A Functorial Query Language

Size: px
Start display at page:

Download "A Functorial Query Language"

Transcription

1 A Funtoril Query Lnguge Ryn Wisnesky, Dvid Spivk Deprtment of Mthemtis Msshusetts Institute of Tehnology {wisnesky, Presented t Boston Hskell April 16, 2014

2 Outline Introdution to FQL. FQL is dtse query lnguge sed on tegory theory. But, there will e no tegory theory in this tlk. How to progrm FQL using Hskell. FQL provides n lterntive semntis for Hskell progrms. If you n progrm Hskell, you n progrm FQL. Demo of the FQL E. Projet wepge: tegorildt.net/fql.html 2 / 30

3 Introdution to FQL In FQL, dtse shem is speil kind of entity-reltionship (ER) digrm. mnger Emp worksin seretry Dept first lst nme Emp.mnger.worksIn Emp.worksIn Emp mgr works first lst q10 Al Akin x02 Bo Bo q10 Crl Cork Dept.seretry.worksIn Dept Dept se nme q CS x Mth 3 / 30

4 Introdution to FQL mnger Emp worksin seretry Dept first lst nme Emp.mnger.worksIn Emp.worksIn Dept.seretry.worksIn Dept Eh lk node represents n entity set (of s). Eh direted edge represents foreign key. Eh open irle represent n ttriute. Dt integrity onstrints re pth equlities. Dt is stored s tles in the ovious wy. 4 / 30

5 Why FQL? FQL is lnguge for mnipulting the shems nd instnes just defined. But you n lso mnipulte suh shems nd instnes using SQL. We ssert tht, euse of its tegoril roots, FQL is etter lnguge for doing so. FQL is dtse t time, not tle t time. FQL opertions neessrily respet onstrints. Unlike SQL, FQL is expressive enough to e used for informtion integrtion (see ppers). Prts of FQL n run on SQL, nd vie vers. 5 / 30

6 FQL Bsis A shem mpping F : S Ñ T is onstrint-respeting mpping: nodespsq Ñ nodespt q edgespsq Ñ pthspt q nd it indues three dt migrtion opertions: F : T -inst Ñ S-inst (like projetion) ΣF : S-inst Ñ T -inst (like union) ΠF : S-inst Ñ T -inst (like join) 6 / 30

7 (Projet) Nme Nme Slry N1 N2 F ÝÝÝÑ N Slry Age Age N1 Nme Slry 1 Bo $250 2 Sue $300 3 Alie $100 N2 Age F ÐÝÝ N Nme Age Slry 1 Bo 20 $250 2 Sue 20 $300 3 Alie 30 $100 7 / 30

8 Π (Join) Nme Nme Slry N1 N2 F ÝÝÝÑ N Slry Age Age N1 Nme Slry 1 Bo $250 2 Sue $300 3 Alie $100 N2 Age Π F ÝÝÑ N Nme Age Slry 1 Alie 20 $100 2 Alie 20 $100 3 Alie 30 $100 4 Bo 20 $250 5 Bo 20 $250 6 Bo 30 $250 7 Sue 20 $300 8 Sue 20 $300 9 Sue 30 $300 8 / 30

9 Σ (Union) Nme Nme Slry N1 N2 F ÝÝÝÑ N Slry Age Age N1 Nme Slry 1 Bo $250 2 Sue $300 3 Alie $100 N2 Age Σ F ÝÝÑ N Nme Age Slry 1 Alie null $100 2 Bo null $250 3 Sue null $300 4 null 20 null 5 null 20 null 6 null 30 null 9 / 30

10 Foreign keys Nme Nme Slry N1 f N2 F ÝÝÝÑ N Slry Age Age N1 Nme Slry f 1 Bo $ Sue $ Alie $100 3 N2 Age F ÐÝÝ Π F,Σ F ÝÝÝÝÑ N Nme Age Slry 1 Alie 20 $100 2 Bo 20 $250 3 Sue 30 $ / 30

11 FQL Summry FQL provides dtse t time query lnguge for ertin kinds of reltionl dtses. For the tegorilly inlined, roughly: Shems re finitely-presented tegories. Shem mppings re funtors. Instnes re funtors to the tegory of sets. The instnes on ny shem form tegory. pσf, F q nd p F, Π F q re djoint funtors. 11 / 30

12 Progrmming FQL Shems nd Mppings using Hskell By Hskell, I men the the simply-typed λ-lulus (STLC): Types t: t :: 0 1 t ` t t ˆ t t Ñ t Expressions e: e :: v λv : t.e ee pq fst e snd e pe, eq K inl e inr e pe ` eq Equtions: fstpe, fq e sndpe, fq f pλv : t.eqf erv ÞÑ fs... Theorem: FQL shems nd mppings re model of the STLC. Given n STLC type t, you get n FQL shem rts. Given n STLC term Γ $ e : t, you get n FQL shem mpping res : rγs Ñ rts 12 / 30

13 Progrmming FQL Shems using Hskell The empty type, 0, (in Hskell, dt Empty = ), eomes shem with no nodes: The unit type, 1, (in Hskell, dt Unit = TT), eomes shem with one node: TT 13 / 30

14 Progrmming FQL Shems using Hskell Sum types, t ` t 1, (in Hskell, Either t t ), re given y ddition: inl inl inl ` d e inr d inr e Produt types, t ˆ t 1, (in Hskell, (t,t )), re given y multiplition: p,dq p,dq p,dq ˆ d e p,eq p,eq p,eq 14 / 30

15 Progrmming FQL Shems using Hskell Funtion types, t Ñ t 1 re given y exponentition: Ñ d e pþñd,þñd,þñdq pþñe,þñd,þñdq pþñd,þñe,þñdq pþñd,þñd,þñeq pþñe,þñe,þñdq pþñd,þñe,þñeq pþñe,þñd,þñeq pþñe,þñe,þñeq 15 / 30

16 Progrmming FQL Shems using Hskell Constnt types, orresponding to user defined types in Hskell, re simply shems: mnger Emp worksin seretry Dept The opertions ˆ, `, Ñ ehve orretly with respet to foreign keys. Hene, STLC types trnslte to FQL shems. 16 / 30

17 Progrmming FQL Mppings using Hskell In Hskell, we hve K ::. In FQL, we hve mpping K : 0 Ñ : K ÝÑ mnger Emp worksin seretry Dept In Hskell, we hve pq :: 1. In FQL, we hve mpping pq : Ñ 1: mnger Emp worksin seretry Dept pq ÝÑ TT 17 / 30

18 Progrmming FQL Mppings using Hskell In Hskell, we hve inl :: Ñ ` nd inr :: Ñ `. ` d e inl,inr ÝÝÝÝÑ inl inl inl inr d inr e In Hskell, we hve fst :: ˆ Ñ nd snd :: ˆ Ñ. ˆ d e fst,snd ÐÝÝÝÝ p,dq p,dq p,dq p,eq p,eq p,eq 18 / 30

