Deterministic Program The While Program

Size: px
Start display at page:

Download "Deterministic Program The While Program"

Transcription

1 Deterministic Program The While Program Shangping Ren Department of Computer Science Illinois Institute of Technology February 24, 2014 Shangping Ren Deterministic Program The While Program February 24, / 25

2 Outline 1 Verification Total Correctness: Proof System TW 2 Developing Programs 3 Proof Outlines Shangping Ren Deterministic Program The While Program February 24, / 25

3 Verification Total Correctness: Proof System TW Proof System (TW) Axiom 1: Skip : the same as in PW Axiom 2: Assignment : the same as in PW Rule 3: Composition : the same as in PW Rule 4: Conditional : the same as in PW Rule 5: Loop : different from PW (given as Rule 7) Rule 6: Consequence : the same as in PW Shangping Ren Deterministic Program The While Program February 24, / 25

4 Verification Total Correctness: Proof System TW Rule 7 : Total Correctness for Loops {p B} S {p}, {p B t = z} S {t < z}, p t 0 {p} while B do S od {p B} Where t is an integer expression and z is an integer variable that does not occur in p, B, t, or S. Why are we talking about variables that don t exist? Shangping Ren Deterministic Program The While Program February 24, / 25

5 Verification Total Correctness: Proof System TW Example 2, Revisited Verify the Total Correctness DIV quo := 0; rem := x; while rem >= y do rem := rem - y; quo := quo + 1 od Verify under total correctness: {x 0 y > 0}DIV {quo y + rem = x 0 rem < y} Shangping Ren Deterministic Program The While Program February 24, / 25

6 Verification Total Correctness: Proof System TW Example 2, Revisited Verify the Total Correctness DIV quo := 0; rem := x; while rem >= y do rem := rem - y; quo := quo + 1 od inv: p quo y + rem = x rem 0 y > 0; B: B rem y; bd t: t rem; z: an integer variable that does not occur in p, B, t, and DIV Shangping Ren Deterministic Program The While Program February 24, / 25

7 Verification Total Correctness: Proof System TW Example 2, Revisited Verify the Total Correctness inv: p quo y + rem = x rem 0 y > 0; B: B rem y; bd t: t rem; z: an integer variable that does not occur in p, B, t, and DIV 1 Invariant is established: {x 0 y > 0}quo := 0; rem := x{p} 2 Loop body does not change the loop invariant {p B}rem := rem y; quo := quo + 1{p} 3 Bounded integer decreases after each iteration {p B rem = z}rem := rem y; quo := quo + 1{rem < z} 4 Invariant implies bounded integer is non-negative: p t 0 5 When it terminates, the postcondition holds p B p rem < y Shangping Ren Deterministic Program The While Program February 24, / 25

8 The Five Equations Developing Programs To do this we need to develop five equations. 1 {r}t {p} 2 {p B}S{p} 3 {p B t = z} S {t < z} 4 p t 0 5 p B q Shangping Ren Deterministic Program The While Program February 24, / 25

9 Extended Example Developing Programs Given an array A, populate array B with the running sum of A. E.g., if A = {1, 1, 2, 3, 4}, then B = {1, 2, 4, 7, 11}. Shangping Ren Deterministic Program The While Program February 24, / 25

10 Proof Outlines for Loops Partial Correctness {p B}S {p} {inv : p}while B do {p B}S {p} od {p B} Total Correctness {p B} S {p}, {p B t = z} S {t < z}, p t 0 {inv : p}{bd : t}while B do {p B}S {p} od {p B} Shangping Ren Deterministic Program The While Program February 24, / 25

11 The Proof Outline for Total Correctness We have a program of the form satisfying under total correctness {r} T ; {inv : p} {bd : t} while B do {p B} S {p} od {p B} {q} R T ; while B do S od {r}r{q} Shangping Ren Deterministic Program The While Program February 24, / 25

12 The Proof Outline for Total Correctness {r} T ; {inv : p} {bd : t} while B do {p B} S {p} od {p B} {q} 21 {x y y > 0} 22 quo := 0; rem := x; 23 {inv : p}{bd : rem} 24 while rem y do 25 {p rem y} 26 rem := rem - y; quo := quo {p} 28 od 29 {p rem < y} 30 {quo y + rem = x 0 rem < y} where p quo y + rem = x rem 0 y > 0 Still need to verify the other two promises in Rule 7. Shangping Ren Deterministic Program The While Program February 24, / 25

13 Decomposition for the Total Correctness Proof Proof under total correctness: {p}s{q} We can separate the proof process into two steps: 1 Establish a partial correctness formula {p}s{q} 2 Proof termination with simpler total correctness formula {p}s{true } Axiom A1: Decomposition p {p}s{q}, t {p}s{true } {p}s{q} Shangping Ren Deterministic Program The While Program February 24, / 25

14 Auxiliary Axims and Rules Axiom A2: Invariance and where free(p) change(s) = φ Rule A3: Disjunction Rule A4: Conjunction {p}s{p} {r}s{q} {p r}s{p q} {p}s{q}, {r}s{q} {p r}s{q} {p 1 }S{q 1 }, {p 2 }S{q 2 } {p 1 p 2 }S{q 1 q 2 } Shangping Ren Deterministic Program The While Program February 24, / 25

