ASSIGNMENT ONE SOLUTIONS MATH 4805 / COMP 4805 / MATH 5605

Size: px
Start display at page:

Download "ASSIGNMENT ONE SOLUTIONS MATH 4805 / COMP 4805 / MATH 5605"

Transcription

1 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 number of 0s and an odd number of 1s r = ( ( )( ) ( )). Next observe that the following regular expression generates the binary strings with an even number of 0s and an odd number of 1s with the additional property that no prefix has even number of 0s and an odd number of 1s s = (1 + ( )( ) 0). Any string that has an even number of 0s and an odd number of 1s must have a longest prefix that has an even number of 0s and an even number of 1s, followed by a suffix that has an even number of 0s and an odd number of 1s. Therefore, a regular expression for the language is rs (finite automata below). (2) (a) Connect passwords Must be between 6 and 8 characters long so there are a finite number of possibilities. Thus, connect passwords are a finite language, and hence a recognizable language. (b) Consider the following languages that are recognizable (or equivalently, regular). The finite automaton below accepts strings that have length at least six. Given any a, b, c A the following regular expression generates strings that have the substring abc: A abca. Therefore, by the closure of regular languages under union, the strings containing a substring of length three in any fixed login name is a regular language. Therefore, by the closure 1

2 of regular language under complement, the strings that do not contain a substring of length three in any fixed login name is a regular language. The following regular expression generates strings that have a substring that is a postal code: A UDUDUDA. Therefore, by the closure of regular language under complement, the strings that do not contain a substring that is a postal code is a regular language. The following regular expression generates strings that have a substring that is a license plate: A UUUDDDA. Therefore, by the closure of regular language under complement, the strings that do not contain a substring that is a license plate is a regular language. In the previous three bullets, replace the initial regular expressions by (i) A cbaa, (ii) A DUDUDUA, and (iii) A DDDUUUA to prove that the strings whose reverse does not contain the given substrings is a regular language, respectively. Next we consider avoiding the desired substrings in ww instead of the reverse of w. In the previous three bullets, replace the initial regular expressions by (i) A abca +bca a+ca ab, (ii) A UDUDUDA +DA UDUDU+ UDA UDUD + DUDA UDU + UDUDA UD + DUDUDA U, and (iii) A UUUDDDA +DA UUUDD+DDA UUUD+DDDA UUU+UDDDA UU+ UUDDDA U to prove that the strings whose concatenation with themselves (ie ww) does not contain the given substrings is a regular language, respectively. Observe that if w is a string of length at least six (as per the first bullet) and s is a string of length at most six (as in the previous three bullets), then some string in w contains s as a substring if and only if ww contains s as a substring. Therefore, the strings of length at least six whose Kleene closure does not contain the given substrings is a regular language by using the same logic above. The following non-deterministic finite automaton accepts strings that contain a symbol in Q. Therefore, by the closure of regular language under complement, the strings that do not contain a symbol in Q is a regular language. Let a 1, a 2, a 3 A. The following regular expression generates strings that contain only these three symbols: (a 1 + a 2 + a 3 ). By considering all choices for a 1, a 2, and a 3 and by the closure of regular languages under union, the set of strings containing at most three distinct symbols is a regular language. By the closure of regular languages under complement, the set of strings that contain at least four distinct symbols is regular. The following regular expression generates strings whose first six symbols contain at least one symbol from L U, one symbol from D, and one symbol from P. In this regular expression, the terms are simply the permutations of the multiset {A, A, A, (L+U), D, P } (ensuring that the first six symbols contain the desired three types of symbols) followed by A. To be complete, 2