19 Progrmming FQL Mppings using Hskell We n trnslte the other STLC opertions too: If f :: t Ñ nd g :: t Ñ, we need pf, gq :: t Ñ ˆ. This is piring. If f :: Ñ t nd g :: Ñ t, we need pf ` gq :: ` Ñ t. This is se. If f :: ˆ Ñ, we need Λf : Ñ p Ñ q. This is usully lled urry. We need ev :: p Ñ q ˆ Ñ. This is funtion pplition. All FQL opertions oey the required equtions, fstp, q sndp, q... And the FQL opertions work orretly with foreign keys. Hene, FQL mppings re model of the STLC. 19 / 30

20 Retrospetive STLC types nd terms, FQL shems nd mppings, nd even sets nd funtions etween them, re ll i-rtesin losed tegories. Hskell progrmmers will eventully enounter tegory theory, strting with i-rtesin losed tegories. Tht theory n e put to use in other ples, nmely dtses. In ft, s we will see next, for every FQL shem S, the tegory of S-instnes is lso i-rtesin losed. 20 / 30

21 Progrmming FQL Instnes nd Morphisms using Hskell By Hskell, I men the the simply-typed λ-lulus (STLC): Types t: t :: 0 1 t ` t t ˆ t t Ñ t Expressions e: e :: v λv : t.e ee pq fst e snd e pe, eq K inl e inr e pe ` eq Equtions: fstpe, fq e sndpe, fq f pλv : t.eqf erv ÞÑ fs... Theorem: For eh shem S, the FQL S-instnes nd S-homomorphisms re model of the STLC. A dtse homomorphism is mp of s to s. Given n STLC type t, you get n FQL S-instne rts. Given n STLC term Γ $ e : t, you get n FQL S-homomorphism res : rγs Ñ rts 21 / 30

22 Progrmming FQL Instnes using Hskell Let S e the shem f The empty type, 0, (in Hskell, dt Empty = ), eomes n S instne with no dt: f The unit type, 1, (in Hskell, dt Unit = TT), eomes n S instne with one per tle: f / 30

23 Progrmming FQL Instnes using Hskell Sum types t ` t 1 re given y disjoint union: f ` f d f inl 1 inl 3 inl 2 inl 3 inr inr inr inr inl 3 inl 4 inr inr d Produt types t ˆ t 1 re given y joining: f ˆ f d (1,) (1,) (2,) (2,) f (3,) (3,) (3,) (3,) (3,) (3,d) (4,) (4,d) 23 / 30

24 Progrmming FQL Instnes using Hskell Funtion types t Ñ t 1 re given y finding ll homomorphisms: f Ñ f d f 1 ÞÑ, 2 ÞÑ, 3 ÞÑ, 4 ÞÑ d 3 ÞÑ, 4 ÞÑ d 1 ÞÑ, 2 ÞÑ, 3 ÞÑ, 4 ÞÑ d 3 ÞÑ, 4 ÞÑ d 1 ÞÑ, 2 ÞÑ, 3 ÞÑ, 4 ÞÑ d 3 ÞÑ, 4 ÞÑ d 1 ÞÑ, 2 ÞÑ, 3 ÞÑ, 4 ÞÑ d 3 ÞÑ, 4 ÞÑ d 1 ÞÑ, 2 ÞÑ, 3 ÞÑ d, 4 ÞÑ 3 ÞÑ d, 4 ÞÑ 1 ÞÑ, 2 ÞÑ, 3 ÞÑ d, 4 ÞÑ 3 ÞÑ d, 4 ÞÑ 1 ÞÑ, 2 ÞÑ, 3 ÞÑ d, 4 ÞÑ 3 ÞÑ d, 4 ÞÑ 1 ÞÑ, 2 ÞÑ, 3 ÞÑ d, 4 ÞÑ 3 ÞÑ d, 4 ÞÑ 3 ÞÑ, 4 ÞÑ 3 ÞÑ, 4 ÞÑ d 3 ÞÑ d, 4 ÞÑ 3 ÞÑ d, 4 ÞÑ d 24 / 30

25 Progrmming FQL Instnes using Hskell Constnt instnes, orresponding to user defined types in Hskell, re simply instnes: f p q q r t t The opertions ˆ, `, Ñ ehve orretly with respet to foreign keys. Hene, for every shem S, STLC types trnslte to S-instnes. 25 / 30

26 Progrmming FQL Homomorphisms using Hskell in Hskell, we hve K ::. In FQL, we hve homomorphism K : 0 Ñ : f K ÝÑ p r f q t q t In Hskell, we hve pq :: 1. In FQL, we hve homomorphism pq : Ñ 1: f pq ÝÑ f p q q r t t 26 / 30

27 Progrmming FQL Homomorphisms using Hskell As efore, inl : Ñ ` nd inr : Ñ ` f ` f d inl,inr ÝÝÝÝÑ f inl 1 inl 3 inl 2 inl 3 inr inr inr inr inl 3 inl 4 inr inr d As efore, fst : ˆ Ñ nd snd : ˆ Ñ f ˆ f d fst,snd ÐÝÝÝÝÝ (1,) (1,) (2,) (2, ) f (3,) (3,) (3,) (3,) (3,) (3,d) (4,) (4,d) 27 / 30

28 Retrospetive The lnguge of FQL instnes ontins ll opertions required to e model of the STLC. In ft, t the level of instnes, FQL is model of higher-order logi: types t ::... P rop expressions e ::... e e The STLC struture interts with the, Σ, Π dt migrtion opertions in nie wy, e.g,: Σ F pi ` Jq Σ F piq ` Σ F pjq Π F pi ˆ Jq Π F piq ˆ Π F piq 28 / 30

29 Demo of the FQL E The FQL E is n open-soure jv pplition, downlodle t tegorildt.net{fql.html It supports ll the opertions disussed ove: 0, 1, `, ˆ, Ñ for shems nd instnes, nd the dt migrtion opertions, Σ, Π. To the extent possile, ll opertions re implemented with SQL: 0, 1, `, ˆ,, Π implemented with SQL. Σ F only implementle with SQL if F hs ertin property. Ñ not implementle with SQL. Other fetures: It trnsltes from SQL to FQL. It emits RDF enodings of instnes. It omes with mny uilt-in exmples. It n e used s ommnd-line ompiler. 29 / 30

30 Conlusion First, we tlked out FQL, funtoril query lnguge sed on tegory theory. Shems re prtiulr ER digrms, nd instnes re reltionl tles. The, Σ, Π opertions migrte dt from one shem to nother. FQL ontins two opies of the STLC: one t the level of shems nd mppings, nd one t the level of instnes nd homomorphisms. Conlusion: Hskell, in the guise of the STLC, ours in mny res of CS outside of progrmming. Finlly, we sw demo of the FQL E. We re looking for ollortors: tegorildt.net/fql.html 30 / 30

Categorical Databases

Categorical Databases Categorical Databases Patrick Schultz, David Spivak MIT Ryan Wisnesky Categorical Informatics and others October 2017 Introduction This talk describes a new algebraic (purely equational) way to formalize

More information

Introduction to Olympiad Inequalities

Introduction to Olympiad Inequalities Introdution to Olympid Inequlities Edutionl Studies Progrm HSSP Msshusetts Institute of Tehnology Snj Simonovikj Spring 207 Contents Wrm up nd Am-Gm inequlity 2. Elementry inequlities......................