15 Auxiliary Axims and Rules Axiom A5: Substitution where u var(s) t change(s). {p}s{q} {p[u := t]}s{q[u := t]} Axiom A6: -Introduction {p}s{q} { x : p]}s{q} where x does not occur in S or in free(q). Shangping Ren Deterministic Program The While Program February 24, / 25

16 Strengthening Precondition and Weakening Postconditions Given a valid triple {p}s{q}, how can we modify p and q and maintain validity? if p 0 p 1 then p 0 is stronger than p 1 and p 1 is weaker than p 0. Example: x = 0 is stronger than x = 0 x = 1 is stronger than x 0 Consequence Rule: we can strength a precondition and weaken a postcondition. What is the strongest predicate? What is the weakest one? Shangping Ren Deterministic Program The While Program February 24, / 25

17 Strengthening Precondition and Weakening Postconditions Given a valid triple {p}s{q}, how can we modify p and q and maintain validity? if p 0 p 1 then p 0 is stronger than p 1 and p 1 is weaker than p 0. Example: x = 0 is stronger than x = 0 x = 1 is stronger than x 0 Consequence Rule: we can strength a precondition and weaken a postcondition. What is the strongest predicate? What is the weakest one? Shangping Ren Deterministic Program The While Program February 24, / 25

18 Strengthening Precondition and Weakening Postconditions Given a valid triple {p}s{q}, how can we modify p and q and maintain validity? if p 0 p 1 then p 0 is stronger than p 1 and p 1 is weaker than p 0. Example: x = 0 is stronger than x = 0 x = 1 is stronger than x 0 Consequence Rule: we can strength a precondition and weaken a postcondition. What is the strongest predicate? What is the weakest one? Shangping Ren Deterministic Program The While Program February 24, / 25

19 Strengthening Precondition and Weakening Postconditions Given a valid triple {p}s{q}, how can we modify p and q and maintain validity? if p 0 p 1 then p 0 is stronger than p 1 and p 1 is weaker than p 0. Example: x = 0 is stronger than x = 0 x = 1 is stronger than x 0 Consequence Rule: we can strength a precondition and weaken a postcondition. What is the strongest predicate? What is the weakest one? Shangping Ren Deterministic Program The While Program February 24, / 25

20 What about Weakening Preconditions and Strengthening Postconditions? if p p 0 and {p}s{q} is valid, can we conclude {p 0 }S{q} is valid? Consider {x = 0}y := x x{y = x}, what about {x = 0 x = 1}y := x x{y = x} or {x 0}y := x x{y = x} if q 0 q and {p}s{q} is valid, can we conclude {p}s{q 0 } is valid? Shangping Ren Deterministic Program The While Program February 24, / 25

21 Definitions about wlp and wp Definition: let S be a while program and Φ a set of proper states, Weakest Liberal Precondition wlp of S with respect to Φ: wlp(s, Φ) = {σ M[[S]](σ) Φ} Weakest Precondition wp of S with respect to Φ: wp(s, Φ) = {σ M tot [[S]](σ) Φ} Shangping Ren Deterministic Program The While Program February 24, / 25

22 Definitions about wlp and wp Definition: let S be a while program and Φ a set of proper states, Weakest Liberal Precondition wlp of S with respect to Φ: wlp(s, Φ) = {σ M[[S]](σ) Φ} Weakest Precondition wp of S with respect to Φ: wp(s, Φ) = {σ M tot [[S]](σ) Φ} Shangping Ren Deterministic Program The While Program February 24, / 25

23 Theorem about wlp and wp Remember the notation of [[p]]? Theorem: let S be a while program and q an assertion. Then the following holds: 1 There is an assertion p defining wlp(s, [[q]]), i.e., with [[p]] = wlp(s, [[q]]) 2 There is an assertion p defining wp(s, [[q]]), i.e., with [[p]] = wp(s, [[q]]). We also write wlp(s, [[q]]) as wlp(s, q) and wp(s, [[q]]) as wp(s, q) Shangping Ren Deterministic Program The While Program February 24, / 25

24 Weakest Liberal Precondition The following statements hold for all while programs and assertions: 1 skip: wlp(skip, q) q, 2 assignment: wlp(u := t, q) q[u := t], 3 sequence: wlp(s 1 ; S 2, q) wlp(s 1, wlp(s 2, q)), 4 conditional: wlp(if B then S 1 else S 2 fi, q) (B wlp(s 1, q) ( B wlp(s 2, q)), 5 S while B do S 1 od : wlp(s, q) B wlp(s 1, wlp(s, q)), 6 S while B do S 1 od : wlp(s, q) B q 7 {p}s{q}: = {p}s{q}iff p wlp(s, q) Shangping Ren Deterministic Program The While Program February 24, / 25

