disclaimr This Configuration Guid is dsignd to assist mmbrs to nhanc thir skills in rspctiv tchnology ara. Whil vry ffort has bn mad to nsur that all matrial is as complt and accurat

More information

Spectral sensitivity and color formats

Spectral sensitivity and color formats FirWir camras Spctral snsitivity and color formats At th "input" of a camra, w hav a CCD chip. It transforms photons into lctrons. Th spctral snsitivity of this transformation is an important charactristic

More information

We ve written these as a grammar, but the grammar also stands for an abstract syntax tree representation of the IR.

We ve written these as a grammar, but the grammar also stands for an abstract syntax tree representation of the IR. CS 4120 Lecture 14 Syntax-directed translation 26 September 2011 Lecturer: Andrew Myers We want to translate from a high-level programming into an intermediate representation (IR). This lecture introduces

More information

Between Testing and Formal Verification

Between Testing and Formal Verification Btwn Tsting and Formal Vrification Jan Tobias Mühlbrg jantobias.muhlbrg@cs.kuluvn.b imc-distrint, KU Luvn, Clstijnnlaan 200A, B-3001 Blgium ScAppDv, Luvn, March 2017 1 /19 Jan Tobias Mühlbrg Btwn Tsting

More information

Extending z/tpf using IBM API Management (APIM)

Extending z/tpf using IBM API Management (APIM) Extnding using API Managmnt (APIM) Mark Gambino, TPF Dvlopmnt Lab March 23, 2015 TPFUG Dallas, TX Th Big Pictur Goal Mobil Applications Cloud APIs Cloud-basd Srvics On-Prmis Entrpris APIs E n t r p r I

More information

i e ai E ig e v / gh E la ES h E A X h ES va / A SX il E A X a S

i e ai E ig e v / gh E la ES h E A X h ES va / A SX il E A X a S isto C o C or Co r op ra p a py ag yr g ri g g gh ht S S S V V K r V K r M K v M r v M rn v MW n W S r W Sa r W K af r: W K f : a H a M r T H r M rn w T H r Mo ns w T i o S ww c ig on a w c g nd af ww

More information

Compiler Construction I

Compiler Construction I TECHNISCHE UNIVERSITÄT MÜNCHEN FAKULTÄT FÜR INFORMATIK Compiler Construction I Dr. Michael Petter, Dr. Axel Simon SoSe 2014 1 / 104 Topic: Semantic Analysis 2 / 104 Topic: Code Synthesis 3 / 104 Generating

More information

DTRB Editor, Support Software for Cell Master

DTRB Editor, Support Software for Cell Master X903594 Vr.1.0 DTRB Editor, Support Softar for Cll Mastr DTRBP-SW-HTC Onr s Manual Vr.1.0 Contnts Chaptr 1 Installation Guid 1. Introduction 1 1-1 Nots 2 1-2 What Is DTRB Editor? 2 1-3 What Is Includd

More information

Multihop MIMO Relay Networks with ARQ

Multihop MIMO Relay Networks with ARQ Multihop MIMO Rlay Ntworks with ARQ Yao Xi Dniz Gündüz Andra Goldsmith Dpartmnt of Elctrical Enginring Stanford Univrsity Stanford CA Dpartmnt of Elctrical Enginring Princton Univrsity Princton NJ Email:

More information

On Some Maximum Area Problems I

On Some Maximum Area Problems I On Som Maximum Ara Problms I 1. Introdution Whn th lngths of th thr sids of a triangl ar givn as I 1, I and I 3, thn its ara A is uniquly dtrmind, and A=s(s-I 1 )(s-i )(s-i 3 ), whr sis th smi-primtr t{i

More information

Code generation scheme for RCMA

Code generation scheme for RCMA Code generation scheme for RCMA Axel Simon July 5th, 2010 1 Revised Specification of the R-CMa We detail what constitutes the Register C-Machine (R-CMa ) and its operations in turn We then detail how the

More information

Evolutionary Clustering and Analysis of Bibliographic Networks

Evolutionary Clustering and Analysis of Bibliographic Networks Evolutionary Clustring and Analysis of Bibliographic Ntworks Manish Gupta Univrsity of Illinois at Urbana-Champaign gupta58@illinois.du Charu C. Aggarwal IBM T. J. Watson Rsarch Cntr charu@us.ibm.com Jiawi

More information

Motivation. Synthetic OOD concepts and reuse Lecture 4: Separation of concerns. Problem. Solution. Deleting composites that share parts. Or is it?