3 the full regular expression appears below. AAA(L + U)DP A + AAA(L + U)P DA + AAAD(L + U)P A + AAADP (L + U)A + AAAP (L + U)DA + AAAP D(L + U)A + AA(L + U)ADP A + AA(L + U)AP DA + AA(L + U)DAP A + AA(L + U)DP AA + AA(L + U)P ADA + AA(L + U)P DAA + AADA(L + U)P A + AADAP (L + U)A + AAD(L + U)AP A + AAD(L + U)P AA + AADP A(L + U)A + AADP (L + U)AA + AAP A(L + U)DA + AAP AD(L + U)A + AAP (L + U)ADA + AAP (L + U)DAA + AAP DA(L + U)A + AAP D(L + U)AA + A(L + U)AADP A + A(L + U)AAP DA + A(L + U)ADAP A + A(L + U)ADP AA + A(L + U)AP ADA + A(L + U)AP DAA + A(L + U)DAAP A + A(L + U)DAP AA + A(L + U)DP AAA + A(L + U)P AADA + A(L + U)P ADAA + A(L + U)P DAAA + ADAA(L + U)P A + ADAAP (L + U)A + ADA(L + U)AP A + ADA(L + U)P AA + ADAP A(L + U)A + ADAP (L + U)AA + AD(L + U)AAP A + AD(L + U)AP AA + AD(L + U)P AAA + ADP AA(L + U)A + ADP A(L + U)AA + ADP (L + U)AAA + AP AA(L + U)DA + AP AAD(L + U)A + AP A(L + U)ADA + AP A(L + U)DAA + AP ADA(L + U)A + AP AD(L + U)AA + AP (L + U)AADA + AP (L + U)ADAA + AP (L + U)DAAA + AP DAA(L + U)A + AP DA(L + U)AA + AP D(L + U)AAA + (L + U)AAADP A + (L + U)AAAP DA + (L + U)AADAP A + (L + U)AADP AA + (L + U)AAP ADA + (L + U)AAP DAA + (L + U)ADAAP A + (L + U)ADAP AA + (L + U)ADP AAA + (L + U)AP AADA + (L + U)AP ADAA + (L + U)AP DAAA + (L + U)DAAAP A + (L + U)DAAP AA + (L + U)DAP AAA + (L + U)DP AAAA + (L + U)P AAADA + (L + U)P AADAA + (L + U)P ADAAA + (L + U)P DAAAA + DAAA(L + U)P A + DAAAP (L + U)A + DAA(L + U)AP A + DAA(L + U)P AA + DAAP A(L + U)A + DAAP (L + U)AA + DA(L + U)AAP A + DA(L + U)AP AA + DA(L + U)P AAA + DAP AA(L + U)A + DAP A(L + U)AA + DAP (L + U)AAA + D(L + U)AAAP A + D(L + U)AAP AA + D(L + U)AP AAA + D(L + U)P AAAA + DP AAA(L + U)A + DP AA(L + U)AA + DP A(L + U)AAA + DP (L + U)AAAA + P AAA(L + U)DA + P AAAD(L + U)A + P AA(L + U)ADA + P AA(L + U)DAA + P AADA(L + U)A + P AAD(L + U)AA + P A(L + U)AADA + P A(L + U)ADAA + P A(L + U)DAAA + P ADAA(L + U)A + P ADA(L + U)AA + P AD(L + U)AAA + P (L + U)AAADA + P (L + U)AADAA + P (L + U)ADAAA + P (L + U)DAAAA + P DAAA(L + U)A + P DAA(L + U)AA + P DA(L + U)AAA + P D(L + U)AAAA For the overall proof, observe that each bullet above proves that certain languages are regular. Moreover, the intersection of these languages are precisely the passwords defined in the question. Therefore, passwords are a regular language by the closure of regular languages under intersection. (3) (a) No, L p is not recognizable. Consider the string w = 1 n 01 n, where n is the pumping constant for L p. Observe that w L p and w n. Consider any x, y, z {0, 1} such that (i) w = xyz, (ii) xy n, and (iii) y > 0. By these constraints, x = 1 a, y = 1 b, and z = 1 c 01 n where a 0, b > 0, and a + b + c = n. If i = 0, then xy i z = xz = 1 a+c 01 n = 1 a+c 01 a+b+c / L p since b > 0. Therefore, L p does not satisfy the pumping property, and hence L p is not regular. (b) Yes, L e is recognizable. Suppose w {0, 1} and let n 01 be its number of 01 substrings and let n 10 be its number of 10 substrings. Observe that n if w begins with 0 and w ends with 1 n 01 = n 10 1 if w begins with 1 and w ends with 0 n 10 otherwise 3

4 where the final case includes (i) w = ɛ, (ii) w begins and ends with 0, and (iii) w begins and ends with 1. Therefore, L e is generated by the regular expression ɛ (0 + 1) 0 + 1(0 + 1) 1. Therefore, L e is regular, and hence L e is recognizable. (4) (a) Consider an arbitrary w = w 1 w 2 w n L a, where each w i {0, 1}. Observe that w can be expressed as w = 0 r 1 s 2 t where r 0 = (s = t). Let x = ɛ, y = w 1, and z = w 2 w 3 w n. Observe that these choices ensure (i) w = xyz, (ii) xy n, and (iii) y > 0, where n is the pumping constant for L a. We wish to prove that (iv) xy i z L a for all i 0. There are two cases to consider. If r 0, then xy i z = 0 r 1+i 1 s 2 t for all i 0. In this case, s = t by the implication given above. Therefore, xy i z = 0 r 1+i 1 s 2 s L for all i 0. On the other and, if r = 0, then xy i z = 1 s 1+i 2 t. Therefore, xy i z L a for all i 0. Therefore, L a satisfies the pumping property. (b) The difference between the pumping property and the generalized pumping property is that the former gives conditions on a prefix of length at most n in each string, whereas the latter gives conditions on a substring of length at most n in each string. (c) Consider the string pws with p = 0, w = 1 n 2 n, and s = ɛ, where n is the generalized pumping constant. Observe that pws = 01 n 2 n L a and w n. Consider any x, y, z {0, 1, 2} such that (i) w = xyz, (ii) xy n, and (iii) y > 0. By these constraints, x = 1 a, y = 1 b, and z = 1 c 2 n where a 0, b > 0, and a + b + c = n. If i = 0, then pxy i zs = 0xz = 01 a+c 2 n = 01 a+c 2 a+b+c / L a since b > 0. Therefore, L a does not satisfy the generalized pumping property. (d) If L is a recognizable language, then there exists some finite automata M = (S, A, s, δ, F ) such that L(M) = L. Let n = S be the number of states in M. Consider a string pws L with w n. Let w = w 1 w 2 w m where each w i A and m n. Consider the states s j = δ (s, pw 1 w 2 w j ) for j = 0, 1,..., n. Since there are only S = n states, there must be a repetition among s 0, s 1,..., s n. Let r and t be chosen such that s r = s t and 0 r < t n. Now consider the strings x = w 0 w 1 w r, y = w r+1 w r+2 w + t, and z = w r+1 w r+2 w t. Observe that the repeated state implies that δ (s, pxy i zs) = δ (s t, zs) for all i 0. Furthermore, the state δ (s t, zs) F since pws = pxyzs L. Therefore, pxy i zs L for all i 0. (5) (a) The language L s = {w A w has suffix s} is recognizable. Therefore, if L is recognizable then so is L L s by the closure of recognizable languages under intersection. Observe that L L s contains all strings in L that have suffix s. Therefore, L L s = L/s, and so L/s is recognizable. (b) Let S = S 1 S 2, i = {(i i, i 2 )} 1, F = (F 1 (S 2 \F 2 )) (F 2 (S 1 \F 1 )), and define δ : S A P (S) by δ((x, y), a) = {(δ 1 (x, a), δ 2 (y, a))} for all (x, y) S and a A. Observe that M is essentially a (deterministic) finite-automata and that it accepts the desired language. 1 This i should have been stated as I in the question since it is a set of states. 4

