CS158 Section B Exam 1 Key

Size: px
Start display at page:

Download "CS158 Section B Exam 1 Key"

Transcription

1 CS158 Section B Exam 1 Key Name This is a closed-book exam. The only items not supplied that you are allowed to use are writing implements. You have 50 minutes to complete this exam. The total amount of points you can score is 61, but note that you only need 50 to score 100%. Good luck! 1. [8 pts] Use mathematical induction to prove that if n people stand in a line, where n is a positive integer, and if the first person in the line is a woman and the last person in line is a man, then somewhere in the line there is a woman directly in front of a man.

2 2. [8 pts] Show that the following program segment terminates with factorial = n! when n is a positive integer. i = 1 factorial = 1 while i < n do i = i + 1 factorial = factorial * i end while 3. [12 pts] Verify the correctness of the following program segment with the assertions shown. {y = 3} x = 2 z = x + y {z = 5} if y > 0 then z = z + 1 else z = 0 end if {z = 6}

3 4. [8 pts] Prove the following statement (try proof by contraposition): If 3n + 2 is odd, then n is odd. 5. [14 pts] Show whether from the hypotheses: It is not sunny this afternoon and it is colder than yesterday, We will go swimming only if it is sunny this afternoon, If we do not go swimming, then we will take a canoe trip, and If we take a canoe trip, then we will be home by sunset we can conclude we will be home by sunset or not.

4 6. [11 pts] Using predicate logic, prove that the following argument is valid. Use the predicate symbols shown. Argument: Some plants are flowers. All flowers smell sweet. Therefore, some plants smells sweet. P (x), F (x), S(x) Answer 1. Proof 1. Base case: n = 2, the first person is a woman and the last person is a man. 2. I.H.: Assume that when n = k(k 2), in the line there is a woman directly in front of a man. 3. Show that when n = k + 1, in the line there is a woman directly in front of a man. From k to k + 1 people, there is 1 new person added in the line. There are three cases. (a) the new person is before the woman that is directly in front of a man. In this case, the woman is still directly in front of the man. (b) the new person is after the man that is directly after a woman. In this case, the woman is still directly in front of the man. (c) the new person is added between the woman and the man who are next to each other. In this case, if the new person is a woman, she is directly in front of the man; if the new person is a man, he is directly after the woman. In both cases, there is still a woman directly in front of a man. Therefore, for any positive integer n (n 2), there is always a woman directly in front of a man in the line. 2. Proof: Let guess Q: factorial = i!. Prove by induction that Q is a loop invariant. 1. Base case: Before the first iteration of the loop, factorial = 1 and i = 1. Q( 0 ) holds. 2. I.H.: Assume that Q( k ): factorial k = i k! holds. 3. Show that Q( k+1 ): factorial k+1 = i k+1! holds. From the assignment statements in the loop, we have: i k+1 = i k + 1 and factorial k+1 = factorial k i k+1. Therefore, factorial k+1 = i k! i k+1 = i k! (i k + 1) = (i k + 1)! = i k+1! Therefore, Q is a loop invariant. At loop termination, factorial = i! and i = n. Hence, factorial = n!. 3. Proof: We can split the program segment into two halves. The first half contains the first two assignment statements and the second half contains the conditional statement. We first prove the first half. We work backwards from the postcondition using the assignment rule twice:

5 {2 + y = 5} or {y = 3} x = 2 {x + y = 5} z = x + y {z = 5} This agrees with the precondition given. Next we prove the second half using the conditional rule. We need to show: (1) {z = 5 y > 0} z = z + 1 {z = 6} and (2) {z = 5 y 0} z = 0 {z = 6} The first one is true by assignment rule. y > 0 adds nothing new to this conditional statement. The second one is true because the precondition is always false. Therefore, the whole program segment is correct. 4. Proof: Using proof by contraposition, let s prove: n is even 3n + 2 is even. if n is even, we can write n = 2k where k is an integer. Then 3n + 2 = 3(2k) + 2 = 6k + 2 = 2(3k + 1) where 3k + 1 is an integer. Therefore, 3n + 2 is an even integer. Hence, if 3n + 2 is odd, then n is odd. 5. S: it is sunny this afternoon C: it is colder than yesterday W: we will go swimming T: we ill take a canoe trip H: we will be home by sunset Argument in propositional wff is: (S C) (W S) (W T ) (T H) H Proof: 1. S C hyp 2. W S hyp 3. W T hyp 4. T H hyp 5. S 1 sim 6. W 2,5 mt 7. T 3,6 mp 8. H 4,7 mp Therefore, we can conclude that we will be home by sunset. 6. The argument is: ( x)[p (x) F (x)] ( x)[p (x) S(x)] A proof sequence is: 1. ( x)[p (x) F (x)] hyp 2. ( y)[f (y) S(y)] hyp 3. P (a) F (a) 1 ei 4. F (a) S(a) 2 ui 5. F (a) 3 sim 6. S(a) 4,5 mp 7. P (a) 3 sim 8. P (a) S(a) 6,7 con 9. ( x)[p (x) S(x)] 8 eg

University of Illinois at Chicago Department of Computer Science. Final Examination. CS 151 Mathematical Foundations of Computer Science Fall 2012

