(From Linz 7.1 p. 183 Exercise 4.)
|
|
|
- Jemima Gallagher
- 9 years ago
- Views:
Transcription
1 Additional NPDA examples (From Lin 7.1 p. 183 Exercise 4.)
2 Formal Definition Non-Deterministic Pushdown Automaton NPDA M = ( Q, Σ, Γ, δ, q,, 0 F ) Final Set of states states Input alphabet Stack alphabet Transition function Initial state Stack start symbol 2
3 Instantaneous Description ( q, u, s) ) Current state Remaining input Current stack contents 3
4 1. Construct NPDA that accepts the language L = {wcw R : w {a, b}} with Σ = {a, b, c} The idea of machine construction*: We construct M that accepts L. It reads w and after seeing c, it reads w R. We will need three states, for reading w, switching to the new state after reading c, and the final accepting state. tt First for each a or b seen we push an a or b respectively onto the stack and stay in state q0. When we encounter a c, we do not push anything on to the stack, but go to the next state, q1. While being in state q1, if we encounter an a or b, we match it with the a or b respectively on the stack and pop one a for each a or one b for each b seen, so that it matches w R against the contents of the stack and the matching starts after it encounters a c. Finally it accepts if the input is done and there are no more a s or b s on the stack. *This is a variation on the example 7.5 on the p. 181 of Lin book, for the language L = {ww R : w {a, b}}
5 L = NPDA { { } * } R wcw w a,b a, λ b, λ a b b,b b λ a, a λ c, λ λ λ, q 0 q 1 q 2 5
6 Instantaneous description of the automaton accepting L = {wcw R : w {a, b}} Σ = {a, b, c} Here is the machine definition. M = ({q0, q1, q2}, Σ, {a, b, }, δ, q0,, {q2}) Instantaneous description (ID): (current state, remaining input, stack) δ(q0, a, a) = {(q0, aa)}, δ(q0, b, a) = {(q0, ba)}, δ(q0, a, b) = {(q0, ab)}, δ(q0 0, b, b) = {(q0, 0 bb)}, δ(q0, a, ) = {(q0, a)}, δ(q0, b, ) = {(q0, b)}, δ(q0, c, ) ) = {(q1, )}, ) δ(q0, c, a) = {(q1, a)}, δ(q0, c, b) = {(q1, b)}, δ(q1, a, a) = {(q1, λ)}, δ(q1, b, b) = {(q1, λ)}, δ(q1, λ, ) = {(q2, )}. a, λ a a, a aa b, λ b a, b ab b,b λ b, b bb a,a λ c, λ λ λ, q 0 q 1 q 2
7 2. Construct NPDA that accepts the language L = {a n b m c n+m : n 0, m 0} with Σ = {a, b, c} The idea of machine construction: We construct M that accepts L. Firstitaccepts it the empty string (n=m=0). Further, for each a seen (if any) it pushes an a onto the stack. Then it pushes an a onto the stack for each b seen (if any). Thus after reading all as and bsin the input, the stack has na (w) + nb (w) as on it. It then pops one a for each c seen guaranteeing that na (w) + nb (w) = nc(w) and they are in the right order. Finally it accepts if the input is done and there are no more as on the stack. M = ({q0, q1, q2, q3, q4}, Σ, {a, }, δ, q0,, {q0, q4 })
8 NPDA L = { a n b m b n + m : n 0, m 0} a, λ a b, λ a c, a λ λ, λ λ λ, λ λ λ,λ q 0 q 1 q 3 q 2 8
9 Instantaneous description of the automaton accepting L = {a n b m c n+m : n 0, m 0} Σ = {a, b, c} Machine definition: M = ({q0, q1, q2, q3, q4}, Σ, {a, }, δ, q0,, {q0, q4 }) Instantaneous description (ID): (current state, remaining input, stack) δ(q0, λ, ) = {(q1, )}, δ(q1, a, ) = {(q1, a)}, δ(q1, a, a) = {(q1, aa)}, δ(q1, λ, a) = {(q2, a)}, δ(q1, λ, ) = {(q2, )}, δ(q2, 2 b, ) ) = {(q2, 2 a)}, δ(q2, b, a) = {(q2, aa)}, δ(q2, c, a) = {(q3, λ)}, δ(q3, c, a) ) = {(q3, λ)}, ) δ(q3, λ, ) = {(q4, λ)}. a, λ a b, λ a c, a λ λ, λ λ λ, λ λ λ, q 0 q 1 q 2 q 3 q 2
10 3. Construct NPDA that accepts the language L = {a n b m : n m 3n, n 0} with Σ = {a, b, c}. The idea of machine construction: We will construct M that accepts L. It accepts empty string. The state q0 keeps track of the n as encountered in the first part of the string and provides a chance for state q1 to match the bs to anywhere between n and 3n. It proceeds to state q2 from state q1 if the number of bs encountered is between n and 3n.