Motivation. Synthetic OOD concepts and reuse Lecture 4: Separation of concerns. Problem. Solution. Deleting composites that share parts. Or is it? Synthtic OOD concpts and rus Lctur 4: Sparation of concrns Topics: Complx concrn: Mmory managmnt Exampl: Complx oprations on composit structurs Problm: Mmory laks Solution: Rfrnc counting Motivation Suppos

More information

CS606- compiler instruction Solved MCQS From Midterm Papers

CS606- compiler instruction Solved MCQS From Midterm Papers CS606- compiler instruction Solved MCQS From Midterm Papers March 06,2014 MC100401285 Moaaz.pk@gmail.com Mc100401285@gmail.com PSMD01 Final Term MCQ s and Quizzes CS606- compiler instruction If X is a

More information

: Mesh Processing. Chapter 6

: Mesh Processing. Chapter 6 600.657: Msh Procssing Chaptr 6 Quad-Dominant Rmshing Goal: Gnrat a rmshing of th surfac that consists mostly of quads whos dgs align with th principal curvatur dirctions. [Marinov t al. 04] [Alliz t al.

More information

To Do. Advanced Computer Graphics. Motivation. Mesh Data Structures. Outline. Mesh Data Structures. Desirable Characteristics 1

To Do. Advanced Computer Graphics. Motivation. Mesh Data Structures. Outline. Mesh Data Structures. Desirable Characteristics 1 Advancd Computr Graphics CSE 63 [Spring 208], Lctur 7 Ravi Ramamoorthi http://www.cs.ucsd.du/~ravir To Do Assignmnt, Du Apr 27 Any last minut issus or difficultis? Starting Gomtry Procssing Assignmnt 2

More information

Ontology and Context. Isabel Cafezeiro Departamento de Ciência da Computação Universidade Federal Fluminense Niterói - RJ, Brazil

Ontology and Context. Isabel Cafezeiro Departamento de Ciência da Computação Universidade Federal Fluminense Niterói - RJ, Brazil Ontology and Contxt Isabl Cafziro Dpartamnto d Ciência da Computação Univrsidad Fdral Fluminns Nitrói - RJ, Brazil isabl@dcc.ic.uff.br dward Hrmann Hauslr, Alxandr Radmakr Dpartamnto d Informática Pontifícia

More information

Linked Data meet Sensor Networks

Linked Data meet Sensor Networks Digital Entrpris Rsarch Institut www.dri.i Linkd Data mt Snsor Ntworks Myriam Lggiri DERI NUI Galway, Irland Copyright 2008 Digital Entrpris Rsarch Institut. All rights rsrvd. Linkd Data mt Snsor Ntworks

More information

Space Subdivision Algorithms for Ray Tracing

Space Subdivision Algorithms for Ray Tracing Spac Subdivision Algorithms for Ray Tracing by David MacDonald A thsis prsntd to th Univrsity of Watrloo in fulfillmnt of th thsis rquirmnt for th dgr of Mastr of Mathmatics in Computr Scinc Watrloo, Ontario,

More information

Formal Foundation, Approach, and Smart Tool for Software Models Comparison

Formal Foundation, Approach, and Smart Tool for Software Models Comparison Formal Foundation, Approach, and Smart Tool for Softwar Modls Comparison Olna V. Chbanyuk, Abdl-Badh M. Salm Softwar Enginring Dpartmnt, National Aviation Univrsity, Kyiv, Ukrain Computr Scinc, Faculty