More information

NON-DETERMINISTIC FSA

NON-DETERMINISTIC FSA Tw o types of non-determinism: NON-DETERMINISTIC FS () Multiple strt-sttes; strt-sttes S Q. The lnguge L(M) ={x:x tkes M from some strt-stte to some finl-stte nd ll of x is proessed}. The string x = is

More information

DATABASE DESIGN I - 1DL300

DATABASE DESIGN I - 1DL300 DATABASE DESIGN I - DL300 Fll 00 An introductory course on dtse systems http://www.it.uu.se/edu/course/homepge/dstekn/ht0/ Mnivskn Sesn Uppsl Dtse Lortory Deprtment of Informtion Technology, Uppsl University,

More information

Discrete Structures Lecture 11

Discrete Structures Lecture 11 Introdution Good morning. In this setion we study funtions. A funtion is mpping from one set to nother set or, perhps, from one set to itself. We study the properties of funtions. A mpping my not e funtion.

More information

DATABASTEKNIK - 1DL116

DATABASTEKNIK - 1DL116 DATABASTEKNIK - DL6 Spring 004 An introductury course on dtse systems http://user.it.uu.se/~udl/dt-vt004/ Kjell Orsorn Uppsl Dtse Lortory Deprtment of Informtion Technology, Uppsl University, Uppsl, Sweden

More information

Chapter 3. Vector Spaces. 3.1 Images and Image Arithmetic

Chapter 3. Vector Spaces. 3.1 Images and Image Arithmetic Chpter 3 Vetor Spes In Chpter 2, we sw tht the set of imges possessed numer of onvenient properties. It turns out tht ny set tht possesses similr onvenient properties n e nlyzed in similr wy. In liner

More information

Finite State Automata and Determinisation

Finite State Automata and Determinisation Finite Stte Automt nd Deterministion Tim Dworn Jnury, 2016 Lnguges fs nf re df Deterministion 2 Outline 1 Lnguges 2 Finite Stte Automt (fs) 3 Non-deterministi Finite Stte Automt (nf) 4 Regulr Expressions

More information

1 PYTHAGORAS THEOREM 1. Given a right angled triangle, the square of the hypotenuse is equal to the sum of the squares of the other two sides.

1 PYTHAGORAS THEOREM 1. Given a right angled triangle, the square of the hypotenuse is equal to the sum of the squares of the other two sides. 1 PYTHAGORAS THEOREM 1 1 Pythgors Theorem In this setion we will present geometri proof of the fmous theorem of Pythgors. Given right ngled tringle, the squre of the hypotenuse is equl to the sum of the

More information

LESSON 11: TRIANGLE FORMULAE

LESSON 11: TRIANGLE FORMULAE . THE SEMIPERIMETER OF TRINGLE LESSON : TRINGLE FORMULE In wht follows, will hve sides, nd, nd these will e opposite ngles, nd respetively. y the tringle inequlity, nd..() So ll of, & re positive rel numers.

More information

Activities. 4.1 Pythagoras' Theorem 4.2 Spirals 4.3 Clinometers 4.4 Radar 4.5 Posting Parcels 4.6 Interlocking Pipes 4.7 Sine Rule Notes and Solutions

Activities. 4.1 Pythagoras' Theorem 4.2 Spirals 4.3 Clinometers 4.4 Radar 4.5 Posting Parcels 4.6 Interlocking Pipes 4.7 Sine Rule Notes and Solutions MEP: Demonstrtion Projet UNIT 4: Trigonometry UNIT 4 Trigonometry tivities tivities 4. Pythgors' Theorem 4.2 Spirls 4.3 linometers 4.4 Rdr 4.5 Posting Prels 4.6 Interloking Pipes 4.7 Sine Rule Notes nd

More information

On Implicative and Strong Implicative Filters of Lattice Wajsberg Algebras

On Implicative and Strong Implicative Filters of Lattice Wajsberg Algebras Glol Journl of Mthemtil Sienes: Theory nd Prtil. ISSN 974-32 Volume 9, Numer 3 (27), pp. 387-397 Interntionl Reserh Pulition House http://www.irphouse.om On Implitive nd Strong Implitive Filters of Lttie

More information

Linear Algebra Introduction

Linear Algebra Introduction Introdution Wht is Liner Alger out? Liner Alger is rnh of mthemtis whih emerged yers k nd ws one of the pioneer rnhes of mthemtis Though, initilly it strted with solving of the simple liner eqution x +

More information

Alpha Algorithm: A Process Discovery Algorithm

Alpha Algorithm: A Process Discovery Algorithm Proess Mining: Dt Siene in Ation Alph Algorithm: A Proess Disovery Algorithm prof.dr.ir. Wil vn der Alst www.proessmining.org Proess disovery = Ply-In Ply-In event log proess model Ply-Out Reply proess

More information

CS311 Computational Structures Regular Languages and Regular Grammars. Lecture 6

CS311 Computational Structures Regular Languages and Regular Grammars. Lecture 6 CS311 Computtionl Strutures Regulr Lnguges nd Regulr Grmmrs Leture 6 1 Wht we know so fr: RLs re losed under produt, union nd * Every RL n e written s RE, nd every RE represents RL Every RL n e reognized

More information

Section 1.3 Triangles

Section 1.3 Triangles Se 1.3 Tringles 21 Setion 1.3 Tringles LELING TRINGLE The line segments tht form tringle re lled the sides of the tringle. Eh pir of sides forms n ngle, lled n interior ngle, nd eh tringle hs three interior

More information

Functions. mjarrar Watch this lecture and download the slides

Functions. mjarrar Watch this lecture and download the slides 9/6/7 Mustf Jrrr: Leture Notes in Disrete Mthemtis. Birzeit University Plestine 05 Funtions 7.. Introdution to Funtions 7. One-to-One Onto Inverse funtions mjrrr 05 Wth this leture nd downlod the slides