University of Illinois at Chicago Department of Computer Science. Final Examination. CS 151 Mathematical Foundations of Computer Science Fall 2012 University of Illinois at Chicago Department of Computer Science Final Examination CS 151 Mathematical Foundations of Computer Science Fall 2012 Thursday, October 18, 2012 Name: Email: Print your name

More information

Inference rule for Induction

Inference rule for Induction Inference rule for Induction Let P( ) be a predicate with domain the positive integers BASE CASE INDUCTIVE STEP INDUCTIVE Step: Usually a direct proof Assume P(x) for arbitrary x (Inductive Hypothesis),

More information

Practice Final. Read all the problems first before start working on any of them, so you can manage your time wisely

Practice Final. Read all the problems first before start working on any of them, so you can manage your time wisely PRINT your name here: Practice Final Print your name immediately on the cover page, as well as each page of the exam, in the space provided. Each time you are caught working on a page without your name

More information

Mathematical Induction

Mathematical Induction Mathematical Induction Victor Adamchik Fall of 2005 Lecture 3 (out of three) Plan 1. Recursive Definitions 2. Recursively Defined Sets 3. Program Correctness Recursive Definitions Sometimes it is easier

More information

Practice Problems: All Computer Science majors are people. Some computer science majors are logical thinkers. Some people are logical thinkers.

Practice Problems: All Computer Science majors are people. Some computer science majors are logical thinkers. Some people are logical thinkers. CSE 240, Fall, 2013 Homework 2 Due, Tuesday September 17. Can turn in class, at the beginning of class, or earlier in the mailbox labelled Pless in Bryan Hall, room 509c. Practice Problems: 1. Consider

More information

An Annotated Language

An Annotated Language Hoare Logic An Annotated Language State and Semantics Expressions are interpreted as functions from states to the corresponding domain of interpretation Operators have the obvious interpretation Free of

More information

Outline. Introduction. 2 Proof of Correctness. 3 Final Notes. Precondition P 1 : Inputs include

Outline. Introduction. 2 Proof of Correctness. 3 Final Notes. Precondition P 1 : Inputs include Outline Computer Science 331 Correctness of Algorithms Mike Jacobson Department of Computer Science University of Calgary Lectures #2-4 1 What is a? Applications 2 Recursive Algorithms 3 Final Notes Additional

More information

CS 3512, Spring Instructor: Doug Dunham. Textbook: James L. Hein, Discrete Structures, Logic, and Computability, 3rd Ed. Jones and Barlett, 2010

CS 3512, Spring Instructor: Doug Dunham. Textbook: James L. Hein, Discrete Structures, Logic, and Computability, 3rd Ed. Jones and Barlett, 2010 CS 3512, Spring 2011 Instructor: Doug Dunham Textbook: James L. Hein, Discrete Structures, Logic, and Computability, 3rd Ed. Jones and Barlett, 2010 Prerequisites: Calc I, CS2511 Rough course outline:

More information

CMPSCI 250: Introduction to Computation. Lecture #22: Graphs, Paths, and Trees David Mix Barrington 12 March 2014

CMPSCI 250: Introduction to Computation. Lecture #22: Graphs, Paths, and Trees David Mix Barrington 12 March 2014 CMPSCI 250: Introduction to Computation Lecture #22: Graphs, Paths, and Trees David Mix Barrington 12 March 2014 Graphs, Paths, and Trees Graph Definitions Paths and the Path Predicate Cycles, Directed

More information

Foundations, Reasoning About Algorithms, and Design By Contract CMPSC 122

Foundations, Reasoning About Algorithms, and Design By Contract CMPSC 122 Foundations, Reasoning About Algorithms, and Design By Contract CMPSC 122 I. Logic 101 In logic, a statement or proposition is a sentence that can either be true or false. A predicate is a sentence in

More information

1KOd17RMoURxjn2 CSE 20 DISCRETE MATH Fall

1KOd17RMoURxjn2 CSE 20 DISCRETE MATH Fall CSE 20 https://goo.gl/forms/1o 1KOd17RMoURxjn2 DISCRETE MATH Fall 2017 http://cseweb.ucsd.edu/classes/fa17/cse20-ab/ Today's learning goals Explain the steps in a proof by mathematical and/or structural

More information

Lecture 5 - Axiomatic semantics

Lecture 5 - Axiomatic semantics Program Verification March 2014 Lecture 5 - Axiomatic semantics Lecturer: Noam Rinetzky Scribes by: Nir Hemed 1.1 Axiomatic semantics The development of the theory is contributed to Robert Floyd, C.A.R

More information

Warmup Problem. Translate the following sentence from English into Propositional Logic. I want to eat ice cream even though I am on a diet.

Warmup Problem. Translate the following sentence from English into Propositional Logic. I want to eat ice cream even though I am on a diet. Warmup Problem Translate the following sentence from English into Propositional Logic I want to eat ice cream even though I am on a diet 1/25 CS 245: Logic and Computation Carmen Bruni Lecture 2 Based

More information

(a) (4 pts) Prove that if a and b are rational, then ab is rational. Since a and b are rational they can be written as the ratio of integers a 1

(a) (4 pts) Prove that if a and b are rational, then ab is rational. Since a and b are rational they can be written as the ratio of integers a 1 CS 70 Discrete Mathematics for CS Fall 2000 Wagner MT1 Sol Solutions to Midterm 1 1. (16 pts.) Theorems and proofs (a) (4 pts) Prove that if a and b are rational, then ab is rational. Since a and b are

More information

Part II. Hoare Logic and Program Verification. Why specify programs? Specification and Verification. Code Verification. Why verify programs?