11 NPDA L { n m a b : n m 3n, 0} = n a, λ a, λ a aa b,a λ a, λ aaa b,a λ λ, q 0 q 1 q 2 11
12 Instantaneous description of the automaton accepting L = {a n b m : n m 3n, n 0} with Σ = {a, b, c}. Machine definition: M = ({q0, q1, q2 }, Σ, {a, b, }, δ, q0,, {q2 }) Instantaneousdescription (ID): (currentstate state, remaininginput input, stack) δ(q0, a, ) = {(q0, a)}, δ(q0, a, ) = {(q0, aa)}, δ(q0, a, ) = {(q0, aaa)}, δ(q0, a, a) = {(q0, aa)}, δ(q0, a, a) = {(q0, aaa)}, δ(q0, a, a) = {(q0, aaaa)}, δ(q0, b, a) = {(q1, λ)}, δ(q1, b, a) = {(q1, λ)}, δ(q1, λ, ) = {(q2, )} a, λ a a, λ aa a, λ aaa a,a a a,a aa a,a aaa b,a λ b,a λ λ, q 0 q 1 q 2
13 4. Construct NPDA that accepts the language L = {w : n a (w) = n b (w) + 1} with Σ = {a, b, c}. L { w : n ( w ) = n ( w ) +, w { a,b} * } = 1 a b The idea of machine construction: Machine M accepts L and it starts with one extra a on the stack and then uses the machine given in Example 7.4 in the Lin book to tell if the number of as and bsare the same. If they are and we started with one more a on the stack then the condition of L is met. Additionally, if it sees a c, it just reads it and does not modify the stack.
14 We start with a simpler machine that accepts the language: L w a,b : n ( w n w * = { { } ) = ( )} a( b Here we use Lin solution. He uses 0 to count a s which will be popped when b s bsare found. Assometimes sometimes in some prefix there may be more b s bs than a s we will find no 0 on the stack. In that case 1 is used that later on can be matched with a s.
15 NPDA for a simpler machine L * = { w { a,b} : n ( w ) = n ( w )} a b a, a, b, 1 b, 0 λ b, 1 11 a, 1 λ q 0 λ, q f
16 NPDA L { { } = } * w a,b : n ( w ) n ( w )+1 = ) a b λ,λ, q 0 a, a,0 a 0 00 b, 1 b, 0 λ b, 1 11 a, 1 λ λ, q 1 q2
17 Instantaneous description of the automaton accepting L = {w : n a (w) = n b (w) + 1} with Σ = {a, b, c}. M = ({q0, q1, q2}, Σ, {a, b, }, δ, q0,, {q2}) Instantaneous description (ID): (current state, remaining input, stack) δ(q0,, λ,, ) ) = {(q1, a)}, δ(q1, a, ) = {(q1, a)}, δ(q1, a, a) = {(q1, aa)}, b, 1 δ(q1, a, b) = {(q1, λ)}, b, 0 λ b, 1 11 a, 0 a, 1 λ δ(q1, b, ) ) = {(q1, b)}, a,0 00 δ(q1, b, a) = {(q1, λ)}, δ(q1, b, b) = {(q1, bb)}, λ,λ a λ, δ(q1, λ, ) = {(q2, λ)}, q 0 q 1 q2 δ(q1, c, ) = {(q1, c)}, δ(q1, c, a) = {(qa, a)}, δ(q1, c, b) = {(q1, b)}. In this solution a and b are used as counters instead of 0 and 1.