More information

8 THREE PHASE A.C. CIRCUITS

8 THREE PHASE A.C. CIRCUITS 8 THREE PHSE.. IRUITS The signls in hpter 7 were sinusoidl lternting voltges nd urrents of the so-lled single se type. n emf of suh type n e esily generted y rotting single loop of ondutor (or single winding),

More information

BİL 354 Veritabanı Sistemleri. Relational Algebra (İlişkisel Cebir)

BİL 354 Veritabanı Sistemleri. Relational Algebra (İlişkisel Cebir) BİL 354 Veritnı Sistemleri Reltionl lger (İlişkisel Ceir) Reltionl Queries Query lnguges: llow mnipultion nd retrievl of dt from dtse. Reltionl model supports simple, powerful QLs: Strong forml foundtion

More information

Exercise 3 Logic Control

Exercise 3 Logic Control Exerise 3 Logi Control OBJECTIVE The ojetive of this exerise is giving n introdution to pplition of Logi Control System (LCS). Tody, LCS is implemented through Progrmmle Logi Controller (PLC) whih is lled

More information

Coalgebra, Lecture 15: Equations for Deterministic Automata

Coalgebra, Lecture 15: Equations for Deterministic Automata Colger, Lecture 15: Equtions for Deterministic Automt Julin Slmnc (nd Jurrin Rot) Decemer 19, 2016 In this lecture, we will study the concept of equtions for deterministic utomt. The notes re self contined

More information

Solutions to Problem Set #1

Solutions to Problem Set #1 CSE 233 Spring, 2016 Solutions to Prolem Set #1 1. The movie tse onsists of the following two reltions movie: title, iretor, tor sheule: theter, title The first reltion provies titles, iretors, n tors

More information

Project 6: Minigoals Towards Simplifying and Rewriting Expressions

Project 6: Minigoals Towards Simplifying and Rewriting Expressions MAT 51 Wldis Projet 6: Minigols Towrds Simplifying nd Rewriting Expressions The distriutive property nd like terms You hve proly lerned in previous lsses out dding like terms ut one prolem with the wy

More information

12.4 Similarity in Right Triangles

12.4 Similarity in Right Triangles Nme lss Dte 12.4 Similrit in Right Tringles Essentil Question: How does the ltitude to the hpotenuse of right tringle help ou use similr right tringles to solve prolems? Eplore Identifing Similrit in Right

More information

Lecture 3: Equivalence Relations

Lecture 3: Equivalence Relations Mthcmp Crsh Course Instructor: Pdric Brtlett Lecture 3: Equivlence Reltions Week 1 Mthcmp 2014 In our lst three tlks of this clss, we shift the focus of our tlks from proof techniques to proof concepts

More information

Learning Goals. Relational Query Languages. Formal Relational Query Languages. Formal Query Languages: Relational Algebra and Relational Calculus

Learning Goals. Relational Query Languages. Formal Relational Query Languages. Formal Query Languages: Relational Algebra and Relational Calculus Forml Query Lnguges: Reltionl Alger nd Reltionl Clculus Chpter 4 Lerning Gols Given dtse ( set of tles ) you will e le to express dtse query in Reltionl Alger (RA), involving the sic opertors (selection,

More information

where the box contains a finite number of gates from the given collection. Examples of gates that are commonly used are the following: a b

where the box contains a finite number of gates from the given collection. Examples of gates that are commonly used are the following: a b CS 294-2 9/11/04 Quntum Ciruit Model, Solovy-Kitev Theorem, BQP Fll 2004 Leture 4 1 Quntum Ciruit Model 1.1 Clssil Ciruits - Universl Gte Sets A lssil iruit implements multi-output oolen funtion f : {0,1}

More information

Dorf, R.C., Wan, Z. T- Equivalent Networks The Electrical Engineering Handbook Ed. Richard C. Dorf Boca Raton: CRC Press LLC, 2000

Dorf, R.C., Wan, Z. T- Equivalent Networks The Electrical Engineering Handbook Ed. Richard C. Dorf Boca Raton: CRC Press LLC, 2000 orf, R.C., Wn,. T- Equivlent Networks The Eletril Engineering Hndook Ed. Rihrd C. orf Bo Rton: CRC Press LLC, 000 9 T P Equivlent Networks hen Wn University of Cliforni, vis Rihrd C. orf University of

More information

Pre-Lie algebras, rooted trees and related algebraic structures

Pre-Lie algebras, rooted trees and related algebraic structures Pre-Lie lgers, rooted trees nd relted lgeri strutures Mrh 23, 2004 Definition 1 A pre-lie lger is vetor spe W with mp : W W W suh tht (x y) z x (y z) = (x z) y x (z y). (1) Exmple 2 All ssoitive lgers

More information

CHENG Chun Chor Litwin The Hong Kong Institute of Education

CHENG Chun Chor Litwin The Hong Kong Institute of Education PE-hing Mi terntionl onferene IV: novtion of Mthemtis Tehing nd Lerning through Lesson Study- onnetion etween ssessment nd Sujet Mtter HENG hun hor Litwin The Hong Kong stitute of Edution Report on using

More information

6.5 Improper integrals

6.5 Improper integrals Eerpt from "Clulus" 3 AoPS In. www.rtofprolemsolving.om 6.5. IMPROPER INTEGRALS 6.5 Improper integrls As we ve seen, we use the definite integrl R f to ompute the re of the region under the grph of y =

More information

Lecture 6: Coding theory

Lecture 6: Coding theory Leture 6: Coing theory Biology 429 Crl Bergstrom Ferury 4, 2008 Soures: This leture loosely follows Cover n Thoms Chpter 5 n Yeung Chpter 3. As usul, some of the text n equtions re tken iretly from those

More information

CS 573 Automata Theory and Formal Languages

CS 573 Automata Theory and Formal Languages Non-determinism Automt Theory nd Forml Lnguges Professor Leslie Lnder Leture # 3 Septemer 6, 2 To hieve our gol, we need the onept of Non-deterministi Finite Automton with -moves (NFA) An NFA is tuple

More information

CS 373, Spring Solutions to Mock midterm 1 (Based on first midterm in CS 273, Fall 2008.)

CS 373, Spring Solutions to Mock midterm 1 (Based on first midterm in CS 273, Fall 2008.) CS 373, Spring 29. Solutions to Mock midterm (sed on first midterm in CS 273, Fll 28.) Prolem : Short nswer (8 points) The nswers to these prolems should e short nd not complicted. () If n NF M ccepts

More information

Part 4. Integration (with Proofs)

Part 4. Integration (with Proofs) Prt 4. Integrtion (with Proofs) 4.1 Definition Definition A prtition P of [, b] is finite set of points {x 0, x 1,..., x n } with = x 0 < x 1

More information

Global alignment. Genome Rearrangements Finding preserved genes. Lecture 18

Global alignment. Genome Rearrangements Finding preserved genes. Lecture 18 Computt onl Biology Leture 18 Genome Rerrngements Finding preserved genes We hve seen before how to rerrnge genome to obtin nother one bsed on: Reversls Knowledge of preserved bloks (or genes) Now we re

More information

, g. Exercise 1. Generator polynomials of a convolutional code, given in binary form, are g. Solution 1.