Part II. Hoare Logic and Program Verification. Why specify programs? Specification and Verification. Code Verification. Why verify programs? Part II. Hoare Logic and Program Verification Part II. Hoare Logic and Program Verification Dilian Gurov Props: Models: Specs: Method: Tool: safety of data manipulation source code logic assertions Hoare

More information

Trees and Inductive Definitions

Trees and Inductive Definitions Lecture 19 CS 1813 Discrete Mathematics Trees and Inductive Definitions 1 Tree What Is a Tree? a diagram or graph that branches usually from a simple stem without forming loops or polygons Merriam-Webster

More information

Hoare Logic: Proving Programs Correct

Hoare Logic: Proving Programs Correct Hoare Logic: Proving Programs Correct 17-654/17-765 Analysis of Software Artifacts Jonathan Aldrich Reading: C.A.R. Hoare, An Axiomatic Basis for Computer Programming Some presentation ideas from a lecture

More information

Fundamental mathematical techniques reviewed: Mathematical induction Recursion. Typically taught in courses such as Calculus and Discrete Mathematics.

Fundamental mathematical techniques reviewed: Mathematical induction Recursion. Typically taught in courses such as Calculus and Discrete Mathematics. Fundamental mathematical techniques reviewed: Mathematical induction Recursion Typically taught in courses such as Calculus and Discrete Mathematics. Techniques introduced: Divide-and-Conquer Algorithms

More information

THE LOGIC OF QUANTIFIED STATEMENTS

THE LOGIC OF QUANTIFIED STATEMENTS CHAPTER 3 THE LOGIC OF QUANTIFIED STATEMENTS Copyright Cengage Learning. All rights reserved. SECTION 3.4 Arguments with Quantified Statements Copyright Cengage Learning. All rights reserved. Arguments

More information

Reasoning about programs

Reasoning about programs Reasoning about programs Last time Coming up This Thursday, Nov 30: 4 th in-class exercise sign up for group on moodle bring laptop to class Final projects: final project presentations: Tue Dec 12, in

More information

Last time. Reasoning about programs. Coming up. Project Final Presentations. This Thursday, Nov 30: 4 th in-class exercise

Last time. Reasoning about programs. Coming up. Project Final Presentations. This Thursday, Nov 30: 4 th in-class exercise Last time Reasoning about programs Coming up This Thursday, Nov 30: 4 th in-class exercise sign up for group on moodle bring laptop to class Final projects: final project presentations: Tue Dec 12, in

More information

Discrete Mathematics and Probability Theory Spring 2016 Rao and Walrand Midterm 1

Discrete Mathematics and Probability Theory Spring 2016 Rao and Walrand Midterm 1 CS 70 Discrete Mathematics and Probability Theory Spring 2016 Rao and Walrand Midterm 1 PRINT Your Name:, (last) SIGN Your Name: (first) PRINT Your Student ID: CIRCLE your exam room: 1 Pimentel 141 Mccone

More information

Backward Reasoning: Rule for Assignment. Backward Reasoning: Rule for Sequence. Simple Example. Hoare Logic, continued Reasoning About Loops

Backward Reasoning: Rule for Assignment. Backward Reasoning: Rule for Sequence. Simple Example. Hoare Logic, continued Reasoning About Loops Backward Reasoning: Rule for Assignment Hoare Logic, continued Reasoning About Loops { wp( x=expression,q) x = expression; { Q Rule: the weakest precondition wp( x=expression,q) is Q with all occurrences

More information

ELEMENTARY NUMBER THEORY AND METHODS OF PROOF

ELEMENTARY NUMBER THEORY AND METHODS OF PROOF CHAPTER 4 ELEMENTARY NUMBER THEORY AND METHODS OF PROOF Copyright Cengage Learning. All rights reserved. SECTION 4.6 Indirect Argument: Contradiction and Contraposition Copyright Cengage Learning. All

More information

Arguing for program correctness and writing correct programs

Arguing for program correctness and writing correct programs Arguing for program correctness and writing correct programs Saying things about states, programs Program state s1: x=4, y=-1.5, A={ me, you, he Assertions about program states x=3 False in s1 (y=x) x>=0

More information

CS 161 Computer Security

CS 161 Computer Security Wagner Spring 2014 CS 161 Computer Security 1/27 Reasoning About Code Often functions make certain assumptions about their arguments, and it is the caller s responsibility to make sure those assumptions

More information

Homework 1. Due Date: Wednesday 11/26/07 - at the beginning of the lecture

Homework 1. Due Date: Wednesday 11/26/07 - at the beginning of the lecture Homework 1 Due Date: Wednesday 11/26/07 - at the beginning of the lecture Problems marked with a [*] are a littlebit harder and count as extra credit. Note 1. For any of the given problems make sure that

More information

SEQUENCES, MATHEMATICAL INDUCTION, AND RECURSION

SEQUENCES, MATHEMATICAL INDUCTION, AND RECURSION CHAPTER 5 SEQUENCES, MATHEMATICAL INDUCTION, AND RECURSION Alessandro Artale UniBZ - http://www.inf.unibz.it/ artale/ SECTION 5.5 Application: Correctness of Algorithms Copyright Cengage Learning. All

More information

You have 90 minutes to work on this exam. It is a "closed-book/closed-notes" test.