More information

To Do. Mesh Data Structures. Mesh Data Structures. Motivation. Outline. Advanced Computer Graphics (Fall 2010) Desirable Characteristics 1

To Do. Mesh Data Structures. Mesh Data Structures. Motivation. Outline. Advanced Computer Graphics (Fall 2010) Desirable Characteristics 1 Advancd Computr Graphics (Fall 200) CS 283, Lctur 5: Msh Data Structurs Ravi Ramamoorthi http://inst.cs.brkly.du/~cs283/fa0 To Do Assignmnt, Du Oct 7. Start rading and working on it now. Som parts you

More information

SPECIFIC CRITERIA FOR THE GENERAL MOTORS GLOBAL TRADING PARTNER LABEL TEMPLATE:

SPECIFIC CRITERIA FOR THE GENERAL MOTORS GLOBAL TRADING PARTNER LABEL TEMPLATE: SPCIFIC CRITRIA FOR TH GNRAL MOTORS GLOBAL TRADING PARTNR LABL TMPLAT: TH TMPLAT IDNTIFIS HOW AND WHR DATA IS TO B PLACD ON TH LABL WHN IT IS RQUIRD AS PART OF A GM BUSINSS RQUIRMNT FONT SIZS AR SPCIFID

More information

Robust and Fault Tolerant Clock Synchronization Nikolaus Kerö, Oregano Systems Aneeq Mahmood, ZISS Thomas Kernen, Cisco Felix Ring, ZISS Tobias

Robust and Fault Tolerant Clock Synchronization Nikolaus Kerö, Oregano Systems Aneeq Mahmood, ZISS Thomas Kernen, Cisco Felix Ring, ZISS Tobias Robust and Fault Tolrant Clock Synchronization Nikolaus Krö, Organo Systms Anq Mahmood, ZISS Thomas Krnn, Cisco Flix Ring, ZISS Tobias Müllr, Organo Systms Thomas Biglr, ZISS Rational Common notion of

More information

Forward and Inverse Kinematic Analysis of Robotic Manipulators

Forward and Inverse Kinematic Analysis of Robotic Manipulators Forward and Invrs Kinmatic Analysis of Robotic Manipulators Tarun Pratap Singh 1, Dr. P. Sursh 2, Dr. Swt Chandan 3 1 M.TECH Scholar, School Of Mchanical Enginring, GALGOTIAS UNIVERSITY, GREATER NOIDA,

More information

TACi: Three-Address Code Interpreter (version 1.0)

TACi: Three-Address Code Interpreter (version 1.0) TACi: Three-Address Code Interpreter (version 1.0) David Sinclair September 23, 2018 1 Introduction TACi is an interpreter for Three-Address Code, the common intermediate representation (IR) used in compilers.

More information

Video Representation. Luminance and Chrominance. Television - NTSC

Video Representation. Luminance and Chrominance. Television - NTSC Vido Rprsntation Chaptr 2: Rprsntation of Multimdia Data Audio Tchnology mags and Graphics Vido Tchnology Chaptr 3: Multimdia Systms Communication Aspcts and Srvics Chaptr 4: Multimdia Systms Storag Aspcts

More information

CPSC 411, Fall 2010 Midterm Examination

CPSC 411, Fall 2010 Midterm Examination CPSC 411, Fall 2010 Midterm Examination. Page 1 of 11 CPSC 411, Fall 2010 Midterm Examination Name: Q1: 10 Q2: 15 Q3: 15 Q4: 10 Q5: 10 60 Please do not open this exam until you are told to do so. But please

More information

To Do. Advanced Computer Graphics. Motivation. Mesh Data Structures. Outline. Mesh Data Structures. Desirable Characteristics 1

To Do. Advanced Computer Graphics. Motivation. Mesh Data Structures. Outline. Mesh Data Structures. Desirable Characteristics 1 Advancd Computr Graphics CSE 63 [Spring 207], Lctur 7 Ravi Ramamoorthi http://www.cs.ucsd.du/~ravir To Do Assignmnt, Du Apr 28 Any last minut issus or difficultis? Starting Gomtry Procssing Assignmnt 2