Pushdown Automata. place the input head on the leftmost input symbol. while symbol read = b and pile contains discs advance head remove disc from pile
Pushdown Automata In the last section we found that restricting the computational power of computing devices produced solvable decision problems for the class of sets accepted by finite automata. But along
Pushdown automata. Informatics 2A: Lecture 9. Alex Simpson. 3 October, 2014. School of Informatics University of Edinburgh [email protected].
Pushdown automata Informatics 2A: Lecture 9 Alex Simpson School of Informatics University of Edinburgh [email protected] 3 October, 2014 1 / 17 Recap of lecture 8 Context-free languages are defined by context-free
Honors Class (Foundations of) Informatics. Tom Verhoeff. Department of Mathematics & Computer Science Software Engineering & Technology
Honors Class (Foundations of) Informatics Tom Verhoeff Department of Mathematics & Computer Science Software Engineering & Technology www.win.tue.nl/~wstomv/edu/hci c 2011, T. Verhoeff @ TUE.NL 1/20 Information
Pushdown Automata. International PhD School in Formal Languages and Applications Rovira i Virgili University Tarragona, Spain
Pushdown Automata transparencies made for a course at the International PhD School in Formal Languages and Applications Rovira i Virgili University Tarragona, Spain Hendrik Jan Hoogeboom, Leiden http://www.liacs.nl/
Formal Languages and Automata Theory - Regular Expressions and Finite Automata -
Formal Languages and Automata Theory - Regular Expressions and Finite Automata - Samarjit Chakraborty Computer Engineering and Networks Laboratory Swiss Federal Institute of Technology (ETH) Zürich March
ÖVNINGSUPPGIFTER I SAMMANHANGSFRIA SPRÅK. 15 april 2003. Master Edition
ÖVNINGSUPPGIFTER I SAMMANHANGSFRIA SPRÅK 5 april 23 Master Edition CONTEXT FREE LANGUAGES & PUSH-DOWN AUTOMATA CONTEXT-FREE GRAMMARS, CFG Problems Sudkamp Problem. (3.2.) Which language generates the grammar
Scanner. tokens scanner parser IR. source code. errors
Scanner source code tokens scanner parser IR errors maps characters into tokens the basic unit of syntax x = x + y; becomes = + ; character string value for a token is a lexeme
Automata and Formal Languages
Automata and Formal Languages Winter 2009-2010 Yacov Hel-Or 1 What this course is all about This course is about mathematical models of computation We ll study different machine models (finite automata,
Intrusion Detection via Static Analysis
Intrusion Detection via Static Analysis IEEE Symposium on Security & Privacy 01 David Wagner Drew Dean Presented by Yongjian Hu Outline Introduction Motivation Models Trivial model Callgraph model Abstract
Regular Languages and Finite State Machines
Regular Languages and Finite State Machines Plan for the Day: Mathematical preliminaries - some review One application formal definition of finite automata Examples 1 Sets A set is an unordered collection
CSC4510 AUTOMATA 2.1 Finite Automata: Examples and D efinitions Definitions
CSC45 AUTOMATA 2. Finite Automata: Examples and Definitions Finite Automata: Examples and Definitions A finite automaton is a simple type of computer. Itsoutputislimitedto yes to or no. It has very primitive
Automata and Computability. Solutions to Exercises
Automata and Computability Solutions to Exercises Fall 25 Alexis Maciel Department of Computer Science Clarkson University Copyright c 25 Alexis Maciel ii Contents Preface vii Introduction 2 Finite Automata
CS103B Handout 17 Winter 2007 February 26, 2007 Languages and Regular Expressions
CS103B Handout 17 Winter 2007 February 26, 2007 Languages and Regular Expressions Theory of Formal Languages In the English language, we distinguish between three different identities: letter, word, sentence.
Chapter 7 Uncomputability
Chapter 7 Uncomputability 190 7.1 Introduction Undecidability of concrete problems. First undecidable problem obtained by diagonalisation. Other undecidable problems obtained by means of the reduction
Lempel-Ziv Coding Adaptive Dictionary Compression Algorithm
Lempel-Ziv Coding Adaptive Dictionary Compression Algorithm 1. LZ77:Sliding Window Lempel-Ziv Algorithm [gzip, pkzip] Encode a string by finding the longest match anywhere within a window of past symbols
Fundamentele Informatica II
Fundamentele Informatica II Answer to selected exercises 1 John C Martin: Introduction to Languages and the Theory of Computation M.M. Bonsangue (and J. Kleijn) Fall 2011 Let L be a language. It is clear
MACM 101 Discrete Mathematics I
MACM 101 Discrete Mathematics I Exercises on Combinatorics, Probability, Languages and Integers. Due: Tuesday, November 2th (at the beginning of the class) Reminder: the work you submit must be your own.