You have 90 minutes to work on this exam. It is a closed-book/closed-notes test. NAME (as it appears on your UF ID): (Please PRINT) UF Student ID#: ----------------------------- CEN 5035 - Software Engineering --------------------------- Exam 2 Fall 2012 You have 90 minutes to work

More information

12/30/2013 S. NALINI,AP/CSE

12/30/2013 S. NALINI,AP/CSE 12/30/2013 S. NALINI,AP/CSE 1 UNIT I ITERATIVE AND RECURSIVE ALGORITHMS Iterative Algorithms: Measures of Progress and Loop Invariants-Paradigm Shift: Sequence of Actions versus Sequence of Assertions-

More information

Discrete Mathematics and Probability Theory Fall 2016 Seshia and Walrand Midterm 1

Discrete Mathematics and Probability Theory Fall 2016 Seshia and Walrand Midterm 1 CS 70 Discrete Mathematics and Probability Theory Fall 2016 Seshia and Walrand Midterm 1 PRINT Your Name:, (last) READ AND SIGN The Honor Code: As a member of the UC Berkeley community, I act with honesty,

More information

Chapter 1.3 Quantifiers, Predicates, and Validity. Reading: 1.3 Next Class: 1.4. Motivation

Chapter 1.3 Quantifiers, Predicates, and Validity. Reading: 1.3 Next Class: 1.4. Motivation Chapter 1.3 Quantifiers, Predicates, and Validity Reading: 1.3 Next Class: 1.4 1 Motivation Propositional logic allows to translate and prove certain arguments from natural language If John s wallet was

More information

Automated Reasoning. Natural Deduction in First-Order Logic

Automated Reasoning. Natural Deduction in First-Order Logic Automated Reasoning Natural Deduction in First-Order Logic Jacques Fleuriot Automated Reasoning Lecture 4, page 1 Problem Consider the following problem: Every person has a heart. George Bush is a person.

More information

Searching Algorithms/Time Analysis

Searching Algorithms/Time Analysis Searching Algorithms/Time Analysis CSE21 Fall 2017, Day 8 Oct 16, 2017 https://sites.google.com/a/eng.ucsd.edu/cse21-fall-2017-miles-jones/ (MinSort) loop invariant induction Loop invariant: After the

More information

Midterm I Exam Principles of Imperative Computation Frank Pfenning. February 17, 2011

Midterm I Exam Principles of Imperative Computation Frank Pfenning. February 17, 2011 Midterm I Exam 15-122 Principles of Imperative Computation Frank Pfenning February 17, 2011 Name: Sample Solution Andrew ID: fp Section: Instructions This exam is closed-book with one sheet of notes permitted.

More information

Lecture 1 Contracts. 1 A Mysterious Program : Principles of Imperative Computation (Spring 2018) Frank Pfenning

Lecture 1 Contracts. 1 A Mysterious Program : Principles of Imperative Computation (Spring 2018) Frank Pfenning Lecture 1 Contracts 15-122: Principles of Imperative Computation (Spring 2018) Frank Pfenning In these notes we review contracts, which we use to collectively denote function contracts, loop invariants,

More information

Complexity, Induction, and Recurrence Relations. CSE 373 Help Session 4/7/2016

Complexity, Induction, and Recurrence Relations. CSE 373 Help Session 4/7/2016 Complexity, Induction, and Recurrence Relations CSE 373 Help Session 4/7/2016 Big-O Definition Definition: g(n) is in O( f(n) ) if there exist positive constants c and n0 such that g(n) c f(n) for all

More information

CSE Discrete Structures

CSE Discrete Structures CSE 2315 - Discrete Structures Lecture 5: Predicate Logic- Fall 2010 1 Motivation The use of predicates, variables, and quantifiers allows to represent a large number of arguments and expressions in formal

More information

Notes slides from before lecture. CSE 21, Winter 2017, Section A00. Lecture 9 Notes. Class URL:

Notes slides from before lecture. CSE 21, Winter 2017, Section A00. Lecture 9 Notes. Class URL: Notes slides from before lecture CSE 21, Winter 2017, Section A00 Lecture 9 Notes Class URL: http://vlsicad.ucsd.edu/courses/cse21-w17/ Notes slides from before lecture Notes February 8 (1) HW4 is due

More information

Lecture 15 : Review DRAFT

Lecture 15 : Review DRAFT CS/Math 240: Introduction to Discrete Mathematics 3/10/2011 Lecture 15 : Review Instructor: Dieter van Melkebeek Scribe: Dalibor Zelený DRAFT Today slectureservesasareviewofthematerialthatwillappearonyoursecondmidtermexam.