25 wlp(s, q) as Loop Invariant Previous slides (5) S while B do S 1 od : wlp(s, q) B wlp(s 1, wlp(s, q)), and (7) {p}s{q}: = {p}s{q}iff p wlp(s, q) We have = {wlp(s, q) B}S 1 {wlp(s, q)}, i.e., wlp(s, q) is a loop invariant of S. Shangping Ren Deterministic Program The While Program February 24, / 25

26 Weakest Precondition The following statements hold for all while programs and assertions: 1 skip: wp(skip, q) q, 2 assignment: wp(u := t, q) q[u := t], 3 sequence: wp(s 1 ; S 2, q) wp(s 1, wp(s 2, q)), 4 conditional: wp(if B then S 1 else S 2 fi, q) (B wp(s 1, q) ( B wp(s 2, q)), 5 S while B do S 1 od : wp(s, q) B wp(s 1, wp(s, q)), 6 S while B do S 1 od : wp(s, q) B q 7 {p}s{q}: = tot {p}s{q}iff p wp(s, q) Shangping Ren Deterministic Program The While Program February 24, / 25

27 Strongest Postcondition For given p and S, there exists a strongest postcondition q such that {p}s{q} is valid, i.e., For partial correctness, {p}s{q} iff sp(p, S) q. For total correctness, {p}s{q} iff sp(p, S) q and S terminates on all states of p Shangping Ren Deterministic Program The While Program February 24, / 25

28 Strongest Postcondition For given p and S, there exists a strongest postcondition q such that {p}s{q} is valid, i.e., For partial correctness, {p}s{q} iff sp(p, S) q. For total correctness, {p}s{q} iff sp(p, S) q and S terminates on all states of p Shangping Ren Deterministic Program The While Program February 24, / 25

29 Strongest Postcondition For given p and S, there exists a strongest postcondition q such that {p}s{q} is valid, i.e., For partial correctness, {p}s{q} iff sp(p, S) q. For total correctness, {p}s{q} iff sp(p, S) q and S terminates on all states of p Shangping Ren Deterministic Program The While Program February 24, / 25

30 Strongest Postconditions for Loop-Free Programs sp(p, skip ) p sp(p, u := v) p[u := u 0 ] u = (v[u := u 0 ]) sp(p, S 1 ; S 2 ) sp(sp(p, S 1 ), S 2 ) sp(p, if B then S 1 else S 2 fi ) sp(p B, S 1 ) sp(p B, S 2 ) Shangping Ren Deterministic Program The While Program February 24, / 25

31 Strongest Postcondition Examples sp(y 0, x := y) y 0[x := z] x = (y[x := z]) y 0 x = y Therefore, we have {y 0}x := y{y 0 x = y}, and the y 0 x = y is the strongest postcondition for the given precondition and the assignment statement. As y 0 x = y x 0, apply consequence rule to {y 0}x := y{y 0 x = y}, we have {y 0}x := y{x 0}. The weakest precondition of given post condition x 0 and program x := y is nevertheless y 0, i.e., wp(x := y, x 0) y 0. Shangping Ren Deterministic Program The While Program February 24, / 25

Floyd-Hoare Style Program Verification

Floyd-Hoare Style Program Verification Floyd-Hoare Style Program Verification Deepak D Souza Department of Computer Science and Automation Indian Institute of Science, Bangalore. 9 Feb 2017 Outline of this talk 1 Overview 2 Hoare Triples 3

More information

Strength; Weakest Preconditions

Strength; Weakest Preconditions 12/14: solved Strength; Weakest Preconditions CS 536: Science of Programming, Spring 2018 A. Why To combine correctness triples, we need to weaken and strengthen conditions. A weakest precondition is the

More information

Axiomatic Semantics. Lecture 9 CS 565 2/12/08

Axiomatic Semantics. Lecture 9 CS 565 2/12/08 Axiomatic Semantics Lecture 9 CS 565 2/12/08 Axiomatic Semantics Operational semantics describes the meaning of programs in terms of the execution steps taken by an abstract machine Denotational semantics

More information

Hoare Calculus and Predicate Transformers

Hoare Calculus and Predicate Transformers Hoare Calculus and Predicate Transformers Wolfgang Schreiner Wolfgang.Schreiner@risc.uni-linz.ac.at Research Institute for Symbolic Computation (RISC) Johannes Kepler University, Linz, Austria http://www.risc.uni-linz.ac.at

More information

Axiomatic Semantics. Hoare s Correctness Triplets Dijkstra s Predicate Transformers

Axiomatic Semantics. Hoare s Correctness Triplets Dijkstra s Predicate Transformers Axiomatic Semantics Hoare s Correctness Triplets Dijkstra s Predicate Transformers Goal of a program = IO Relation Problem Specification Properties satisfied by the input and expected of the output (usually

More information

Hoare Logic I. Introduction to Deductive Program Verification. Simple Imperative Programming Language. Hoare Logic. Meaning of Hoare Triples

Hoare Logic I. Introduction to Deductive Program Verification. Simple Imperative Programming Language. Hoare Logic. Meaning of Hoare Triples Hoare Logic I Introduction to Deductive Program Verification Işıl Dillig Program Spec Deductive verifier FOL formula Theorem prover valid contingent Example specs: safety (no crashes), absence of arithmetic