5 (c) If L is recognizable, then there exists a finite automata M = (S, A, i, δ, F ) such that L(M) = L. We will construct an ɛ-finite automata M (S, B, I, δ, F ) as follows. S is a set of states that includes those in S as well as additional states to be defined, and the set of initial states I = {i} includes only the single initial state from M. The basic idea is to replace each arc labeled a in M by a path whose arcs are labeled with the symbols in f(a) Formally, define δ : S B P (S ) as follows. If f(a) = ɛ for a A, then for each s S let δ (s, ɛ) = {δ(s, a)}. If f(a) = b for a A and b B, then for each s S let δ (s, ɛ) = {δ(s, a)}. (6) (a) δ (s 1, 1) = s 0 / F and δ (s 2, 1) = s 1 F so s 1 M s 2. (b) See the tables below. Partition Table for S/ M s 1 s 2 s 3 s 4 s 5 s 6 x 0 x 0 x 0 x 0 x 0 s 0 x 1 x 0 x 1 s 1 x 1 x 0 x 1 s 2 x 0 x 1 s 3 x 0 x 0 s 4 x 1 s 5 Table (0,4) (1,5) (4,0) (1,2) (3,1) (2,0) (1,3) (3,3) (2,6) (1,5) (3,1) (2,6) (1,6) (3,1) (2,4) (2,3) (1,3) (0,6) (2,5) (1,1) (0,6) (2,6) (1,1) (0,4) (3,5) (3,1) (6,6) (3,6) (3,1) (6,4) (5,6) (1,1) (6,4) Table (0,4) (1,5) (4,0) (1,3) (3,3) (2,6) (1,5) (3,1) (2,6) (2,6) (1,1) (0,4) (3,5) (3,1) (6,6) (c) The language is {w {0, 1} w has suffix 0 or 01}. See the minimal automata below. (7) The finite automaton is given by the transition table below. (The shortest strings that distinguish between each pair of states are given in parentheses.) 5

6 0 1 {a} {b, d} {b} (ɛ) {b} {c} {b, c} (1) {b, d} {c} {a, b, c} (0) {c} {d} {a} (10) {b, c} {c, d} {a, b, c} (11) {a, b, c} {b, c, d} {a, b, c} (01) {d} {a} (100) {c, d} {d} {a} (110) {b, c, d} {c, d} {a, b, c} (010) (1000) In the above table and denote the start state and final states, respectively. (8) (a) See the table below. (b) See the table below. (c) See the table below. state x E(x) E(x) a E(x) b E(E(x) a) E(E(x) b) s 1 {s 1, s 2 } {s 4 } {s 1, s 2, s 3, s 4 } s 2 {s 2 } {s 4 } {s 1, s 2, s 3, s 4 } s 3 {s 1, s 2, s 3 } {s 2, s 4 } {s 1 } {s 1, s 2, s 3, s 4 } {s 1, s 2 } s 4 {s 1, s 2, s 3, s 4 } {s 2, s 4 } {s 1 } {s 1, s 2, s 3, s 4 } {s 1, s 2 } (d) See the NFA below. (9) Since L 1 and L 2 are recognizable languages there are finite automata that accept these languages. Let M 1 = (S 1, A 1, δ 1, F 1, i 1 ) and M 2 = (S 2, A 2, δ 2, F 2, i 2 ) be finite automata such that L(M 1 ) = L 1 and L(M 2 ) = L 2. Consider the non-deterministic finite automata M = (S, A, δ, F, i) such that S = S 1 S 2 {1, 2}, A = A 1 A 2, F = F 1 F 2 {1}, i = {(i 1, i 2, 1)} and δ is defined as follows. If a 1 A 1 then, and if a 2 A 2 then, δ((s 1, s 2, 1), a 1 ) = {(δ 1 (s 1, a 1 ), s 2, 2)} δ((s 1, s 2, 2), a 2 ) = {(s 1, δ 2 (s 2, a 2 ), 1)} and for all other inputs, δ returns the empty set. Observe that M accepts the shuffle of L 1 and L 2. Therefore, the shuffle of two regular languages is also a regular language. 6