, g. Exercise 1. Generator polynomials of a convolutional code, given in binary form, are g. Solution 1. Exerise Genertor polynomils of onvolutionl ode, given in binry form, re g, g j g. ) Sketh the enoding iruit. b) Sketh the stte digrm. ) Find the trnsfer funtion T. d) Wht is the minimum free distne of

More information

Reference : Croft & Davison, Chapter 12, Blocks 1,2. A matrix ti is a rectangular array or block of numbers usually enclosed in brackets.

Reference : Croft & Davison, Chapter 12, Blocks 1,2. A matrix ti is a rectangular array or block of numbers usually enclosed in brackets. I MATRIX ALGEBRA INTRODUCTION TO MATRICES Referene : Croft & Dvison, Chpter, Blos, A mtri ti is retngulr rr or lo of numers usull enlosed in rets. A m n mtri hs m rows nd n olumns. Mtri Alger Pge If the

More information

Logic Synthesis and Verification

Logic Synthesis and Verification Logi Synthesis nd Verifition SOPs nd Inompletely Speified Funtions Jie-Hong Rolnd Jing 江介宏 Deprtment of Eletril Engineering Ntionl Tiwn University Fll 2010 Reding: Logi Synthesis in Nutshell Setion 2 most

More information

System Validation (IN4387) November 2, 2012, 14:00-17:00

System Validation (IN4387) November 2, 2012, 14:00-17:00 System Vlidtion (IN4387) Novemer 2, 2012, 14:00-17:00 Importnt Notes. The exmintion omprises 5 question in 4 pges. Give omplete explntion nd do not onfine yourself to giving the finl nswer. Good luk! Exerise

More information

Spacetime and the Quantum World Questions Fall 2010

Spacetime and the Quantum World Questions Fall 2010 Spetime nd the Quntum World Questions Fll 2010 1. Cliker Questions from Clss: (1) In toss of two die, wht is the proility tht the sum of the outomes is 6? () P (x 1 + x 2 = 6) = 1 36 - out 3% () P (x 1

More information

Hardware Verification 2IMF20

Hardware Verification 2IMF20 Hrdwre Verifition 2IMF20 Julien Shmltz Leture 02: Boolen Funtions, ST, CEC Course ontent - Forml tools Temporl Logis (LTL, CTL) Domin Properties System Verilog ssertions demi & Industrils Proessors Networks

More information

Green s Theorem. (2x e y ) da. (2x e y ) dx dy. x 2 xe y. (1 e y ) dy. y=1. = y e y. y=0. = 2 e

Green s Theorem. (2x e y ) da. (2x e y ) dx dy. x 2 xe y. (1 e y ) dy. y=1. = y e y. y=0. = 2 e Green s Theorem. Let be the boundry of the unit squre, y, oriented ounterlokwise, nd let F be the vetor field F, y e y +, 2 y. Find F d r. Solution. Let s write P, y e y + nd Q, y 2 y, so tht F P, Q. Let

More information

F / x everywhere in some domain containing R. Then, + ). (10.4.1)

F / x everywhere in some domain containing R. Then, + ). (10.4.1) 0.4 Green's theorem in the plne Double integrls over plne region my be trnsforme into line integrls over the bounry of the region n onversely. This is of prtil interest beuse it my simplify the evlution

More information

SECTION A STUDENT MATERIAL. Part 1. What and Why.?

SECTION A STUDENT MATERIAL. Part 1. What and Why.? SECTION A STUDENT MATERIAL Prt Wht nd Wh.? Student Mteril Prt Prolem n > 0 n > 0 Is the onverse true? Prolem If n is even then n is even. If n is even then n is even. Wht nd Wh? Eploring Pure Mths Are

More information

Intermediate Math Circles Wednesday 17 October 2012 Geometry II: Side Lengths

Intermediate Math Circles Wednesday 17 October 2012 Geometry II: Side Lengths Intermedite Mth Cirles Wednesdy 17 Otoer 01 Geometry II: Side Lengths Lst week we disussed vrious ngle properties. As we progressed through the evening, we proved mny results. This week, we will look t

More information

The University of Nottingham SCHOOL OF COMPUTER SCIENCE A LEVEL 2 MODULE, SPRING SEMESTER MACHINES AND THEIR LANGUAGES ANSWERS

The University of Nottingham SCHOOL OF COMPUTER SCIENCE A LEVEL 2 MODULE, SPRING SEMESTER MACHINES AND THEIR LANGUAGES ANSWERS The University of ottinghm SCHOOL OF COMPUTR SCIC A LVL 2 MODUL, SPRIG SMSTR 2015 2016 MACHIS AD THIR LAGUAGS ASWRS Time llowed TWO hours Cndidtes my omplete the front over of their nswer ook nd sign their

More information

CSE : Exam 3-ANSWERS, Spring 2011 Time: 50 minutes

CSE : Exam 3-ANSWERS, Spring 2011 Time: 50 minutes CSE 260-002: Exm 3-ANSWERS, Spring 20 ime: 50 minutes Nme: his exm hs 4 pges nd 0 prolems totling 00 points. his exm is closed ook nd closed notes.. Wrshll s lgorithm for trnsitive closure computtion is

More information

Prefix-Free Regular-Expression Matching

Prefix-Free Regular-Expression Matching Prefix-Free Regulr-Expression Mthing Yo-Su Hn, Yjun Wng nd Derik Wood Deprtment of Computer Siene HKUST Prefix-Free Regulr-Expression Mthing p.1/15 Pttern Mthing Given pttern P nd text T, find ll sustrings

More information

ILLUSTRATING THE EXTENSION OF A SPECIAL PROPERTY OF CUBIC POLYNOMIALS TO NTH DEGREE POLYNOMIALS

ILLUSTRATING THE EXTENSION OF A SPECIAL PROPERTY OF CUBIC POLYNOMIALS TO NTH DEGREE POLYNOMIALS ILLUSTRATING THE EXTENSION OF A SPECIAL PROPERTY OF CUBIC POLYNOMIALS TO NTH DEGREE POLYNOMIALS Dvid Miller West Virgini University P.O. BOX 6310 30 Armstrong Hll Morgntown, WV 6506 millerd@mth.wvu.edu

More information

TOPIC: LINEAR ALGEBRA MATRICES

TOPIC: LINEAR ALGEBRA MATRICES Interntionl Blurete LECTUE NOTES for FUTHE MATHEMATICS Dr TOPIC: LINEA ALGEBA MATICES. DEFINITION OF A MATIX MATIX OPEATIONS.. THE DETEMINANT deta THE INVESE A -... SYSTEMS OF LINEA EQUATIONS. 8. THE AUGMENTED

More information

Nondeterministic Finite Automata

Nondeterministic Finite Automata Nondeterministi Finite utomt The Power of Guessing Tuesdy, Otoer 4, 2 Reding: Sipser.2 (first prt); Stoughton 3.3 3.5 S235 Lnguges nd utomt eprtment of omputer Siene Wellesley ollege Finite utomton (F)

More information

How do we solve these things, especially when they get complicated? How do we know when a system has a solution, and when is it unique?