Turing Machines: An Introduction
CIT 596 Theory of Computation 1 We have seen several abstract models of computing devices: Deterministic Finite Automata, Nondeterministic Finite Automata, Nondeterministic Finite Automata with ɛ-transitions,
(IALC, Chapters 8 and 9) Introduction to Turing s life, Turing machines, universal machines, unsolvable problems.
3130CIT: Theory of Computation Turing machines and undecidability (IALC, Chapters 8 and 9) Introduction to Turing s life, Turing machines, universal machines, unsolvable problems. An undecidable problem
CMPSCI 250: Introduction to Computation. Lecture #19: Regular Expressions and Their Languages David Mix Barrington 11 April 2013
CMPSCI 250: Introduction to Computation Lecture #19: Regular Expressions and Their Languages David Mix Barrington 11 April 2013 Regular Expressions and Their Languages Alphabets, Strings and Languages
Data Structures and Algorithms V22.0102. Otávio Braga
Data Structures and Algorithms V22.0102 Otávio Braga We use a stack When an operand is read, output it When an operator is read Pop until the top of the stack has an element of lower precedence Then push
Compiler I: Syntax Analysis Human Thought
Course map Compiler I: Syntax Analysis Human Thought Abstract design Chapters 9, 12 H.L. Language & Operating Sys. Compiler Chapters 10-11 Virtual Machine Software hierarchy Translator Chapters 7-8 Assembly
Software Model Checking: Theory and Practice
Software Model Checking: Theory and Practice Lecture: Specification Checking - LTL Model Checking Copyright 2004, Matt Dwyer, John Hatcliff, and Robby. The syllabus and all lectures for this course are
CAs and Turing Machines. The Basis for Universal Computation
CAs and Turing Machines The Basis for Universal Computation What We Mean By Universal When we claim universal computation we mean that the CA is capable of calculating anything that could possibly be calculated*.
Introduction to Finite Automata
Introduction to Finite Automata Our First Machine Model Captain Pedro Ortiz Department of Computer Science United States Naval Academy SI-340 Theory of Computing Fall 2012 Captain Pedro Ortiz (US Naval
C H A P T E R Regular Expressions regular expression
7 CHAPTER Regular Expressions Most programmers and other power-users of computer systems have used tools that match text patterns. You may have used a Web search engine with a pattern like travel cancun
On Winning Conditions of High Borel Complexity in Pushdown Games
Fundamenta Informaticae (2005) 1 22 1 IOS Press On Winning Conditions of High Borel Complexity in Pushdown Games Olivier Finkel Equipe de Logique Mathématique U.F.R. de Mathématiques, Université Paris
The Halting Problem is Undecidable
185 Corollary G = { M, w w L(M) } is not Turing-recognizable. Proof. = ERR, where ERR is the easy to decide language: ERR = { x { 0, 1 }* x does not have a prefix that is a valid code for a Turing machine
Compiler Construction
Compiler Construction Regular expressions Scanning Görel Hedin Reviderad 2013 01 23.a 2013 Compiler Construction 2013 F02-1 Compiler overview source code lexical analysis tokens intermediate code generation
T-79.186 Reactive Systems: Introduction and Finite State Automata
T-79.186 Reactive Systems: Introduction and Finite State Automata Timo Latvala 14.1.2004 Reactive Systems: Introduction and Finite State Automata 1-1 Reactive Systems Reactive systems are a class of software
6.045: Automata, Computability, and Complexity Or, Great Ideas in Theoretical Computer Science Spring, 2010. Class 4 Nancy Lynch
6.045: Automata, Computability, and Complexity Or, Great Ideas in Theoretical Computer Science Spring, 2010 Class 4 Nancy Lynch Today Two more models of computation: Nondeterministic Finite Automata (NFAs)
Push-down Automata and Context-free Grammars
14 Push-down Automata and Context-free Grammars This chapter details the design of push-down automata (PDA) for various languages, the conversion of CFGs to PDAs, and vice versa. In particular, after formally
Automata Theory. Şubat 2006 Tuğrul Yılmaz Ankara Üniversitesi
Automata Theory Automata theory is the study of abstract computing devices. A. M. Turing studied an abstract machine that had all the capabilities of today s computers. Turing s goal was to describe the
7.1 Our Current Model
Chapter 7 The Stack In this chapter we examine what is arguably the most important abstract data type in computer science, the stack. We will see that the stack ADT and its implementation are very simple.