Formal Languages and Automata Theory - Regular Expressions and Finite Automata -

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

More information

Automata and Formal Languages

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,

More information

Automata and Computability. Solutions to Exercises

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

More information

Reading 13 : Finite State Automata and Regular Expressions

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

More information

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 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)

More information

Regular Languages and Finite State Machines

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

More information

C H A P T E R Regular Expressions regular expression

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

More information

(IALC, Chapters 8 and 9) Introduction to Turing s life, Turing machines, universal machines, unsolvable problems.

(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

More information

CS103B Handout 17 Winter 2007 February 26, 2007 Languages and Regular Expressions

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.

More information

Regular Expressions and Automata using Haskell

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

More information

Fundamentele Informatica II

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

More information

1. Prove that the empty set is a subset of every set.

1. Prove that the empty set is a subset of every set. 1. Prove that the empty set is a subset of every set. Basic Topology Written by Men-Gen Tsai email: b89902089@ntu.edu.tw Proof: For any element x of the empty set, x is also an element of every set since

More information

Scanner. tokens scanner parser IR. source code. errors

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

More information

Automata on Infinite Words and Trees

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:

More information

Deterministic Finite Automata

Deterministic Finite Automata 1 Deterministic Finite Automata Definition: A deterministic finite automaton (DFA) consists of 1. a finite set of states (often denoted Q) 2. a finite set Σ of symbols (alphabet) 3. a transition function

More information

Finite Automata. Reading: Chapter 2

Finite Automata. Reading: Chapter 2 Finite Automata Reading: Chapter 2 1 Finite Automata Informally, a state machine that comprehensively captures all possible states and transitions that a machine can take while responding to a stream (or

More information

Finite Automata. Reading: Chapter 2

Finite Automata. Reading: Chapter 2 Finite Automata Reading: Chapter 2 1 Finite Automaton (FA) Informally, a state diagram that comprehensively captures all possible states and transitions that a machine can take while responding to a stream

More information

Automata Theory. Şubat 2006 Tuğrul Yılmaz Ankara Üniversitesi

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

More information

Finite Automata and Regular Languages

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

More information

CS5236 Advanced Automata Theory

CS5236 Advanced Automata Theory CS5236 Advanced Automata Theory Frank Stephan Semester I, Academic Year 2012-2013 Advanced Automata Theory is a lecture which will first review the basics of formal languages and automata theory and then

More information

Lights and Darks of the Star-Free Star

Lights and Darks of the Star-Free Star Lights and Darks of the Star-Free Star Edward Ochmański & Krystyna Stawikowska Nicolaus Copernicus University, Toruń, Poland Introduction: star may destroy recognizability In (finitely generated) trace

More information

Lecture 17 : Equivalence and Order Relations DRAFT

Lecture 17 : Equivalence and Order Relations DRAFT CS/Math 240: Introduction to Discrete Mathematics 3/31/2011 Lecture 17 : Equivalence and Order Relations Instructor: Dieter van Melkebeek Scribe: Dalibor Zelený DRAFT Last lecture we introduced the notion

More information

Compiler Construction

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

More information

SOLUTIONS TO ASSIGNMENT 1 MATH 576

SOLUTIONS TO ASSIGNMENT 1 MATH 576 SOLUTIONS TO ASSIGNMENT 1 MATH 576 SOLUTIONS BY OLIVIER MARTIN 13 #5. Let T be the topology generated by A on X. We want to show T = J B J where B is the set of all topologies J on X with A J. This amounts

More information

Testing LTL Formula Translation into Büchi Automata

Testing LTL Formula Translation into Büchi Automata Testing LTL Formula Translation into Büchi Automata Heikki Tauriainen and Keijo Heljanko Helsinki University of Technology, Laboratory for Theoretical Computer Science, P. O. Box 5400, FIN-02015 HUT, Finland

More information

Lecture 2: Regular Languages [Fa 14]

Lecture 2: Regular Languages [Fa 14] Caveat lector: This is the first edition of this lecture note. Please send bug reports and suggestions to jeffe@illinois.edu. But the Lord came down to see the city and the tower the people were building.