How do we solve these things, especially when they get complicated? How do we know when a system has a solution, and when is it unique? XII. LINEAR ALGEBRA: SOLVING SYSTEMS OF EQUATIONS Tody we re going to tlk out solving systems of liner equtions. These re prolems tht give couple of equtions with couple of unknowns, like: 6= x + x 7=

More information

INTEGRATION. 1 Integrals of Complex Valued functions of a REAL variable

INTEGRATION. 1 Integrals of Complex Valued functions of a REAL variable INTEGRATION NOTE: These notes re supposed to supplement Chpter 4 of the online textbook. 1 Integrls of Complex Vlued funtions of REAL vrible If I is n intervl in R (for exmple I = [, b] or I = (, b)) nd

More information

INF1383 -Bancos de Dados

INF1383 -Bancos de Dados 3//0 INF383 -ncos de Ddos Prof. Sérgio Lifschitz DI PUC-Rio Eng. Computção, Sistems de Informção e Ciênci d Computção LGER RELCIONL lguns slides sedos ou modificdos dos originis em Elmsri nd Nvthe, Fundmentls

More information

arxiv: v1 [math.ca] 21 Aug 2018

arxiv: v1 [math.ca] 21 Aug 2018 rxiv:1808.07159v1 [mth.ca] 1 Aug 018 Clulus on Dul Rel Numbers Keqin Liu Deprtment of Mthemtis The University of British Columbi Vnouver, BC Cnd, V6T 1Z Augest, 018 Abstrt We present the bsi theory of

More information

Generalization of 2-Corner Frequency Source Models Used in SMSIM

Generalization of 2-Corner Frequency Source Models Used in SMSIM Generliztion o 2-Corner Frequeny Soure Models Used in SMSIM Dvid M. Boore 26 Mrh 213, orreted Figure 1 nd 2 legends on 5 April 213, dditionl smll orretions on 29 My 213 Mny o the soure spetr models ville

More information

Matrices SCHOOL OF ENGINEERING & BUILT ENVIRONMENT. Mathematics (c) 1. Definition of a Matrix

Matrices SCHOOL OF ENGINEERING & BUILT ENVIRONMENT. Mathematics (c) 1. Definition of a Matrix tries Definition of tri mtri is regulr rry of numers enlosed inside rkets SCHOOL OF ENGINEERING & UIL ENVIRONEN Emple he following re ll mtries: ), ) 9, themtis ), d) tries Definition of tri Size of tri

More information

Algebra Basics. Algebra Basics. Curriculum Ready ACMNA: 133, 175, 176, 177, 179.

Algebra Basics. Algebra Basics. Curriculum Ready ACMNA: 133, 175, 176, 177, 179. Curriulum Redy ACMNA: 33 75 76 77 79 www.mthletis.om Fill in the spes with nything you lredy know out Alger Creer Opportunities: Arhitets eletriins plumers et. use it to do importnt lultions. Give this

More information

3 Angle Geometry. 3.1 Measuring Angles. 1. Using a protractor, measure the marked angles.

3 Angle Geometry. 3.1 Measuring Angles. 1. Using a protractor, measure the marked angles. 3 ngle Geometry MEP Prtie ook S3 3.1 Mesuring ngles 1. Using protrtor, mesure the mrked ngles. () () (d) (e) (f) 2. Drw ngles with the following sizes. () 22 () 75 120 (d) 90 (e) 153 (f) 45 (g) 180 (h)

More information

2.1 ANGLES AND THEIR MEASURE. y I

2.1 ANGLES AND THEIR MEASURE. y I .1 ANGLES AND THEIR MEASURE Given two interseting lines or line segments, the mount of rottion out the point of intersetion (the vertex) required to ring one into orrespondene with the other is lled the

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

CS241 Week 6 Tutorial Solutions

CS241 Week 6 Tutorial Solutions 241 Week 6 Tutoril olutions Lnguges: nning & ontext-free Grmmrs Winter 2018 1 nning Exerises 1. 0x0x0xd HEXINT 0x0 I x0xd 2. 0xend--- HEXINT 0xe I nd ER -- MINU - 3. 1234-120x INT 1234 INT -120 I x 4.

More information

ON THE INEQUALITY OF THE DIFFERENCE OF TWO INTEGRAL MEANS AND APPLICATIONS FOR PDFs

ON THE INEQUALITY OF THE DIFFERENCE OF TWO INTEGRAL MEANS AND APPLICATIONS FOR PDFs ON THE INEQUALITY OF THE DIFFERENCE OF TWO INTEGRAL MEANS AND APPLICATIONS FOR PDFs A.I. KECHRINIOTIS AND N.D. ASSIMAKIS Deprtment of Eletronis Tehnologil Edutionl Institute of Lmi, Greee EMil: {kehrin,

More information

expression simply by forming an OR of the ANDs of all input variables for which the output is

expression simply by forming an OR of the ANDs of all input variables for which the output is 2.4 Logic Minimiztion nd Krnugh Mps As we found ove, given truth tle, it is lwys possile to write down correct logic expression simply y forming n OR of the ANDs of ll input vriles for which the output

More information

THE PYTHAGOREAN THEOREM

THE PYTHAGOREAN THEOREM THE PYTHAGOREAN THEOREM The Pythgoren Theorem is one of the most well-known nd widely used theorems in mthemtis. We will first look t n informl investigtion of the Pythgoren Theorem, nd then pply this

More information

AUTOMATA AND LANGUAGES. Definition 1.5: Finite Automaton

AUTOMATA AND LANGUAGES. Definition 1.5: Finite Automaton 25. Finite Automt AUTOMATA AND LANGUAGES A system of computtion tht only hs finite numer of possile sttes cn e modeled using finite utomton A finite utomton is often illustrted s stte digrm d d d. d q