More information

EDI Specifications Guide. 850 Supplier Purchase Order Last Updated February 2017

EDI Specifications Guide. 850 Supplier Purchase Order Last Updated February 2017 EDI Spcifications Guid 850 Supplir Purchas Ordr Last Updatd Fbruary 2017 EDI Spcifications Guid 850 Purchas Ordr - Functional Group=PO VER. 4010 FISHER SCIENTIFIC This Standard contains th format and stablishs

More information

CS412/CS413. Introduction to Compilers Tim Teitelbaum. Lecture 21: Generating Pentium Code 10 March 08

CS412/CS413. Introduction to Compilers Tim Teitelbaum. Lecture 21: Generating Pentium Code 10 March 08 CS412/CS413 Introduction to Compilers Tim Teitelbaum Lecture 21: Generating Pentium Code 10 March 08 CS 412/413 Spring 2008 Introduction to Compilers 1 Simple Code Generation Three-address code makes it

More information

1 Lexical Considerations

1 Lexical Considerations Massachusetts Institute of Technology Department of Electrical Engineering and Computer Science 6.035, Spring 2013 Handout Decaf Language Thursday, Feb 7 The project for the course is to write a compiler

More information

[MS-OXRTFEX]: Rich Text Format (RTF) Extensions Algorithm. Intellectual Property Rights Notice for Open Specifications Documentation

[MS-OXRTFEX]: Rich Text Format (RTF) Extensions Algorithm. Intellectual Property Rights Notice for Open Specifications Documentation [MS-OXRTFEX]: Intllctual Proprty Rights Notic for Opn Spcifications Documntation Tchnical Documntation. Microsoft publishs Opn Spcifications documntation ( this documntation ) for protocols, fil formats,

More information

TCP Congestion Control. Congestion Avoidance

TCP Congestion Control. Congestion Avoidance TCP Congstion Control TCP sourcs chang th snding rat by modifying th window siz: Window = min {Advrtisd window, Congstion Window} Rcivr Transmittr ( cwnd ) In othr words, snd at th rat of th slowst componnt:

More information

Prof. Mohamed Hamada Software Engineering Lab. The University of Aizu Japan

Prof. Mohamed Hamada Software Engineering Lab. The University of Aizu Japan Language Processing Systems Prof. Mohamed Hamada Software ngineering Lab. The University of Aizu Japan Intermediate/Code Generation Source language Scanner (lexical analysis) tokens Parser (syntax analysis)

More information

Compositional specification of commercial contracts

Compositional specification of commercial contracts Int J Softw Tools Tchnol Transfr DOI 10.1007/s10009-006-0010-1 SPECIAL SECTION ON LEVERAGING APPLICATIONS OF FORMAL METHODS Compositional spcification of commrcial contracts Jspr Andrsn Ebb Elsborg Fritz

More information

COMPILER (CSE 4120) (Lecture 6: Parsing 4 Bottom-up Parsing )

COMPILER (CSE 4120) (Lecture 6: Parsing 4 Bottom-up Parsing ) COMPILR (CS 4120) (Lecture 6: Parsing 4 Bottom-up Parsing ) Sungwon Jung Mobile Computing & Data ngineering Lab Dept. of Computer Science and ngineering Sogang University Seoul, Korea Tel: +82-2-705-8930

More information

About Notes And Symbols

About Notes And Symbols About Nots And Symbols by Batric Wildr Contnts Sht 1 Sht 2 Sht 3 Sht 4 Sht 5 Sht 6 Sht 7 Sht 8 Sht 9 Sht 10 Sht 11 Sht 12 Sht 13 Sht 14 Sht 15 Sht 16 Sht 17 Sht 18 Sht 19 Sht 20 Sht 21 Sht 22 Sht 23 Sht