More information

THE BANACH CONTRACTION PRINCIPLE. Contents

THE BANACH CONTRACTION PRINCIPLE. Contents THE BANACH CONTRACTION PRINCIPLE ALEX PONIECKI Abstract. This paper will study contractions of metric spaces. To do this, we will mainly use tools from topology. We will give some examples of contractions,

More information

CSC4510 AUTOMATA 2.1 Finite Automata: Examples and D efinitions Definitions

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

More information

Mathematics for Computer Science/Software Engineering. Notes for the course MSM1F3 Dr. R. A. Wilson

Mathematics for Computer Science/Software Engineering. Notes for the course MSM1F3 Dr. R. A. Wilson Mathematics for Computer Science/Software Engineering Notes for the course MSM1F3 Dr. R. A. Wilson October 1996 Chapter 1 Logic Lecture no. 1. We introduce the concept of a proposition, which is a statement

More information

Baltic Way 1995. Västerås (Sweden), November 12, 1995. Problems and solutions

Baltic Way 1995. Västerås (Sweden), November 12, 1995. Problems and solutions Baltic Way 995 Västerås (Sweden), November, 995 Problems and solutions. Find all triples (x, y, z) of positive integers satisfying the system of equations { x = (y + z) x 6 = y 6 + z 6 + 3(y + z ). Solution.

More information

CS 3719 (Theory of Computation and Algorithms) Lecture 4

CS 3719 (Theory of Computation and Algorithms) Lecture 4 CS 3719 (Theory of Computation and Algorithms) Lecture 4 Antonina Kolokolova January 18, 2012 1 Undecidable languages 1.1 Church-Turing thesis Let s recap how it all started. In 1990, Hilbert stated a

More information

Regular Languages and Finite Automata

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

More information

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 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

More information

Informatique Fondamentale IMA S8

Informatique Fondamentale IMA S8 Informatique Fondamentale IMA S8 Cours 1 - Intro + schedule + finite state machines Laure Gonnord http://laure.gonnord.org/pro/teaching/ Laure.Gonnord@polytech-lille.fr Université Lille 1 - Polytech Lille

More information

The Goldberg Rao Algorithm for the Maximum Flow Problem

The Goldberg Rao Algorithm for the Maximum Flow Problem The Goldberg Rao Algorithm for the Maximum Flow Problem COS 528 class notes October 18, 2006 Scribe: Dávid Papp Main idea: use of the blocking flow paradigm to achieve essentially O(min{m 2/3, n 1/2 }

More information

The Halting Problem is Undecidable

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

More information

I. GROUPS: BASIC DEFINITIONS AND EXAMPLES

I. GROUPS: BASIC DEFINITIONS AND EXAMPLES I GROUPS: BASIC DEFINITIONS AND EXAMPLES Definition 1: An operation on a set G is a function : G G G Definition 2: A group is a set G which is equipped with an operation and a special element e G, called

More information

CS154. Turing Machines. Turing Machine. Turing Machines versus DFAs FINITE STATE CONTROL AI N P U T INFINITE TAPE. read write move.

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

More information

Chapter 3. Cartesian Products and Relations. 3.1 Cartesian Products

Chapter 3. Cartesian Products and Relations. 3.1 Cartesian Products Chapter 3 Cartesian Products and Relations The material in this chapter is the first real encounter with abstraction. Relations are very general thing they are a special type of subset. After introducing

More information

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. 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

More information

Sample Induction Proofs

Sample Induction Proofs Math 3 Worksheet: Induction Proofs III, Sample Proofs A.J. Hildebrand Sample Induction Proofs Below are model solutions to some of the practice problems on the induction worksheets. The solutions given

More information

Learning Analysis by Reduction from Positive Data

Learning Analysis by Reduction from Positive Data Learning Analysis by Reduction from Positive Data František Mráz 1, Friedrich Otto 1, and Martin Plátek 2 1 Fachbereich Mathematik/Informatik, Universität Kassel 34109 Kassel, Germany {mraz,otto}@theory.informatik.uni-kassel.de

More information

Increasing Interaction and Support in the Formal Languages and Automata Theory Course

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 rodger@cs.duke.edu Jinghui Lim Stephen Reading ABSTRACT The introduction of educational

More information

Lecture I FINITE AUTOMATA

Lecture I FINITE AUTOMATA 1. Regular Sets and DFA Lecture I Page 1 Lecture I FINITE AUTOMATA Lecture 1: Honors Theory, Spring 02, Yap We introduce finite automata (deterministic and nondeterministic) and regular languages. Some

More information

Solutions to In-Class Problems Week 4, Mon.

Solutions to In-Class Problems Week 4, Mon. Massachusetts Institute of Technology 6.042J/18.062J, Fall 05: Mathematics for Computer Science September 26 Prof. Albert R. Meyer and Prof. Ronitt Rubinfeld revised September 26, 2005, 1050 minutes Solutions

More information

T-79.186 Reactive Systems: Introduction and Finite State Automata

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

More information

ω-automata Automata that accept (or reject) words of infinite length. Languages of infinite words appear:

ω-automata Automata that accept (or reject) words of infinite length. Languages of infinite words appear: ω-automata ω-automata Automata that accept (or reject) words of infinite length. Languages of infinite words appear: in verification, as encodings of non-terminating executions of a program. in arithmetic,

More information

NFAs with Tagged Transitions, their Conversion to Deterministic Automata and Application to Regular Expressions

NFAs with Tagged Transitions, their Conversion to Deterministic Automata and Application to Regular Expressions NFAs with Tagged Transitions, their Conversion to Deterministic Automata and Application to Regular Expressions Ville Laurikari Helsinki University of Technology Laboratory of Computer Science PL 9700,