More information

Hyers-Ulam stability of Pielou logistic difference equation

Hyers-Ulam stability of Pielou logistic difference equation vilble online t wwwisr-publitionsom/jns J Nonliner Si ppl, 0 (207, 35 322 Reserh rtile Journl Homepge: wwwtjnsom - wwwisr-publitionsom/jns Hyers-Ulm stbility of Pielou logisti differene eqution Soon-Mo

More information

Something found at a salad bar

Something found at a salad bar Nme PP Something found t sld r 4.7 Notes RIGHT TRINGLE hs extly one right ngle. To solve right tringle, you n use things like SOH-H-TO nd the Pythgoren Theorem. n OLIQUE TRINGLE hs no right ngles. To solve

More information

Connected-components. Summary of lecture 9. Algorithms and Data Structures Disjoint sets. Example: connected components in graphs

Connected-components. Summary of lecture 9. Algorithms and Data Structures Disjoint sets. Example: connected components in graphs Prm University, Mth. Deprtment Summry of lecture 9 Algorithms nd Dt Structures Disjoint sets Summry of this lecture: (CLR.1-3) Dt Structures for Disjoint sets: Union opertion Find opertion Mrco Pellegrini

More information

QUADRATIC EQUATION. Contents

QUADRATIC EQUATION. Contents QUADRATIC EQUATION Contents Topi Pge No. Theory 0-04 Exerise - 05-09 Exerise - 09-3 Exerise - 3 4-5 Exerise - 4 6 Answer Key 7-8 Syllus Qudrti equtions with rel oeffiients, reltions etween roots nd oeffiients,

More information

u(t)dt + i a f(t)dt f(t) dt b f(t) dt (2) With this preliminary step in place, we are ready to define integration on a general curve in C.

u(t)dt + i a f(t)dt f(t) dt b f(t) dt (2) With this preliminary step in place, we are ready to define integration on a general curve in C. Lecture 4 Complex Integrtion MATH-GA 2451.001 Complex Vriles 1 Construction 1.1 Integrting complex function over curve in C A nturl wy to construct the integrl of complex function over curve in the complex

More information

Trigonometry Revision Sheet Q5 of Paper 2

Trigonometry Revision Sheet Q5 of Paper 2 Trigonometry Revision Sheet Q of Pper The Bsis - The Trigonometry setion is ll out tringles. We will normlly e given some of the sides or ngles of tringle nd we use formule nd rules to find the others.

More information

Unit 4. Combinational Circuits

Unit 4. Combinational Circuits Unit 4. Comintionl Ciruits Digitl Eletroni Ciruits (Ciruitos Eletrónios Digitles) E.T.S.I. Informáti Universidd de Sevill 5/10/2012 Jorge Jun 2010, 2011, 2012 You re free to opy, distriute

More information

AP Calculus BC Chapter 8: Integration Techniques, L Hopital s Rule and Improper Integrals

AP Calculus BC Chapter 8: Integration Techniques, L Hopital s Rule and Improper Integrals AP Clulus BC Chpter 8: Integrtion Tehniques, L Hopitl s Rule nd Improper Integrls 8. Bsi Integrtion Rules In this setion we will review vrious integrtion strtegies. Strtegies: I. Seprte the integrnd into

More information

Intermediate Math Circles Wednesday, November 14, 2018 Finite Automata II. Nickolas Rollick a b b. a b 4

Intermediate Math Circles Wednesday, November 14, 2018 Finite Automata II. Nickolas Rollick a b b. a b 4 Intermedite Mth Circles Wednesdy, Novemer 14, 2018 Finite Automt II Nickols Rollick nrollick@uwterloo.c Regulr Lnguges Lst time, we were introduced to the ide of DFA (deterministic finite utomton), one

More information

Math 4310 Solutions to homework 1 Due 9/1/16

Math 4310 Solutions to homework 1 Due 9/1/16 Mth 4310 Solutions to homework 1 Due 9/1/16 1. Use the Eucliden lgorithm to find the following gretest common divisors. () gcd(252, 180) = 36 (b) gcd(513, 187) = 1 (c) gcd(7684, 4148) = 68 252 = 180 1

More information

6.3.2 Spectroscopy. N Goalby chemrevise.org 1 NO 2 H 3 CH3 C. NMR spectroscopy. Different types of NMR

6.3.2 Spectroscopy. N Goalby chemrevise.org 1 NO 2 H 3 CH3 C. NMR spectroscopy. Different types of NMR 6.. Spetrosopy NMR spetrosopy Different types of NMR NMR spetrosopy involves intertion of mterils with the lowenergy rdiowve region of the eletromgneti spetrum NMR spetrosopy is the sme tehnology s tht

More information

Line Integrals and Entire Functions

Line Integrals and Entire Functions Line Integrls nd Entire Funtions Defining n Integrl for omplex Vlued Funtions In the following setions, our min gol is to show tht every entire funtion n be represented s n everywhere onvergent power series

More information

ELECTRICAL AND COMPUTER ENGINEERING DEPARTMENT, OAKLAND UNIVERSITY ECE-378: Computer Hardware Design Winter Notes - Unit 1

ELECTRICAL AND COMPUTER ENGINEERING DEPARTMENT, OAKLAND UNIVERSITY ECE-378: Computer Hardware Design Winter Notes - Unit 1 ELETRIL ND OMPUTER ENGINEERING DEPRTMENT, OKLND UNIVERSIT EE-78: omputer Hrdwre Design Winter 016 INTRODUTION TO LOGI IRUITS Notes - Unit 1 OOLEN LGER This is the oundtion or designing nd nlyzing digitl

More information

I1 = I2 I1 = I2 + I3 I1 + I2 = I3 + I4 I 3

I1 = I2 I1 = I2 + I3 I1 + I2 = I3 + I4 I 3 2 The Prllel Circuit Electric Circuits: Figure 2- elow show ttery nd multiple resistors rrnged in prllel. Ech resistor receives portion of the current from the ttery sed on its resistnce. The split is

More information

Proportions: A ratio is the quotient of two numbers. For example, 2 3

Proportions: A ratio is the quotient of two numbers. For example, 2 3 Proportions: rtio is the quotient of two numers. For exmple, 2 3 is rtio of 2 n 3. n equlity of two rtios is proportion. For exmple, 3 7 = 15 is proportion. 45 If two sets of numers (none of whih is 0)

More information

Lecture 2: January 27

Lecture 2: January 27 CS 684: Algorithmic Gme Theory Spring 217 Lecturer: Év Trdos Lecture 2: Jnury 27 Scrie: Alert Julius Liu 2.1 Logistics Scrie notes must e sumitted within 24 hours of the corresponding lecture for full

More information

PAIR OF LINEAR EQUATIONS IN TWO VARIABLES

PAIR OF LINEAR EQUATIONS IN TWO VARIABLES PAIR OF LINEAR EQUATIONS IN TWO VARIABLES. Two liner equtions in the sme two vriles re lled pir of liner equtions in two vriles. The most generl form of pir of liner equtions is x + y + 0 x + y + 0 where,,,,,,