More information

Assertions & Verification & Example Loop Invariants Example Exam Questions

Assertions & Verification & Example Loop Invariants Example Exam Questions 2014 November 27 1. Assertions & Verification & Example Loop Invariants Example Exam Questions 2. A B C Give a general template for refining an operation into a sequence and state what questions a designer

More information

Semantics. There is no single widely acceptable notation or formalism for describing semantics Operational Semantics

Semantics. There is no single widely acceptable notation or formalism for describing semantics Operational Semantics There is no single widely acceptable notation or formalism for describing semantics Operational Describe the meaning of a program by executing its statements on a machine, either simulated or actual. The

More information

10/9/17. Using recursion to define objects. CS 220: Discrete Structures and their Applications

10/9/17. Using recursion to define objects. CS 220: Discrete Structures and their Applications Using recursion to define objects CS 220: Discrete Structures and their Applications Recursive objects and 6.9 6.10 in zybooks We can use recursion to define functions: The factorial function can be defined

More information

Review: Hoare Logic Rules

Review: Hoare Logic Rules Review: Hoare Logic Rules wp(x := E, P) = [E/x] P wp(s;t, Q) = wp(s, wp(t, Q)) wp(if B then S else T, Q) = B wp(s,q) && B wp(t,q) Proving loops correct First consider partial correctness The loop may not

More information

Binary Search to find item in sorted array

Binary Search to find item in sorted array Binary Search to find item in sorted array January 15, 2008 QUESTION: Suppose we are given a sorted list A[1..n] (as an array), of n real numbers: A[1] A[2] A[n]. Given a real number x, decide whether

More information

More Complicated Recursion CMPSC 122

More Complicated Recursion CMPSC 122 More Complicated Recursion CMPSC 122 Now that we've gotten a taste of recursion, we'll look at several more examples of recursion that are special in their own way. I. Example with More Involved Arithmetic

More information

Induction and Semantics in Dafny

Induction and Semantics in Dafny 15-414 Lecture 11 1 Instructor: Matt Fredrikson Induction and Semantics in Dafny TA: Ryan Wagner Encoding the syntax of Imp Recall the abstract syntax of Imp: a AExp ::= n Z x Var a 1 + a 2 b BExp ::=

More information

CIS 500 Software Foundations. Midterm I. (Standard and advanced versions together) October 1, 2013 Answer key

CIS 500 Software Foundations. Midterm I. (Standard and advanced versions together) October 1, 2013 Answer key CIS 500 Software Foundations Midterm I (Standard and advanced versions together) October 1, 2013 Answer key 1. (12 points) Write the type of each of the following Coq expressions, or write ill-typed if

More information

Assertions & Verification Example Exam Questions

Assertions & Verification Example Exam Questions 2009 November 23 Assertions & Verification Example Exam Questions 1. 2. A B C Give a general template for refining an operation into a sequence and state what questions a designer must answer to verify

More information

Algorithms. Notations/pseudo-codes vs programs Algorithms for simple problems Analysis of algorithms

Algorithms. Notations/pseudo-codes vs programs Algorithms for simple problems Analysis of algorithms Algorithms Notations/pseudo-codes vs programs Algorithms for simple problems Analysis of algorithms Is it correct? Loop invariants Is it good? Efficiency Is there a better algorithm? Lower bounds * DISC

More information

Chapter 3. Set Theory. 3.1 What is a Set?

Chapter 3. Set Theory. 3.1 What is a Set? Chapter 3 Set Theory 3.1 What is a Set? A set is a well-defined collection of objects called elements or members of the set. Here, well-defined means accurately and unambiguously stated or described. Any

More information

Program Verification (Rosen, Sections 5.5)

Program Verification (Rosen, Sections 5.5) Program Verification (Rosen, Sections 5.5) TOPICS Program Correctness Preconditions & Postconditions Program Verification Assignments Composition Conditionals Loops Proofs about Programs Why study logic?

More information

Theorem 3.1 (Berge) A matching M in G is maximum if and only if there is no M- augmenting path.

Theorem 3.1 (Berge) A matching M in G is maximum if and only if there is no M- augmenting path. 3 Matchings Hall s Theorem Matching: A matching in G is a subset M E(G) so that no edge in M is a loop, and no two edges in M are incident with a common vertex. A matching M is maximal if there is no matching

More information

Lecture 1 Contracts : Principles of Imperative Computation (Fall 2018) Frank Pfenning

Lecture 1 Contracts : Principles of Imperative Computation (Fall 2018) Frank Pfenning Lecture 1 Contracts 15-122: Principles of Imperative Computation (Fall 2018) Frank Pfenning In these notes we review contracts, which we use to collectively denote function contracts, loop invariants,

More information

Symbolic Execution and Proof of Properties

Symbolic Execution and Proof of Properties Chapter 7 Symbolic Execution and Proof of Properties Symbolic execution builds predicates that characterize the conditions under which execution paths can be taken and the effect of the execution on program

More information

Recall our recursive multiply algorithm:

Recall our recursive multiply algorithm: Recall our recursive multiply algorithm: PRECONDITION: x and y are both binary bit arrays of length n, n a power of 2. POSTCONDITION: Returns a binary bit array equal to the product of x and y. REC MULTIPLY

More information

NAME (as it appears on your UF ID): (Please PRINT) CEN Software Engineering

NAME (as it appears on your UF ID): (Please PRINT) CEN Software Engineering NAME (as it appears on your UF ID): (Please PRINT) UF Student ID#: ------------------------------- CEN 5035 - Software Engineering ----------------------------- Exam 2 Fall 2010 You have 90 minutes to

More information

Hardware versus software

Hardware versus software Logic 1 Hardware versus software 2 In hardware such as chip design or architecture, designs are usually proven to be correct using proof tools In software, a program is very rarely proved correct Why?