More information

Practice with Proofs

Practice with Proofs Practice with Proofs October 6, 2014 Recall the following Definition 0.1. A function f is increasing if for every x, y in the domain of f, x < y = f(x) < f(y) 1. Prove that h(x) = x 3 is increasing, using

More information

Hint 1. Answer (b) first. Make the set as simple as possible and try to generalize the phenomena it exhibits. [Caution: the next hint is an answer to

Hint 1. Answer (b) first. Make the set as simple as possible and try to generalize the phenomena it exhibits. [Caution: the next hint is an answer to Problem. Consider the collection of all subsets A of the topological space X. The operations of osure A Ā and ementation A X A are functions from this collection to itself. (a) Show that starting with

More information

United States Naval Academy Electrical and Computer Engineering Department. EC262 Exam 1

United States Naval Academy Electrical and Computer Engineering Department. EC262 Exam 1 United States Naval Academy Electrical and Computer Engineering Department EC262 Exam 29 September 2. Do a page check now. You should have pages (cover & questions). 2. Read all problems in their entirety.

More information

Introduction to Finite Automata

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

More information

Math 312 Homework 1 Solutions

Math 312 Homework 1 Solutions Math 31 Homework 1 Solutions Last modified: July 15, 01 This homework is due on Thursday, July 1th, 01 at 1:10pm Please turn it in during class, or in my mailbox in the main math office (next to 4W1) Please

More information

Pushdown automata. Informatics 2A: Lecture 9. Alex Simpson. 3 October, 2014. School of Informatics University of Edinburgh als@inf.ed.ac.

Pushdown automata. Informatics 2A: Lecture 9. Alex Simpson. 3 October, 2014. School of Informatics University of Edinburgh als@inf.ed.ac. Pushdown automata Informatics 2A: Lecture 9 Alex Simpson School of Informatics University of Edinburgh als@inf.ed.ac.uk 3 October, 2014 1 / 17 Recap of lecture 8 Context-free languages are defined by context-free

More information

ÖVNINGSUPPGIFTER I SAMMANHANGSFRIA SPRÅK. 15 april 2003. Master Edition

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

More information

How To Compare A Markov Algorithm To A Turing Machine

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

More information

Turing Machines: An Introduction

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,

More information

6.080/6.089 GITCS Feb 12, 2008. Lecture 3

6.080/6.089 GITCS Feb 12, 2008. Lecture 3 6.8/6.89 GITCS Feb 2, 28 Lecturer: Scott Aaronson Lecture 3 Scribe: Adam Rogal Administrivia. Scribe notes The purpose of scribe notes is to transcribe our lectures. Although I have formal notes of my

More information

Today s Agenda. Automata and Logic. Quiz 4 Temporal Logic. Introduction Buchi Automata Linear Time Logic Summary

Today s Agenda. Automata and Logic. Quiz 4 Temporal Logic. Introduction Buchi Automata Linear Time Logic Summary Today s Agenda Quiz 4 Temporal Logic Formal Methods in Software Engineering 1 Automata and Logic Introduction Buchi Automata Linear Time Logic Summary Formal Methods in Software Engineering 2 1 Buchi Automata

More information

Modeling of Graph and Automaton in Database

Modeling of Graph and Automaton in Database 1, 2 Modeling of Graph and Automaton in Database Shoji Miyanaga 1, 2 Table scheme that relational database provides can model the structure of graph which consists of vertices and edges. Recent database

More information

Techniques algébriques en calcul quantique

Techniques algébriques en calcul quantique Techniques algébriques en calcul quantique E. Jeandel Laboratoire de l Informatique du Parallélisme LIP, ENS Lyon, CNRS, INRIA, UCB Lyon 8 Avril 25 E. Jeandel, LIP, ENS Lyon Techniques algébriques en calcul

More information

Regular Languages and Finite Automata

Regular Languages and Finite Automata Regular Languages and Finite Automata A C Norman, Lent Term 1996 Part IA 1 Introduction This course is short, but it is present in Part 1A because of the way it introduces links between many different

More information

On Recognizable Timed Languages FOSSACS 2004

On Recognizable Timed Languages FOSSACS 2004 On Recognizable Timed Languages Oded Maler VERIMAG Grenoble France Amir Pnueli NYU and Weizmann New York and Rehovot USA FOSSACS 2004 Nutrition Facts Classical (Untimed) Recognizability Timed Languages

More information

Lecture 16 : Relations and Functions DRAFT

Lecture 16 : Relations and Functions DRAFT CS/Math 240: Introduction to Discrete Mathematics 3/29/2011 Lecture 16 : Relations and Functions Instructor: Dieter van Melkebeek Scribe: Dalibor Zelený DRAFT In Lecture 3, we described a correspondence

More information

P. Jeyanthi and N. Angel Benseera

P. Jeyanthi and N. Angel Benseera Opuscula Math. 34, no. 1 (014), 115 1 http://dx.doi.org/10.7494/opmath.014.34.1.115 Opuscula Mathematica A TOTALLY MAGIC CORDIAL LABELING OF ONE-POINT UNION OF n COPIES OF A GRAPH P. Jeyanthi and N. Angel