3515ICT Theory of Computation Turing Machines
Griffith University 3515ICT Theory of Computation Turing Machines (Based loosely on slides by Harald Søndergaard of The University of Melbourne) 9-0 Overview Turing machines: a general model of computation
Fast nondeterministic recognition of context-free languages using two queues
Fast nondeterministic recognition of context-free languages using two queues Burton Rosenberg University of Miami Abstract We show how to accept a context-free language nondeterministically in O( n log
Omega Automata: Minimization and Learning 1
Omega Automata: Minimization and Learning 1 Oded Maler CNRS - VERIMAG Grenoble, France 2007 1 Joint work with A. Pnueli, late 80s Summary Machine learning in general and of formal languages in particular
Algorithms and Data Structures
Algorithms and Data Structures Part 2: Data Structures PD Dr. rer. nat. habil. Ralf-Peter Mundani Computation in Engineering (CiE) Summer Term 2016 Overview general linked lists stacks queues trees 2 2
Regular Expressions and Automata using Haskell
Regular Expressions and Automata using Haskell Simon Thompson Computing Laboratory University of Kent at Canterbury January 2000 Contents 1 Introduction 2 2 Regular Expressions 2 3 Matching regular expressions
Last not not Last Last Next! Next! Line Line Forms Forms Here Here Last In, First Out Last In, First Out not Last Next! Call stack: Worst line ever!
ECE 551 C++ Programming, Data structures, and Algorithms Abstract Data Type: Stack Last In First Out (LIFO) 1 2 2 1 4 3 1 3 4 Stacks in Programming Worst line ever! 5 3 1 5 Stacks are not useful for waiting
SIF Validation Tool. Wages Protection System Qatar Central Bank& Ministry of Labour And Social Affairs. End User Guide
SIF Validation Tool Wages Protection System Qatar Central Bank& Ministry of Labour And Social Affairs End User Guide [1] SIF Validation Tool at a Glance Content 1 SIF VALIDATION TOOL AT A GLANCE 3 2 GETTING
Stack Allocation. Run-Time Data Structures. Static Structures
Run-Time Data Structures Stack Allocation Static Structures For static structures, a fixed address is used throughout execution. This is the oldest and simplest memory organization. In current compilers,
Appendix C: Keyboard Scan Codes
Thi d t t d ith F M k 4 0 2 Appendix C: Keyboard Scan Codes Table 90: PC Keyboard Scan Codes (in hex) Key Down Up Key Down Up Key Down Up Key Down Up Esc 1 81 [ { 1A 9A, < 33 B3 center 4C CC 1! 2 82 ]
Informatique Fondamentale IMA S8
Informatique Fondamentale IMA S8 Cours 1 - Intro + schedule + finite state machines Laure Gonnord http://laure.gonnord.org/pro/teaching/ [email protected] Université Lille 1 - Polytech Lille
SOLUTION Trial Test Grammar & Parsing Deficiency Course for the Master in Software Technology Programme Utrecht University
SOLUTION Trial Test Grammar & Parsing Deficiency Course for the Master in Software Technology Programme Utrecht University Year 2004/2005 1. (a) LM is a language that consists of sentences of L continued
Course Manual Automata & Complexity 2015
Course Manual Automata & Complexity 2015 Course code: Course homepage: Coordinator: Teachers lectures: Teacher exercise classes: Credits: X_401049 http://www.cs.vu.nl/~tcs/ac prof. dr. W.J. Fokkink home:
Administrative Services of Kansas
Administrative Services of Kansas ANSI X12N 837D V4010A1 Health Care Claim Companion Guide - Dental, INC BlueCross BlueShield of Western New York BlueShield of Northeastern New York Last Updated March
ASSIGNMENT ONE SOLUTIONS MATH 4805 / COMP 4805 / MATH 5605
ASSIGNMENT ONE SOLUTIONS MATH 4805 / COMP 4805 / MATH 5605 (1) (a) (0 + 1) 010 (finite automata below). (b) First observe that the following regular expression generates the binary strings with an even
CS143 Handout 08 Summer 2008 July 02, 2007 Bottom-Up Parsing