More information

Dynamic Semantics. Dynamic Semantics. Operational Semantics Axiomatic Semantics Denotational Semantic. Operational Semantics

Dynamic Semantics. Dynamic Semantics. Operational Semantics Axiomatic Semantics Denotational Semantic. Operational Semantics Dynamic Semantics Operational Semantics Denotational Semantic Dynamic Semantics Operational Semantics Operational Semantics Describe meaning by executing program on machine Machine can be actual or simulated

More information

Lecture Notes: Axiomatic Semantics and Hoare-style Verification

Lecture Notes: Axiomatic Semantics and Hoare-style Verification Lecture Notes: Axiomatic Semantics and Hoare-style Verification 17-355/17-665/17-819O: Program Analysis (Spring 2018) Claire Le Goues and Jonathan Aldrich clegoues@cs.cmu.edu, aldrich@cs.cmu.edu It has

More information

Programming Languages and Compilers (CS 421)

Programming Languages and Compilers (CS 421) Programming Languages and Compilers (CS 421) Sasa Misailovic 4110 SC, UIUC https://courses.engr.illinois.edu/cs421/fa2017/cs421a Based in part on slides by Mattox Beckman, as updated by Vikram Adve, Gul

More information

Loop Convergence. CS 536: Science of Programming, Fall 2018

Loop Convergence. CS 536: Science of Programming, Fall 2018 Solved Loop Convergence CS 536: Science of Programming, Fall 2018 A. Why Diverging programs aren t useful, so it s useful to know how to show that loops terminate. B. Objectives At the end of this lecture

More information

Classical Program Logics: Hoare Logic, Weakest Liberal Preconditions

Classical Program Logics: Hoare Logic, Weakest Liberal Preconditions Chapter 1 Classical Program Logics: Hoare Logic, Weakest Liberal Preconditions 1.1 The IMP Language IMP is a programming language with an extensible syntax that was developed in the late 1960s. We will

More information

Weakest Precondition Calculus

Weakest Precondition Calculus Weakest Precondition Calculus COMP2600 Formal Methods for Software Engineering Rajeev Goré Australian National University Semester 2, 2016 (Most lecture slides due to Ranald Clouston) COMP 2600 Weakest

More information

Predicate Transforms I

Predicate Transforms I Predicate Transforms I Software Testing and Verification Lecture Notes 19 Prepared by Stephen M. Thebaut, Ph.D. University of Florida Predicate Transforms I 1. Introduction: weakest pre-conditions (wp

More information

Program Analysis and Verification

Program Analysis and Verification Program Analysis and Verification 0368-4479 Noam Rinetzky Lecture 4: Axiomatic Semantics Slides credit: Tom Ball, Dawson Engler, Roman Manevich, Erik Poll, Mooly Sagiv, Jean Souyris, Eran Tromer, Avishai

More information

Proof Rules for Correctness Triples

Proof Rules for Correctness Triples Proof Rules for Correctness Triples CS 536: Science of Programming, Fall 2018 A. Why? We can t generally prove that correctness triples are valid using truth tables. We need proof axioms for atomic statements

More information

Hoare Logic: Part II

Hoare Logic: Part II Hoare Logic: Part II COMP2600 Formal Methods for Software Engineering Jinbo Huang Australian National University COMP 2600 Hoare Logic II 1 Factorial {n 0} fact := 1; i := n; while (i >0) do fact := fact

More information

Program verification. 18 October 2017

Program verification. 18 October 2017 Program verification 18 October 2017 Example revisited // assume(n>2); void partition(int a[], int n) { int pivot = a[0]; int lo = 1, hi = n-1; while (lo

More information

What happens to the value of the expression x + y every time we execute this loop? while x>0 do ( y := y+z ; x := x:= x z )

What happens to the value of the expression x + y every time we execute this loop? while x>0 do ( y := y+z ; x := x:= x z ) Starter Questions Feel free to discuss these with your neighbour: Consider two states s 1 and s 2 such that s 1, x := x + 1 s 2 If predicate P (x = y + 1) is true for s 2 then what does that tell us about

More information

The Assignment Axiom (Hoare)

The Assignment Axiom (Hoare) The Assignment Axiom (Hoare) Syntax: V := E Semantics: value of V in final state is value of E in initial state Example: X:=X+ (adds one to the value of the variable X) The Assignment Axiom {Q[E/V ]} V

More information

Axiomatic Semantics: Verification Conditions. Review of Soundness of Axiomatic Semantics. Questions? Announcements

Axiomatic Semantics: Verification Conditions. Review of Soundness of Axiomatic Semantics. Questions? Announcements Axiomatic Semantics: Verification Conditions Meeting 18, CSCI 5535, Spring 2010 Announcements Homework 6 is due tonight Today s forum: papers on automated testing using symbolic execution Anyone looking

More information

Program verification. Hoare triples. Assertional semantics (cont) Example: Semantics of assignment. Assertional semantics of a program