More information

2110711 THEORY of COMPUTATION

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

More information

On line construction of suffix trees 1

On line construction of suffix trees 1 (To appear in ALGORITHMICA) On line construction of suffix trees 1 Esko Ukkonen Department of Computer Science, University of Helsinki, P. O. Box 26 (Teollisuuskatu 23), FIN 00014 University of Helsinki,

More information

Composability of Infinite-State Activity Automata*

Composability of Infinite-State Activity Automata* Composability of Infinite-State Activity Automata* Zhe Dang 1, Oscar H. Ibarra 2, Jianwen Su 2 1 Washington State University, Pullman 2 University of California, Santa Barbara Presented by Prof. Hsu-Chun

More information

CH3 Boolean Algebra (cont d)

CH3 Boolean Algebra (cont d) CH3 Boolean Algebra (cont d) Lecturer: 吳 安 宇 Date:2005/10/7 ACCESS IC LAB v Today, you ll know: Introduction 1. Guidelines for multiplying out/factoring expressions 2. Exclusive-OR and Equivalence operations

More information

Models for Quantitative Distributed Systems and Multi-Valued Logics

Models for Quantitative Distributed Systems and Multi-Valued Logics Universität Leipzig Institut für Informatik Models for Quantitative Distributed Systems and Multi-Valued Logics Master Thesis Leipzig, September 2010 Author Supervisor B.Sc. Martin Huschenbett Master Student

More information

E3: PROBABILITY AND STATISTICS lecture notes

E3: PROBABILITY AND STATISTICS lecture notes E3: PROBABILITY AND STATISTICS lecture notes 2 Contents 1 PROBABILITY THEORY 7 1.1 Experiments and random events............................ 7 1.2 Certain event. Impossible event............................

More information

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 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

More information

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 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

More information

3515ICT Theory of Computation Turing Machines

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

More information

Genetic programming with regular expressions

Genetic programming with regular expressions Genetic programming with regular expressions Børge Svingen Chief Technology Officer, Open AdExchange bsvingen@openadex.com 2009-03-23 Pattern discovery Pattern discovery: Recognizing patterns that characterize

More information

Omega Automata: Minimization and Learning 1

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

More information

The Optimum One-Pass Strategy for Juliet

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

More information

Section 1.1 Real Numbers

Section 1.1 Real Numbers . Natural numbers (N):. Integer numbers (Z): Section. Real Numbers Types of Real Numbers,, 3, 4,,... 0, ±, ±, ±3, ±4, ±,... REMARK: Any natural number is an integer number, but not any integer number is

More information

Cardinality. The set of all finite strings over the alphabet of lowercase letters is countable. The set of real numbers R is an uncountable set.

Cardinality. The set of all finite strings over the alphabet of lowercase letters is countable. The set of real numbers R is an uncountable set. Section 2.5 Cardinality (another) Definition: The cardinality of a set A is equal to the cardinality of a set B, denoted A = B, if and only if there is a bijection from A to B. If there is an injection

More information

Math Workshop October 2010 Fractions and Repeating Decimals

Math Workshop October 2010 Fractions and Repeating Decimals Math Workshop October 2010 Fractions and Repeating Decimals This evening we will investigate the patterns that arise when converting fractions to decimals. As an example of what we will be looking at,

More information

Math 319 Problem Set #3 Solution 21 February 2002

Math 319 Problem Set #3 Solution 21 February 2002 Math 319 Problem Set #3 Solution 21 February 2002 1. ( 2.1, problem 15) Find integers a 1, a 2, a 3, a 4, a 5 such that every integer x satisfies at least one of the congruences x a 1 (mod 2), x a 2 (mod

More information

A First Investigation of Sturmian Trees

A First Investigation of Sturmian Trees A First Investigation of Sturmian Trees Jean Berstel 2, Luc Boasson 1 Olivier Carton 1, Isabelle Fagnot 2 1 LIAFA, CNRS Université Paris 7 2 IGM, CNRS Université de Marne-la-Vallée Atelier de Combinatoire,

More information

CPS 140 - Mathematical Foundations of CS Dr. S. Rodger Section: Properties of Context-Free Languages èhandoutè Section 3.5 Which of the following languages are CFL? æ L=fa n b n c j j 0 énçjg æ L=fa n

More information

L 2 : x = s + 1, y = s, z = 4s + 4. 3. Suppose that C has coordinates (x, y, z). Then from the vector equality AC = BD, one has

L 2 : x = s + 1, y = s, z = 4s + 4. 3. Suppose that C has coordinates (x, y, z). Then from the vector equality AC = BD, one has The line L through the points A and B is parallel to the vector AB = 3, 2, and has parametric equations x = 3t + 2, y = 2t +, z = t Therefore, the intersection point of the line with the plane should satisfy:

More information

SOLUTIONS TO EXERCISES FOR. MATHEMATICS 205A Part 3. Spaces with special properties