CS143 Handout 08 Summer 2008 July 02, 2007 Bottom-Up Parsing Handout written by Maggie Johnson and revised by Julie Zelenski. Bottom-up parsing As the name suggests, bottom-up parsing works in the opposite
Automata and Formal Languages. Push Down Automata. Sipser pages 109-114. Lecture 13. Tim Sheard 1
Automata and Formal Languages Push Down Automata Sipser pages 109-114 Lecture 13 Tim Sheard 1 Push Down Automata Push Down Automata (PDAs) are ε-nfas with stack memory. Transitions are labeled by an input
Implementation of Recursively Enumerable Languages using Universal Turing Machine in JFLAP
International Journal of Information and Computation Technology. ISSN 0974-2239 Volume 4, Number 1 (2014), pp. 79-84 International Research Publications House http://www. irphouse.com /ijict.htm Implementation
2110711 THEORY of COMPUTATION
2110711 THEORY of COMPUTATION ATHASIT SURARERKS ELITE Athasit Surarerks ELITE Engineering Laboratory in Theoretical Enumerable System Computer Engineering, Faculty of Engineering Chulalongkorn University
How to Make the Most of Excel Spreadsheets
How to Make the Most of Excel Spreadsheets Analyzing data is often easier when it s in an Excel spreadsheet rather than a PDF for example, you can filter to view just a particular grade, sort to view which
PROGRAMMING CONCEPTS AND EMBEDDED PROGRAMMING IN C, C++ and JAVA: Lesson-4: Data Structures: Stacks
PROGRAMMING CONCEPTS AND EMBEDDED PROGRAMMING IN C, C++ and JAVA: Lesson-4: Data Structures: Stacks 1 STACK A structure with a series of data elements with last sent element waiting for a delete operation.
CS154. Turing Machines. Turing Machine. Turing Machines versus DFAs FINITE STATE CONTROL AI N P U T INFINITE TAPE. read write move.
CS54 Turing Machines Turing Machine q 0 AI N P U T IN TAPE read write move read write move Language = {0} q This Turing machine recognizes the language {0} Turing Machines versus DFAs TM can both write
Regular Languages and Finite Automata
Regular Languages and Finite Automata 1 Introduction Hing Leung Department of Computer Science New Mexico State University Sep 16, 2010 In 1943, McCulloch and Pitts [4] published a pioneering work on a
2) Write in detail the issues in the design of code generator.
COMPUTER SCIENCE AND ENGINEERING VI SEM CSE Principles of Compiler Design Unit-IV Question and answers UNIT IV CODE GENERATION 9 Issues in the design of code generator The target machine Runtime Storage
Board Notes on Virtual Memory
Board Notes on Virtual Memory Part A: Why Virtual Memory? - Letʼs user program size exceed the size of the physical address space - Supports protection o Donʼt know which program might share memory at
Automata on Infinite Words and Trees
Automata on Infinite Words and Trees Course notes for the course Automata on Infinite Words and Trees given by Dr. Meghyn Bienvenu at Universität Bremen in the 2009-2010 winter semester Last modified:
Overview of E0222: Automata and Computability
Overview of E0222: Automata and Computability Deepak D Souza Department of Computer Science and Automation Indian Institute of Science, Bangalore. August 3, 2011 What this course is about What we study
Reading 13 : Finite State Automata and Regular Expressions
CS/Math 24: Introduction to Discrete Mathematics Fall 25 Reading 3 : Finite State Automata and Regular Expressions Instructors: Beck Hasti, Gautam Prakriya In this reading we study a mathematical model
Windows Performance Monitor Troubleshooting Guide
Windows Performance Monitor Troubleshooting Guide Document Owner - Support Version Control Alan Davis Author John Nuttall Windows Performance counter troubleshooting guide This document is designed to
How to Format a Bibliography or References List in the American University Thesis and Dissertation Template