Program verification. Hoare triples. Assertional semantics (cont) Example: Semantics of assignment. Assertional semantics of a program Program verification Assertional semantics of a program Meaning of a program: relation between its inputs and outputs; specified by input assertions (pre-conditions) and output assertions (post-conditions)

More information

CSE 331 Winter 2018 Reasoning About Code I

CSE 331 Winter 2018 Reasoning About Code I CSE 331 Winter 2018 Reasoning About Code I Notes by Krysta Yousoufian Original lectures by Hal Perkins Additional contributions from Michael Ernst, David Notkin, and Dan Grossman These notes cover most

More information

Axiomatic Semantics: Verification Conditions. Review of Soundness and Completeness of Axiomatic Semantics. Announcements

Axiomatic Semantics: Verification Conditions. Review of Soundness and Completeness of Axiomatic Semantics. Announcements Axiomatic Semantics: Verification Conditions Meeting 12, CSCI 5535, Spring 2009 Announcements Homework 4 is due tonight Wed forum: papers on automated testing using symbolic execution 2 Questions? Review

More information

COP4020 Programming Languages. Introduction to Axiomatic Semantics Prof. Robert van Engelen

COP4020 Programming Languages. Introduction to Axiomatic Semantics Prof. Robert van Engelen COP4020 Programming Languages Introduction to Axiomatic Semantics Prof. Robert van Engelen Assertions and Preconditions Assertions are used by programmers to verify run-time execution An assertion is a

More information

Proof Calculus for Partial Correctness

Proof Calculus for Partial Correctness Proof Calculus for Partial Correctness Bow-Yaw Wang Institute of Information Science Academia Sinica, Taiwan September 7, 2016 Bow-Yaw Wang (Academia Sinica) Proof Calculus for Partial Correctness September

More information

Program verification using Hoare Logic¹

Program verification using Hoare Logic¹ Program verification using Hoare Logic¹ Automated Reasoning - Guest Lecture Petros Papapanagiotou Part 2 of 2 ¹Contains material from Mike Gordon s slides: Previously on Hoare Logic A simple while language

More information

What? Correctness? Bugs!

What? Correctness? Bugs! Program Correctness Literatuur Verification of Sequential and Concurrent Programs. Krzysztof R. Apt, Frank S. de Boer, Ernst-Rüdiger Olderog. Series: Texts in Computer Science. Springer. 3rd ed. 2nd Printing.

More information

Spring 2014 Program Analysis and Verification. Lecture 6: Axiomatic Semantics III. Roman Manevich Ben-Gurion University

Spring 2014 Program Analysis and Verification. Lecture 6: Axiomatic Semantics III. Roman Manevich Ben-Gurion University Spring 2014 Program Analysis and Verification Lecture 6: Axiomatic Semantics III Roman Manevich Ben-Gurion University Syllabus Semantics Static Analysis Abstract Interpretation fundamentals Analysis Techniques

More information

Verification Frameworks and Hoare Logic

Verification Frameworks and Hoare Logic CMSC 630 February 11, 2015 1 Verification Frameworks and Hoare Logic Sources K. Apt and E.-R. Olderog. Verification of Sequential and Concurrent Programs (Second Edition). Springer-Verlag, Berlin, 1997.

More information

COMP2111 Glossary. Kai Engelhardt. Contents. 1 Symbols. 1 Symbols 1. 2 Hoare Logic 3. 3 Refinement Calculus 5. rational numbers Q, real numbers R.

COMP2111 Glossary. Kai Engelhardt. Contents. 1 Symbols. 1 Symbols 1. 2 Hoare Logic 3. 3 Refinement Calculus 5. rational numbers Q, real numbers R. COMP2111 Glossary Kai Engelhardt Revision: 1.3, May 18, 2018 Contents 1 Symbols 1 2 Hoare Logic 3 3 Refinement Calculus 5 1 Symbols Booleans B = {false, true}, natural numbers N = {0, 1, 2,...}, integers

More information

Mid-Semester Quiz Second Semester, 2012

Mid-Semester Quiz Second Semester, 2012 THE AUSTRALIAN NATIONAL UNIVERSITY Mid-Semester Quiz Second Semester, 2012 COMP2600 (Formal Methods for Software Engineering) Writing Period: 1 hour duration Study Period: 10 minutes duration Permitted

More information

Hoare Logic (I): Axiomatic Semantics and Program Correctness

Hoare Logic (I): Axiomatic Semantics and Program Correctness Hoare Logic (I): Axiomatic Semantics and Program Correctness (Based on [Apt and Olderog 1991; Gries 1981; Hoare 1969; Kleymann 1999; Sethi 199]) Yih-Kuen Tsay Dept. of Information Management National Taiwan

More information

A Humble Introduction to DIJKSTRA S A A DISCIPLINE OF PROGRAMMING

A Humble Introduction to DIJKSTRA S A A DISCIPLINE OF PROGRAMMING A Humble Introduction to DIJKSTRA S A A DISCIPLINE OF PROGRAMMING Do-Hyung Kim School of Computer Science and Engineering Sungshin Women s s University CONTENTS Bibliographic Information and Organization