More information

Introduction to Axiomatic Semantics

Introduction to Axiomatic Semantics Introduction to Axiomatic Semantics Meeting 10, CSCI 5535, Spring 2009 Announcements Homework 3 due tonight Homework 2 is graded 13 (mean), 14 (median), out of 21 total, but Graduate class: final project

More information

Lecture Notes: Hoare Logic

Lecture Notes: Hoare Logic Lecture Notes: Hoare Logic 17-654/17-754: Analysis of Software Artifacts Jonathan Aldrich (jonathan.aldrich@cs.cmu.edu) Lecture 3 1 Hoare Logic The goal of Hoare logic is to provide a formal system for

More information

CITS2211 Discrete Structures Logic

CITS2211 Discrete Structures Logic CITS2211 Discrete Structures Logic Unit coordinator: Rachel Cardell-Oliver August 6, 2017 Highlights All men are mortal, Socrates is a man, therefore Socrates is mortal. Reading Chapter 3: Logical Formulas

More information

Lecture Notes on Linear Search

Lecture Notes on Linear Search Lecture Notes on Linear Search 15-122: Principles of Imperative Computation Frank Pfenning Lecture 5 January 28, 2014 1 Introduction One of the fundamental and recurring problems in computer science is

More information

CS 220: Discrete Structures and their Applications. Recursive objects and structural induction in zybooks

CS 220: Discrete Structures and their Applications. Recursive objects and structural induction in zybooks CS 220: Discrete Structures and their Applications Recursive objects and structural induction 6.9 6.10 in zybooks Using recursion to define objects We can use recursion to define functions: The factorial

More information

Propositional Calculus: Boolean Functions and Expressions. CS 270: Mathematical Foundations of Computer Science Jeremy Johnson

Propositional Calculus: Boolean Functions and Expressions. CS 270: Mathematical Foundations of Computer Science Jeremy Johnson Propositional Calculus: Boolean Functions and Expressions CS 270: Mathematical Foundations of Computer Science Jeremy Johnson Propositional Calculus Objective: To provide students with the concepts and

More information

Math 454 Final Exam, Fall 2005

Math 454 Final Exam, Fall 2005 c IIT Dept. Applied Mathematics, December 12, 2005 1 PRINT Last name: Signature: First name: Student ID: Math 454 Final Exam, Fall 2005 I. Examples, Counterexamples and short answer. (6 2 ea.) Do not give

More information

How invariants help writing loops Author: Sander Kooijmans Document version: 1.0

How invariants help writing loops Author: Sander Kooijmans Document version: 1.0 How invariants help writing loops Author: Sander Kooijmans Document version: 1.0 Why this document? Did you ever feel frustrated because of a nasty bug in your code? Did you spend hours looking at the

More information

6.001 Notes: Section 4.1

6.001 Notes: Section 4.1 6.001 Notes: Section 4.1 Slide 4.1.1 In this lecture, we are going to take a careful look at the kinds of procedures we can build. We will first go back to look very carefully at the substitution model,

More information

Structure and Interpretation of Computer Programs

Structure and Interpretation of Computer Programs CS 61A Fall 2013 Structure and Interpretation of Computer Programs Final Solutions INSTRUCTIONS You have 3 hours to complete the exam. The exam is closed book, closed notes, closed computer, closed calculator,

More information

On the Adequacy of Program Dependence Graphs for Representing Programs

On the Adequacy of Program Dependence Graphs for Representing Programs - 1 - On the Adequacy of Program Dependence Graphs for Representing Programs Susan Horwitz, Jan Prins, and Thomas Reps University of Wisconsin Madison Abstract Program dependence graphs were introduced

More information

15-122: Principles of Imperative Computation (Section G)

15-122: Principles of Imperative Computation (Section G) 15-122: Principles of Imperative Computation (Section G) Document 2 Solutions 0. Contracts This lecture was mainly about contracts and ensuring correctness of code. Josh Zimmerman There are 4 types of

More information

Notes for Recitation 8

Notes for Recitation 8 6.04/8.06J Mathematics for Computer Science October 5, 00 Tom Leighton and Marten van Dijk Notes for Recitation 8 Build-up error Recall a graph is connected iff there is a path between every pair of its

More information

(l) Represent each of the sets A, B and C using bit strings. Then, use bit string representation and bitwise logical operations to find

(l) Represent each of the sets A, B and C using bit strings. Then, use bit string representation and bitwise logical operations to find Fall 2004 Ahmed Elgammal CS 205: Sample Final Exam December 6th, 2004 1. [10 points] Let A = {1, 3, 5, 7, 9}, B = {4, 5, 6, 7, 8}, C = {2, 4, 6, 8, 10}, D = {1, 2, 3} and let the universal set be U = {1,

More information

Introduction to Sets and Logic (MATH 1190)

Introduction to Sets and Logic (MATH 1190) Introduction to Sets and Logic () Instructor: Email: shenlili@yorku.ca Department of Mathematics and Statistics York University Dec 4, 2014 Outline 1 2 3 4 Definition A relation R from a set A to a set