PC Word 2010/2007 Bibliographies and References Lists Page 1 of 7 Click to Jump to a Topic How to Format a Bibliography or References List in the American University Thesis and Dissertation Template In
RULE 1: Additive Identity Property
RULE 1: Additive Identity Property Additive Identity Property a + 0 = a x + 0 = x If we add 0 to any number, we will end up with the same number. Zero is represented through the the green vortex. When
The Optimum One-Pass Strategy for Juliet
Master s Thesis One-Pass Strategies for Context-Free Games Christian Cöster August 2015 Examiners: Prof. Dr. Thomas Schwentick Prof. Dr. Christoph Buchheim Technische Universität Dortmund Fakultät für
DATA STRUCTURES USING C
DATA STRUCTURES USING C QUESTION BANK UNIT I 1. Define data. 2. Define Entity. 3. Define information. 4. Define Array. 5. Define data structure. 6. Give any two applications of data structures. 7. Give
Increasing Interaction and Support in the Formal Languages and Automata Theory Course
Increasing Interaction and Support in the Formal Languages and Automata Theory Course [Extended Abstract] Susan H. Rodger [email protected] Jinghui Lim Stephen Reading ABSTRACT The introduction of educational
Levels of Programming Languages. Gerald Penn CSC 324
Levels of Programming Languages Gerald Penn CSC 324 Levels of Programming Language Microcode Machine code Assembly Language Low-level Programming Language High-level Programming Language Levels of Programming
A laboratory work: A teaching robot arm for mechanics and electronic circuits
A laboratory work: A teaching robot arm for mechanics and electronic circuits Omer Sise * Department of Physics, Kocatepe University, Science and Art Faculty, Afyon, 03200, Turkey * e-mail: [email protected]
Bottom-Up Syntax Analysis LR - metódy
Bottom-Up Syntax Analysis LR - metódy Ján Šturc Shift-reduce parsing LR methods (Left-to-right, Righ most derivation) SLR, Canonical LR, LALR Other special cases: Operator-precedence parsing Backward deterministic
How to Read Music Notation
How to Read Music Notation The New School of American Music IN JUST 30 MINUTES! C D E F G A B C D E F G A B C D E F G A B C D E F G A B C D E F G A B C D E 1. MELODIES The first thing to learn about reading
Outline. Computer Science 331. Stack ADT. Definition of a Stack ADT. Stacks. Parenthesis Matching. Mike Jacobson
Outline Computer Science 1 Stacks Mike Jacobson Department of Computer Science University of Calgary Lecture #12 1 2 Applications Array-Based Linked List-Based 4 Additional Information Mike Jacobson (University
Addressing The problem. When & Where do we encounter Data? The concept of addressing data' in computations. The implications for our machine design(s)
Addressing The problem Objectives:- When & Where do we encounter Data? The concept of addressing data' in computations The implications for our machine design(s) Introducing the stack-machine concept Slide
Storage Classes CS 110B - Rule Storage Classes Page 18-1 \handouts\storclas
CS 110B - Rule Storage Classes Page 18-1 Attributes are distinctive features of a variable. Data type, int or double for example, is an attribute. Storage class is another attribute. There are four storage
BEGINNING ALGEBRA ACKNOWLEDMENTS
BEGINNING ALGEBRA The Nursing Department of Labouré College requested the Department of Academic Planning and Support Services to help with mathematics preparatory materials for its Bachelor of Science
NetPortal All your documents, direct to your iphone
Copyright Stratospherix 2010 Apple, the Apple logo, ipod, ipod touch, and itunes are trademarks of Apple Inc., registered in the U.S. and other countries. iphone is a trademark of Apple Inc. App Store
Working with Visio Connectors
Working with Visio Connectors Overview Connectors are lines that connect your shapes. Once a connection has been made, when the shape is moved, the connector points stay connected and move with the shape.