More information

Deductive Verification

Deductive Verification Deductive Verification Mooly Sagiv Slides from Zvonimir Rakamaric First-Order Logic A formal notation for mathematics, with expressions involving Propositional symbols Predicates Functions and constant

More information

Formal Reasoning CSE 331. Lecture 2 Formal Reasoning. Announcements. Formalization and Reasoning. Software Design and Implementation

Formal Reasoning CSE 331. Lecture 2 Formal Reasoning. Announcements. Formalization and Reasoning. Software Design and Implementation CSE 331 Software Design and Implementation Lecture 2 Formal Reasoning Announcements Homework 0 due Friday at 5 PM Heads up: no late days for this one! Homework 1 due Wednesday at 11 PM Using program logic

More information

Design of Distributed Systems Melinda Tóth, Zoltán Horváth

Design of Distributed Systems Melinda Tóth, Zoltán Horváth Design of Distributed Systems Melinda Tóth, Zoltán Horváth Design of Distributed Systems Melinda Tóth, Zoltán Horváth Publication date 2014 Copyright 2014 Melinda Tóth, Zoltán Horváth Supported by TÁMOP-412A/1-11/1-2011-0052

More information

Axiomatic semantics. Semantics and Application to Program Verification. Antoine Miné. École normale supérieure, Paris year

Axiomatic semantics. Semantics and Application to Program Verification. Antoine Miné. École normale supérieure, Paris year Axiomatic semantics Semantics and Application to Program Verification Antoine Miné École normale supérieure, Paris year 2015 2016 Course 6 18 March 2016 Course 6 Axiomatic semantics Antoine Miné p. 1 /

More information

THE AUSTRALIAN NATIONAL UNIVERSITY Second Semester COMP2600/COMP6260 (Formal Methods for Software Engineering)

THE AUSTRALIAN NATIONAL UNIVERSITY Second Semester COMP2600/COMP6260 (Formal Methods for Software Engineering) THE AUSTRALIAN NATIONAL UNIVERSITY Second Semester 2016 COMP2600/COMP6260 (Formal Methods for Software Engineering) Writing Period: 3 hours duration Study Period: 15 minutes duration Permitted Materials:

More information

Proofs of Correctness: Introduction to Axiomatic Verification

Proofs of Correctness: Introduction to Axiomatic Verification Proofs of Correctness: Introduction to Axiomatic Verification Introduction Weak correctness predicate Assignment statements Sequencing Selection statements Iteration 1 Introduction What is Axiomatic Verification?

More information

Hoare Logic: Reasoning About Imperative Programs

Hoare Logic: Reasoning About Imperative Programs Hoare Logic: Reasoning About Imperative Programs COMP1600 / COMP6260 Dirk Pattinson Australian National University Semester 2, 2017 Catch Up / Drop in Lab When Fridays, 15.00-17.00 Where N335, CSIT Building

More information

Program Analysis Part I : Sequential Programs

Program Analysis Part I : Sequential Programs Program Analysis Part I : Sequential Programs IN5170/IN9170 Models of concurrency Program Analysis, lecture 5 Fall 2018 26. 9. 2018 2 / 44 Program correctness Is my program correct? Central question for

More information

Axiomatic Semantics. Semantics of Programming Languages course. Joosep Rõõmusaare

Axiomatic Semantics. Semantics of Programming Languages course. Joosep Rõõmusaare Axiomatic Semantics Semantics of Programming Languages course Joosep Rõõmusaare 2014 Direct Proofs of Program Correctness Partial correctness properties are properties expressing that if a given program

More information

Spring 2015 Program Analysis and Verification. Lecture 6: Axiomatic Semantics III. Roman Manevich Ben-Gurion University

Spring 2015 Program Analysis and Verification. Lecture 6: Axiomatic Semantics III. Roman Manevich Ben-Gurion University Spring 2015 Program Analysis and Verification Lecture 6: Axiomatic Semantics III Roman Manevich Ben-Gurion University Tentative syllabus Semantics Static Analysis Abstract Interpretation fundamentals Analysis

More information

Introduction to Axiomatic Semantics

Introduction to Axiomatic Semantics #1 Introduction to Axiomatic Semantics #2 How s The Homework Going? Remember that you can t just define a meaning function in terms of itself you must use some fixed point machinery. #3 Observations A

More information

Soundness and Completeness of Axiomatic Semantics

Soundness and Completeness of Axiomatic Semantics #1 Soundness and Completeness of Axiomatic Semantics #2 One-Slide Summary A system of axiomatic semantics is sound if everything we can prove is also true: if ` { A } c { B } then ² { A } c { B } We prove

More information

Spring 2015 Program Analysis and Verification. Lecture 4: Axiomatic Semantics I. Roman Manevich Ben-Gurion University

Spring 2015 Program Analysis and Verification. Lecture 4: Axiomatic Semantics I. Roman Manevich Ben-Gurion University Spring 2015 Program Analysis and Verification Lecture 4: Axiomatic Semantics I Roman Manevich Ben-Gurion University Agenda Basic concepts of correctness Axiomatic semantics (pages 175-183) Hoare Logic