More information

The Size of the 3D Visibility Skeleton: Analysis and Application

The Size of the 3D Visibility Skeleton: Analysis and Application Th Siz of th 3D Visibility Sklton: Analysis and Application Ph.D. thsis proposal Linqiao Zhang lzhang15@cs.mcgill.ca School of Computr Scinc, McGill Univrsity March 20, 2008 thsis proposal: Th Siz of th

More information

Principles for Computer System Design

Principles for Computer System Design Principls for Computr Systm Dsign 10 yars ago: Hints for Computr Systm Dsign Not that much larnd sinc thn disappointing Instad of standing on ach othr s shouldrs, w stand on ach othr s tos. (Hamming) On

More information

Descriptors story. talented developers flexible teams agile experts. Adrian Dziubek - EuroPython

Descriptors story. talented developers flexible teams agile experts. Adrian Dziubek - EuroPython Dscriptors story talntd dvloprs flxibl tams agil xprts Adrian Dziubk - EuroPython - 2016-07-18 m t u o b A Adrian Dziubk Snior Python dvlopr at STX Nxt in Wrocław, Crating wb applications using Python

More information

Compiler Construction I

Compiler Construction I TECHNISCHE UNIVERSITÄT MÜNCHEN FAKULTÄT FÜR INFORMATIK Compiler Construction I Dr. Michael Petter, Dr. Axel Simon SoSe 2013 1 / 108 Organizing Master or Bachelor in the 6th Semester with 5 ECTS Prerequisites

More information

AN EVALUATION MODEL FOR THE CHAINS OF DISTRIBUTED MULTIMEDIA INDEXING TOOLS RESPECTING USER PREFERENCES

AN EVALUATION MODEL FOR THE CHAINS OF DISTRIBUTED MULTIMEDIA INDEXING TOOLS RESPECTING USER PREFERENCES AN EVALUATION MODEL FOR THE CHAINS OF DISTRIBUTED MULTIMEDIA INDEXING TOOLS RESPECTING USER PREFERENCES 1 Bassm HAIDAR, 2 Bilal CHEBARO, 3 Hassan WEHBI 1 Asstt Prof., Dpartmnt of Computr Scincs, Faculty

More information

Semantic analysis and intermediate representations. Which methods / formalisms are used in the various phases during the analysis?

Semantic analysis and intermediate representations. Which methods / formalisms are used in the various phases during the analysis? Semantic analysis and intermediate representations Which methods / formalisms are used in the various phases during the analysis? The task of this phase is to check the "static semantics" and generate

More information

A positional container ("pcontainer" for short) is a generic container that is organized by position, which means

A positional container (pcontainer for short) is a generic container that is organized by position, which means Chaptr: Gnric Positional Containrs and Doul Endd Quus Gnric Positional Containrs A positional containr is a gnric containr that stors lmnts y position at th discrtion of a clint. For xampl, a vctor stors

More information

Terrain Mapping and Analysis

Terrain Mapping and Analysis Trrain Mapping and Analysis Data for Trrain Mapping and Analysis Digital Trrain Modl (DEM) DEM rprsnts an array of lvation points. Th quality of DEM influncs th accuracy of trrain masurs such as slop and

More information

LAB 4: DMVPN OSPF. OSPF over DMVPN. Disclaimer. Pag e

LAB 4: DMVPN OSPF. OSPF over DMVPN. Disclaimer. Pag e LAB 4: DMVPN OSPF Disclaimr This Configuration Guid is dsignd to assist mmbrs to nhanc thir skills in rspctiv tchnology ara. Whil vry ffort has bn mad to nsur that all matrial is as complt and accurat

More information

Chapter 3: Describing Syntax and Semantics. Introduction Formal methods of describing syntax (BNF)

Chapter 3: Describing Syntax and Semantics. Introduction Formal methods of describing syntax (BNF) Chapter 3: Describing Syntax and Semantics Introduction Formal methods of describing syntax (BNF) We can analyze syntax of a computer program on two levels: 1. Lexical level 2. Syntactic level Lexical

More information