More information

Softwaretechnik. Program verification. Albert-Ludwigs-Universität Freiburg. June 28, Softwaretechnik June 28, / 24

Softwaretechnik. Program verification. Albert-Ludwigs-Universität Freiburg. June 28, Softwaretechnik June 28, / 24 Softwaretechnik Program verification Albert-Ludwigs-Universität Freiburg June 28, 2012 Softwaretechnik June 28, 2012 1 / 24 Road Map Program verification Automatic program verification Programs with loops

More information

Geometry Lesson 2.1 Conditional Statements. September 4, 2007

Geometry Lesson 2.1 Conditional Statements. September 4, 2007 Geometry Lesson 2.1 Conditional Statements September 4, 2007 Objectives Students will be able to: Define: conditional statement, hypothesis, conclusion, converse, inverse, contrapositive, equivalent statements

More information

Exam I Principles of Imperative Computation, Summer 2011 William Lovas. May 27, 2011

Exam I Principles of Imperative Computation, Summer 2011 William Lovas. May 27, 2011 Exam I 15-122 Principles of Imperative Computation, Summer 2011 William Lovas May 27, 2011 Name: Sample Solution Andrew ID: wlovas Instructions This exam is closed-book with one sheet of notes permitted.

More information

Statistics Case Study 2000 M. J. Clancy and M. C. Linn

Statistics Case Study 2000 M. J. Clancy and M. C. Linn Statistics Case Study 2000 M. J. Clancy and M. C. Linn Problem Write and test functions to compute the following statistics for a nonempty list of numeric values: The mean, or average value, is computed

More information

Section 2.2: Introduction to the Logic of Quantified Statements

Section 2.2: Introduction to the Logic of Quantified Statements Section 2.2: Introduction to the Logic of Quantified Statements In this section, we shall continue to examine some of the fundamentals of predicate calculus. Specifically, we shall look at the negations

More information

1 / 43. Today. Finish Euclid. Bijection/CRT/Isomorphism. Fermat s Little Theorem. Review for Midterm.

1 / 43. Today. Finish Euclid. Bijection/CRT/Isomorphism. Fermat s Little Theorem. Review for Midterm. 1 / 43 Today Finish Euclid. Bijection/CRT/Isomorphism. Fermat s Little Theorem. Review for Midterm. 2 / 43 Finding an inverse? We showed how to efficiently tell if there is an inverse. Extend euclid to

More information

SEQUENCES, MATHEMATICAL INDUCTION, AND RECURSION

SEQUENCES, MATHEMATICAL INDUCTION, AND RECURSION CHAPTER 5 SEQUENCES, MATHEMATICAL INDUCTION, AND RECURSION Copyright Cengage Learning. All rights reserved. SECTION 5.5 Application: Correctness of Algorithms Copyright Cengage Learning. All rights reserved.

More information

CPSC 121 Some Sample Questions for the Final Exam Tuesday, April 15, 2014, 8:30AM

CPSC 121 Some Sample Questions for the Final Exam Tuesday, April 15, 2014, 8:30AM CPSC 121 Some Sample Questions for the Final Exam Tuesday, April 15, 2014, 8:30AM Name: Student ID: Signature: Section (circle one): George Steve Your signature acknowledges your understanding of and agreement

More information

Outline. Computer Science 331. Three Classical Algorithms. The Sorting Problem. Classical Sorting Algorithms. Mike Jacobson. Description Analysis

Outline. Computer Science 331. Three Classical Algorithms. The Sorting Problem. Classical Sorting Algorithms. Mike Jacobson. Description Analysis Outline Computer Science 331 Classical Sorting Algorithms Mike Jacobson Department of Computer Science University of Calgary Lecture #22 1 Introduction 2 3 4 5 Comparisons Mike Jacobson (University of

More information

Programming Languages Third Edition

Programming Languages Third Edition Programming Languages Third Edition Chapter 12 Formal Semantics Objectives Become familiar with a sample small language for the purpose of semantic specification Understand operational semantics Understand

More information

1. Chapter 1, # 1: Prove that for all sets A, B, C, the formula

1. Chapter 1, # 1: Prove that for all sets A, B, C, the formula Homework 1 MTH 4590 Spring 2018 1. Chapter 1, # 1: Prove that for all sets,, C, the formula ( C) = ( ) ( C) is true. Proof : It suffices to show that ( C) ( ) ( C) and ( ) ( C) ( C). ssume that x ( C),

More information

Recursive Definitions Structural Induction Recursive Algorithms

Recursive Definitions Structural Induction Recursive Algorithms Chapter 4 1 4.3-4.4 Recursive Definitions Structural Induction Recursive Algorithms 2 Section 4.1 3 Principle of Mathematical Induction Principle of Mathematical Induction: To prove that P(n) is true for

More information

Solutions to the Second Midterm Exam

Solutions to the Second Midterm Exam CS/Math 240: Intro to Discrete Math 3/27/2011 Instructor: Dieter van Melkebeek Solutions to the Second Midterm Exam Problem 1 This question deals with the following implementation of binary search. Function

More information

AXIOMS FOR THE INTEGERS

AXIOMS FOR THE INTEGERS AXIOMS FOR THE INTEGERS BRIAN OSSERMAN We describe the set of axioms for the integers which we will use in the class. The axioms are almost the same as what is presented in Appendix A of the textbook,