More information

SEMANTIC ANALYSIS PRINCIPLES OF PROGRAMMING LANGUAGES. Norbert Zeh Winter Dalhousie University 1/28

SEMANTIC ANALYSIS PRINCIPLES OF PROGRAMMING LANGUAGES. Norbert Zeh Winter Dalhousie University 1/28 SEMNTI NLYSIS PRINIPLES OF PROGRMMING LNGUGES Norbert Zeh Winter 2018 Dlhousie University 1/28 PROGRM TRNSLTION FLOW HRT Soure progrm (hrter strem) Snner (lexil nlysis) Front end Prse tree Prser (syntti

More information

Trigonometry and Constructive Geometry

Trigonometry and Constructive Geometry Trigonometry nd Construtive Geometry Trining prolems for M2 2018 term 1 Ted Szylowie tedszy@gmil.om 1 Leling geometril figures 1. Prtie writing Greek letters. αβγδɛθλµπψ 2. Lel the sides, ngles nd verties

More information

Chapter 4 State-Space Planning

Chapter 4 State-Space Planning Leture slides for Automted Plnning: Theory nd Prtie Chpter 4 Stte-Spe Plnning Dn S. Nu CMSC 722, AI Plnning University of Mrylnd, Spring 2008 1 Motivtion Nerly ll plnning proedures re serh proedures Different

More information

I 3 2 = I I 4 = 2A

I 3 2 = I I 4 = 2A ECE 210 Eletril Ciruit Anlysis University of llinois t Chigo 2.13 We re ske to use KCL to fin urrents 1 4. The key point in pplying KCL in this prolem is to strt with noe where only one of the urrents

More information

Designing Information Devices and Systems I Fall 2016 Babak Ayazifar, Vladimir Stojanovic Homework 6. This homework is due October 11, 2016, at Noon.

Designing Information Devices and Systems I Fall 2016 Babak Ayazifar, Vladimir Stojanovic Homework 6. This homework is due October 11, 2016, at Noon. EECS 16A Designing Informtion Devices nd Systems I Fll 2016 Bk Ayzifr, Vldimir Stojnovic Homework 6 This homework is due Octoer 11, 2016, t Noon. 1. Homework process nd study group Who else did you work

More information

RELATIONAL MODEL.

RELATIONAL MODEL. RELATIONAL MODEL Structure of Reltionl Dtbses Reltionl Algebr Tuple Reltionl Clculus Domin Reltionl Clculus Extended Reltionl-Algebr- Opertions Modifiction of the Dtbse Views EXAMPLE OF A RELATION BASIC

More information

The Double Integral. The Riemann sum of a function f (x; y) over this partition of [a; b] [c; d] is. f (r j ; t k ) x j y k

The Double Integral. The Riemann sum of a function f (x; y) over this partition of [a; b] [c; d] is. f (r j ; t k ) x j y k The Double Integrl De nition of the Integrl Iterted integrls re used primrily s tool for omputing double integrls, where double integrl is n integrl of f (; y) over region : In this setion, we de ne double

More information

Figure 1. The left-handed and right-handed trefoils

Figure 1. The left-handed and right-handed trefoils The Knot Group A knot is n emedding of the irle into R 3 (or S 3 ), k : S 1 R 3. We shll ssume our knots re tme, mening the emedding n e extended to solid torus, K : S 1 D 2 R 3. The imge is lled tuulr

More information

22: Union Find. CS 473u - Algorithms - Spring April 14, We want to maintain a collection of sets, under the operations of:

22: Union Find. CS 473u - Algorithms - Spring April 14, We want to maintain a collection of sets, under the operations of: 22: Union Fin CS 473u - Algorithms - Spring 2005 April 14, 2005 1 Union-Fin We wnt to mintin olletion of sets, uner the opertions of: 1. MkeSet(x) - rete set tht ontins the single element x. 2. Fin(x)

More information

Fundamental Theorem of Calculus

Fundamental Theorem of Calculus Fundmentl Theorem of Clculus Recll tht if f is nonnegtive nd continuous on [, ], then the re under its grph etween nd is the definite integrl A= f() d Now, for in the intervl [, ], let A() e the re under

More information

Semantic Analysis. CSCI 3136 Principles of Programming Languages. Faculty of Computer Science Dalhousie University. Winter Reading: Chapter 4

Semantic Analysis. CSCI 3136 Principles of Programming Languages. Faculty of Computer Science Dalhousie University. Winter Reading: Chapter 4 Semnti nlysis SI 16 Priniples of Progrmming Lnguges Fulty of omputer Siene Dlhousie University Winter 2012 Reding: hpter 4 Motivtion Soure progrm (hrter strem) Snner (lexil nlysis) Front end Prse tree

More information

Bisimulation, Games & Hennessy Milner logic

Bisimulation, Games & Hennessy Milner logic Bisimultion, Gmes & Hennessy Milner logi Leture 1 of Modelli Mtemtii dei Proessi Conorrenti Pweł Soboiński Univeristy of Southmpton, UK Bisimultion, Gmes & Hennessy Milner logi p.1/32 Clssil lnguge theory

More information

Section 4.4. Green s Theorem

Section 4.4. Green s Theorem The Clulus of Funtions of Severl Vriles Setion 4.4 Green s Theorem Green s theorem is n exmple from fmily of theorems whih onnet line integrls (nd their higher-dimensionl nlogues) with the definite integrls

More information

ON LEFT(RIGHT) SEMI-REGULAR AND g-reguar po-semigroups. Sang Keun Lee

ON LEFT(RIGHT) SEMI-REGULAR AND g-reguar po-semigroups. Sang Keun Lee Kngweon-Kyungki Mth. Jour. 10 (2002), No. 2, pp. 117 122 ON LEFT(RIGHT) SEMI-REGULAR AND g-reguar po-semigroups Sng Keun Lee Astrt. In this pper, we give some properties of left(right) semi-regulr nd g-regulr

More information

AVL Trees. D Oisín Kidney. August 2, 2018

AVL Trees. D Oisín Kidney. August 2, 2018 AVL Trees D Oisín Kidne August 2, 2018 Astrt This is verified implementtion of AVL trees in Agd, tking ides primril from Conor MBride s pper How to Keep Your Neighours in Order [2] nd the Agd stndrd lirr

More information

Test Generation from Timed Input Output Automata

Test Generation from Timed Input Output Automata Chpter 8 Test Genertion from Timed Input Output Automt The purpose of this hpter is to introdue tehniques for the genertion of test dt from models of softwre sed on vrints of timed utomt. The tests generted

More information