Table 1 Comparison of DC, Uni-Polar and Bi-polar Stepper Motors
Electronics Exercise 3: Uni-Polar Stepper Motor Controller / Driver Mechatronics Instructional Laboratory Woodruff School of Mechanical Engineering Georgia Institute of Technology Lab Director: I. Charles
How To Compare A Markov Algorithm To A Turing Machine
Markov Algorithm CHEN Yuanmi December 18, 2007 1 Abstract Markov Algorithm can be understood as a priority string rewriting system. In this short paper we give the definition of Markov algorithm and also
An Introduction to Assembly Programming with the ARM 32-bit Processor Family
An Introduction to Assembly Programming with the ARM 32-bit Processor Family G. Agosta Politecnico di Milano December 3, 2011 Contents 1 Introduction 1 1.1 Prerequisites............................. 2
Excel supplement: Chapter 7 Matrix and vector algebra
Excel supplement: Chapter 7 atrix and vector algebra any models in economics lead to large systems of linear equations. These problems are particularly suited for computers. The main purpose of this chapter
How to create PDF maps, pdf layer maps and pdf maps with attributes using ArcGIS. Lynne W Fielding, GISP Town of Westwood
How to create PDF maps, pdf layer maps and pdf maps with attributes using ArcGIS Lynne W Fielding, GISP Town of Westwood PDF maps are a very handy way to share your information with the public as well
Finite Automata and Regular Languages
CHAPTER 3 Finite Automata and Regular Languages 3. Introduction 3.. States and Automata A finite-state machine or finite automaton (the noun comes from the Greek; the singular is automaton, the Greek-derived
ECDL. European Computer Driving Licence. Spreadsheet Software BCS ITQ Level 2. Syllabus Version 5.0
European Computer Driving Licence Spreadsheet Software BCS ITQ Level 2 Using Microsoft Excel 2010 Syllabus Version 5.0 This training, which has been approved by BCS, The Chartered Institute for IT, includes
Monitoring and Analyzing Switch Operation
B Monitoring and Analyzing Switch Operation Contents Overview..................................................... B-3....................................... B-4 Menu Access To Status and Counters.........................
Compilers. Introduction to Compilers. Lecture 1. Spring term. Mick O Donnell: [email protected] Alfonso Ortega: alfonso.ortega@uam.
Compilers Spring term Mick O Donnell: [email protected] Alfonso Ortega: [email protected] Lecture 1 to Compilers 1 Topic 1: What is a Compiler? 3 What is a Compiler? A compiler is a computer
Konica Minolta s Optimised Print Services (OPS)
Konica Minolta s Optimised Print Services (OPS) Document Collection Agent (DCA) System Requirements V1.1 Page 1 of 6 Table of Contents Installation location... 3 Network requirements... 4 System requirements...
Ź Ź ł ź Ź ś ź ł ź Ś ę ż ż ł ż ż Ż Ś ę Ż Ż ę ś ź ł Ź ł ł ż ż ź ż ż Ś ę ż ż Ź Ł Ż Ż Ą ż ż ę ź Ń Ź ś ł ź ż ł ś ź ź Ą ć ś ś Ź Ś ę ę ć ż Ź Ą Ń Ą ł ć ć ł ł ź ę Ś ę ś ę ł ś ć ź ś ł ś ł ł ł ł ć ć Ś ł ź Ś ł
GCM for Android Setup Guide
GCM for Android Setup Guide This guide provides information on...... Prerequisites for using Google Cloud Messaging service... Instructions for setting up GCM service via the Google API console... Configuring
Assignment Kits. Summary Kit Contents Lecture 1: Kit cover sheet (page 40)
Assignment Kits These assignment kits contain the forms students need to do the assignments in the textbook A Discipline for Software Engineering by Watts S. Humphrey. In using them: - Provide each student
Theory of Computation Chapter 2: Turing Machines
Theory of Computation Chapter 2: Turing Machines Guan-Shieng Huang Feb. 24, 2003 Feb. 19, 2006 0-0 Turing Machine δ K 0111000a 01bb 1 Definition of TMs A Turing Machine is a quadruple M = (K, Σ, δ, s),
Web Data Extraction: 1 o Semestre 2007/2008
Web Data : Given Slides baseados nos slides oficiais do livro Web Data Mining c Bing Liu, Springer, December, 2006. Departamento de Engenharia Informática Instituto Superior Técnico 1 o Semestre 2007/2008