More information

Galois Connections. Roland Backhouse 3rd December, 2002

Galois Connections. Roland Backhouse 3rd December, 2002 1 Galois Connections Roland Backhouse 3rd December, 2002 Fusion 2 Many problems are expressed in the form evaluate generate where generate generates a (possibly infinite) candidate set of solutions, and

More information

CSE 331 Software Design & Implementation

CSE 331 Software Design & Implementation CSE 331 Software Design & Implementation Kevin Zatloukal Summer 2017 Lecture 2 Reasoning About Code With Logic (Based on slides by Mike Ernst, Dan Grossman, David Notkin, Hal Perkins, Zach Tatlock) Recall

More information

Verification and Validation

Verification and Validation 2010-2011 Cycle Ingénieur 2 ème année Département Informatique Verification and Validation Part IV : Proof-based Verification (III) Burkhart Wolff Département Informatique Université Paris-Sud / Orsay

More information

In this episode of The Verification Corner, Rustan Leino talks about Loop Invariants. He gives a brief summary of the theoretical foundations and

In this episode of The Verification Corner, Rustan Leino talks about Loop Invariants. He gives a brief summary of the theoretical foundations and In this episode of The Verification Corner, Rustan Leino talks about Loop Invariants. He gives a brief summary of the theoretical foundations and shows how a program can sometimes be systematically constructed

More information

5. Program Correctness: Mechanics

5. Program Correctness: Mechanics 5. Program Correctness: Mechanics Program A: LinearSearch with function specification @pre 0 l u < a @post rv i. l i u a[i] = e bool LinearSearch(int[] a, int l, int u, int e) { for @ (int i := l; i u;

More information

Softwaretechnik. Lecture 13: Design by Contract. Peter Thiemann University of Freiburg, Germany

Softwaretechnik. Lecture 13: Design by Contract. Peter Thiemann University of Freiburg, Germany Softwaretechnik Lecture 13: Design by Contract Peter Thiemann University of Freiburg, Germany 25.06.2012 Table of Contents Design by Contract Contracts for Procedural Programs Contracts for Object-Oriented

More information

Softwaretechnik. Lecture 13: Design by Contract. Peter Thiemann University of Freiburg, Germany

Softwaretechnik. Lecture 13: Design by Contract. Peter Thiemann University of Freiburg, Germany Softwaretechnik Lecture 13: Design by Contract Peter Thiemann University of Freiburg, Germany 25.06.2012 Table of Contents Design by Contract Contracts for Procedural Programs Contracts for Object-Oriented

More information

Spring 2016 Program Analysis and Verification. Lecture 3: Axiomatic Semantics I. Roman Manevich Ben-Gurion University

Spring 2016 Program Analysis and Verification. Lecture 3: Axiomatic Semantics I. Roman Manevich Ben-Gurion University Spring 2016 Program Analysis and Verification Lecture 3: Axiomatic Semantics I Roman Manevich Ben-Gurion University Warm-up exercises 1. Define program state: 2. Define structural semantics configurations:

More information

Hoare Logic and Model Checking

Hoare Logic and Model Checking Hoare Logic and Model Checking Kasper Svendsen University of Cambridge CST Part II 2016/17 Acknowledgement: slides heavily based on previous versions by Mike Gordon and Alan Mycroft Introduction In the

More information

CS156: The Calculus of Computation

CS156: The Calculus of Computation Page 1 of 61 CS156: The Calculus of Computation Zohar Manna Winter 2010 Chapter 5: Program Correctness: Mechanics Page 2 of 61 Program A: LinearSearch with function specification @pre 0 l u < a @post rv

More information

Verificación de Programas!

Verificación de Programas! Verificación de Programas! rafael ramirez rafael.ramirez@upf.edu 55.316 (Tanger) Porque verificar programas Debido a un error de programación, el cohete que llevaba al Mariner I, en viaje sin tripulación

More information

A Short Introduction to Hoare Logic

A Short Introduction to Hoare Logic A Short Introduction to Hoare Logic Supratik Chakraborty I.I.T. Bombay June 23, 2008 Supratik Chakraborty (I.I.T. Bombay) A Short Introduction to Hoare Logic June 23, 2008 1 / 34 Motivation Assertion checking

More information

Programming Languages

Programming Languages CSE 230: Winter 2008 Principles of Programming Languages Lecture 6: Axiomatic Semantics Deriv. Rules for Hoare Logic `{A} c {B} Rules for each language construct ` {A} c 1 {B} ` {B} c 2 {C} ` {A} skip

More information

Hoare Logic: Reasoning About Imperative Programs

Hoare Logic: Reasoning About Imperative Programs Hoare Logic: Reasoning About Imperative Programs COMP1600 / COMP6260 Dirk Pattinson Australian National University Semester 2, 2018 Programming Paradigms Functional. (Haskell, SML, OCaml,... ) main paradigm:

More information

THE AUSTRALIAN NATIONAL UNIVERSITY Second Semester COMP2600 (Formal Methods for Software Engineering)