More information

CSCI.6962/4962 Software Verification Fundamental Proof Methods in Computer Science (Arkoudas and Musser) Chapter 12

CSCI.6962/4962 Software Verification Fundamental Proof Methods in Computer Science (Arkoudas and Musser) Chapter 12 CSCI.6962/4962 Software Verification Fundamental Proof Methods in Computer Science (Arkoudas and Musser) Chapter 12 p. 1/27 CSCI.6962/4962 Software Verification Fundamental Proof Methods in Computer Science

More information

Basic Verification Strategy

Basic Verification Strategy ormal Verification Basic Verification Strategy compare behavior to intent System Model of system behavior intent Verifier results Intent Usually, originates with requirements, refined through design and

More information

Data Abstraction & Problem Solving with C++: Walls and Mirrors 6th Edition Carrano, Henry Test Bank

Data Abstraction & Problem Solving with C++: Walls and Mirrors 6th Edition Carrano, Henry Test Bank Data Abstraction & Problem Solving with C++: Walls and Mirrors 6th Edition Carrano, Henry Test Bank Download link: https://solutionsmanualbank.com/download/test-bank-for-data-abstractionproblem-solving-with-c-walls-and-mirrors-6-e-carrano-henry/

More information

CS 512, Spring 2017: Take-Home End-of-Term Examination

CS 512, Spring 2017: Take-Home End-of-Term Examination CS 512, Spring 2017: Take-Home End-of-Term Examination Out: Tuesday, 9 May 2017, 12:00 noon Due: Wednesday, 10 May 2017, by 11:59 am Turn in your solutions electronically, as a single PDF file, by placing

More information

Cornell University 12 Oct Solutions. (a) [9 pts] For each of the 3 functions below, pick an appropriate type for it from the list below.

Cornell University 12 Oct Solutions. (a) [9 pts] For each of the 3 functions below, pick an appropriate type for it from the list below. Cornell University 12 Oct 2006 Solutions 1. Types, Polymorphism [14 pts] (parts a b) (a) [9 pts] For each of the 3 functions below, pick an appropriate type for it from the list below. i. fun f x y = (y,

More information

CS 2113 Midterm Exam, November 6, 2007

CS 2113 Midterm Exam, November 6, 2007 CS 2113 Midterm Exam, November 6, 2007 Problem 1 [20 pts] When the following VBA program is executed, what will be displayed in the message box? Option Explicit Sub problem1() Dim m As Integer, n As Integer

More information

Discrete Mathematics and Probability Theory Fall 2015 Rao Midterm 1

Discrete Mathematics and Probability Theory Fall 2015 Rao Midterm 1 CS 70 Discrete Mathematics and Probability Theory Fall 2015 Rao Midterm 1 PRINT Your Name:, (last) SIGN Your Name: (first) PRINT Your Student ID: CIRCLE your exam room: 2050 VLSB A1 Hearst Annex 120 Latimer

More information

Preliminary Examination I Computer Science 312, Cornell University 6 March 2003

Preliminary Examination I Computer Science 312, Cornell University 6 March 2003 Preliminary Examination I Computer Science 312, Cornell University 6 March 2003 Before starting the exam, write your name on this page and your netid on both this page and the next page. There are 5 problems

More information

Today. Finish Euclid. Bijection/CRT/Isomorphism. Review for Midterm.

Today. Finish Euclid. Bijection/CRT/Isomorphism. Review for Midterm. Today Finish Euclid. Bijection/CRT/Isomorphism. Review for Midterm. Finding an inverse? We showed how to efficiently tell if there is an inverse. Extend euclid to find inverse. Euclid s GCD algorithm.

More information

Lecture 3: Recursion; Structural Induction

Lecture 3: Recursion; Structural Induction 15-150 Lecture 3: Recursion; Structural Induction Lecture by Dan Licata January 24, 2012 Today, we are going to talk about one of the most important ideas in functional programming, structural recursion

More information

Test Bank Ver. 5.0: Data Abstraction and Problem Solving with C++: Walls and Mirrors, 5 th edition, Frank M. Carrano

Test Bank Ver. 5.0: Data Abstraction and Problem Solving with C++: Walls and Mirrors, 5 th edition, Frank M. Carrano Chapter 2 Recursion: The Mirrors Multiple Choice Questions 1. In a recursive solution, the terminates the recursive processing. a) local environment b) pivot item c) base case d) recurrence relation 2.

More information

CSE 331 Summer 2016 Final Exam. Please wait to turn the page until everyone is told to begin.

CSE 331 Summer 2016 Final Exam. Please wait to turn the page until everyone is told to begin. Name The exam is closed book, closed notes, and closed electronics. Please wait to turn the page until everyone is told to begin. Score / 54 1. / 12 2. / 12 3. / 10 4. / 10 5. / 10 Bonus: 1. / 6 2. / 4

More information

MULTIPLE CHOICE. Choose the one alternative that best completes the statement or answers the question.

MULTIPLE CHOICE. Choose the one alternative that best completes the statement or answers the question. Practice Exam I Mat-107 Spring A 2011 Name MULTIPLE CHOICE. Choose the one alternative that best completes the statement or answers the question. List the elements in the set. 1) {x x is a whole number

More information