SOLUTIONS TO EXERCISES FOR. MATHEMATICS 205A Part 3. Spaces with special properties SOLUTIONS TO EXERCISES FOR MATHEMATICS 205A Part 3 Fall 2008 III. Spaces with special properties III.1 : Compact spaces I Problems from Munkres, 26, pp. 170 172 3. Show that a finite union of compact subspaces

More information

Lexical analysis FORMAL LANGUAGES AND COMPILERS. Floriano Scioscia. Formal Languages and Compilers A.Y. 2015/2016

Lexical analysis FORMAL LANGUAGES AND COMPILERS. Floriano Scioscia. Formal Languages and Compilers A.Y. 2015/2016 Master s Degree Course in Computer Engineering Formal Languages FORMAL LANGUAGES AND COMPILERS Lexical analysis Floriano Scioscia 1 Introductive terminological distinction Lexical string or lexeme = meaningful

More information

Lecture 24: Saccheri Quadrilaterals

Lecture 24: Saccheri Quadrilaterals Lecture 24: Saccheri Quadrilaterals 24.1 Saccheri Quadrilaterals Definition In a protractor geometry, we call a quadrilateral ABCD a Saccheri quadrilateral, denoted S ABCD, if A and D are right angles

More information

CONTENTS 1. Peter Kahn. Spring 2007

CONTENTS 1. Peter Kahn. Spring 2007 CONTENTS 1 MATH 304: CONSTRUCTING THE REAL NUMBERS Peter Kahn Spring 2007 Contents 2 The Integers 1 2.1 The basic construction.......................... 1 2.2 Adding integers..............................

More information

a 11 x 1 + a 12 x 2 + + a 1n x n = b 1 a 21 x 1 + a 22 x 2 + + a 2n x n = b 2.

a 11 x 1 + a 12 x 2 + + a 1n x n = b 1 a 21 x 1 + a 22 x 2 + + a 2n x n = b 2. Chapter 1 LINEAR EQUATIONS 1.1 Introduction to linear equations A linear equation in n unknowns x 1, x,, x n is an equation of the form a 1 x 1 + a x + + a n x n = b, where a 1, a,..., a n, b are given

More information

So let us begin our quest to find the holy grail of real analysis.

So let us begin our quest to find the holy grail of real analysis. 1 Section 5.2 The Complete Ordered Field: Purpose of Section We present an axiomatic description of the real numbers as a complete ordered field. The axioms which describe the arithmetic of the real numbers

More information

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 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

More information

Index support for regular expression search. Alexander Korotkov PGCon 2012, Ottawa

Index support for regular expression search. Alexander Korotkov PGCon 2012, Ottawa Index support for regular expression search Alexander Korotkov PGCon 2012, Ottawa Introduction What is regular expressions? Regular expressions are: powerful tool for text processing based on formal language

More information

Two Way F finite Automata and Three Ways to Solve Them

Two Way F finite Automata and Three Ways to Solve Them An Exponential Gap between LasVegas and Deterministic Sweeping Finite Automata Christos Kapoutsis, Richard Královič, and Tobias Mömke Department of Computer Science, ETH Zürich Abstract. A two-way finite

More information

Computability Theory

Computability Theory CSC 438F/2404F Notes (S. Cook and T. Pitassi) Fall, 2014 Computability Theory This section is partly inspired by the material in A Course in Mathematical Logic by Bell and Machover, Chap 6, sections 1-10.

More information

MACM 101 Discrete Mathematics I

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.

More information

1 Approximating Set Cover

1 Approximating Set Cover CS 05: Algorithms (Grad) Feb 2-24, 2005 Approximating Set Cover. Definition An Instance (X, F ) of the set-covering problem consists of a finite set X and a family F of subset of X, such that every elemennt

More information

Projective Geometry - Part 2

Projective Geometry - Part 2 Projective Geometry - Part 2 Alexander Remorov alexanderrem@gmail.com Review Four collinear points A, B, C, D form a harmonic bundle (A, C; B, D) when CA : DA CB DB = 1. A pencil P (A, B, C, D) is the

More information

Similarity and Diagonalization. Similar Matrices

Similarity and Diagonalization. Similar Matrices MATH022 Linear Algebra Brief lecture notes 48 Similarity and Diagonalization Similar Matrices Let A and B be n n matrices. We say that A is similar to B if there is an invertible n n matrix P such that

More information

INCIDENCE-BETWEENNESS GEOMETRY

INCIDENCE-BETWEENNESS GEOMETRY INCIDENCE-BETWEENNESS GEOMETRY MATH 410, CSUSM. SPRING 2008. PROFESSOR AITKEN This document covers the geometry that can be developed with just the axioms related to incidence and betweenness. The full

More information

How To Factorize Of Finite Abelian Groups By A Cyclic Subset Of A Finite Group

How To Factorize Of Finite Abelian Groups By A Cyclic Subset Of A Finite Group Comment.Math.Univ.Carolin. 51,1(2010) 1 8 1 A Hajós type result on factoring finite abelian groups by subsets II Keresztély Corrádi, Sándor Szabó Abstract. It is proved that if a finite abelian group is

More information