THE AUSTRALIAN NATIONAL UNIVERSITY Second Semester COMP2600 (Formal Methods for Software Engineering) THE AUSTRALIAN NATIONAL UNIVERSITY Second Semester 2012 COMP2600 (Formal Methods for Software Engineering) Writing Period: 3 hours duration Study Period: 15 minutes duration Permitted Materials: One A4

More information

First Order Logic vs Propositional Logic CS477 Formal Software Dev Methods

First Order Logic vs Propositional Logic CS477 Formal Software Dev Methods First Order Logic vs Propositional Logic CS477 Formal Software Dev Methods Elsa L Gunter 2112 SC, UIUC egunter@illinois.edu http://courses.engr.illinois.edu/cs477 Slides based in part on previous lectures

More information

Last Time. Inference Rules

Last Time. Inference Rules Last Time When program S executes it switches to a different state We need to express assertions on the states of the program S before and after its execution We can do it using a Hoare triple written

More information

Declarative View of Imperative Programs

Declarative View of Imperative Programs Declarative View of Imperative Programs Hugh Gibbons, Trinity College, Dublin, Ireland. Abstract By giving a declarative meaning to an imperative program, the verification of the imperative program is

More information

Solutions to exercises for the Hoare logic (based on material written by Mark Staples)

Solutions to exercises for the Hoare logic (based on material written by Mark Staples) Solutions to exercises for the Hoare logic (based on material written by Mark Staples) Exercise 1 We are interested in termination, so that means we need to use the terminology of total correctness, i.e.

More information

Decision Procedures. Jochen Hoenicke. Software Engineering Albert-Ludwigs-University Freiburg. Winter Term 2016/17

Decision Procedures. Jochen Hoenicke. Software Engineering Albert-Ludwigs-University Freiburg. Winter Term 2016/17 Decision Procedures Jochen Hoenicke Software Engineering Albert-Ludwigs-University Freiburg Winter Term 2016/17 Jochen Hoenicke (Software Engineering) Decision Procedures Winter Term 2016/17 1 / 436 Program

More information

Software Engineering

Software Engineering Software Engineering Lecture 07: Design by Contract Peter Thiemann University of Freiburg, Germany 02.06.2014 Table of Contents Design by Contract Contracts for Procedural Programs Contracts for Object-Oriented

More information

that shows the semi-decidability of the problem (i.e. a semi-decision procedure for EXISTS-HALTING) and argue that it is correct.

that shows the semi-decidability of the problem (i.e. a semi-decision procedure for EXISTS-HALTING) and argue that it is correct. Exercise 1 (15) Consider the following problem: EXISTS-HALTING INSTANCE: A program Π, which takes as input a string over the alphabet {a, b, c,..., z}. QUESTION: Does there exist an input I, such that

More information

Foundations of Computation

Foundations of Computation The Australian National University Semester 2, 2018 Research School of Computer Science Tutorial 6 Dirk Pattinson Foundations of Computation The tutorial contains a number of exercises designed for the

More information

Proving Inter-Program Properties

Proving Inter-Program Properties Unité Mixte de Recherche 5104 CNRS - INPG - UJF Centre Equation 2, avenue de VIGNATE F-38610 GIERES tel : +33 456 52 03 40 fax : +33 456 52 03 50 http://www-verimag.imag.fr Proving Inter-Program Properties

More information

Calculating axiomatic semantics from program equations by means of functional predicate calculus

Calculating axiomatic semantics from program equations by means of functional predicate calculus Calculating axiomatic semantics from program equations by means of functional predicate calculus (Some initial results of recent work not for dissemination) Raymond Boute INTEC Ghent University 2004/02

More information

Bilateral Proofs of Safety and Progress Properties of Concurrent Programs (Working Draft)

Bilateral Proofs of Safety and Progress Properties of Concurrent Programs (Working Draft) Bilateral Proofs of Safety and Progress Properties of Concurrent Programs (Working Draft) Jayadev Misra December 18, 2015 Contents 1 Introduction 3 2 Program and Execution Model 4 2.1 Program Structure..........................

More information

Axiomatic Semantics. Operational semantics. Good for. Not good for automatic reasoning about programs

Axiomatic Semantics. Operational semantics. Good for. Not good for automatic reasoning about programs Review Operational semantics relatively l simple many flavors (small vs. big) not compositional (rule for while) Good for describing language implementation reasoning about properties of the language eg.

More information

Reasoning About Imperative Programs. COS 441 Slides 10b

Reasoning About Imperative Programs. COS 441 Slides 10b Reasoning About Imperative Programs COS 441 Slides 10b Last time Hoare Logic: { P } C { Q } Agenda If P is true in the initial state s. And C in state s evaluates to s. Then Q must be true in s. Program

More information

Unifying Theories of Programming

Unifying Theories of Programming 1&2 Unifying Theories of Programming Unifying Theories of Programming 3&4 Theories Unifying Theories of Programming designs predicates relations reactive CSP processes Jim Woodcock University of York May

More information

CSE 331 Winter 2018 Homework 1

CSE 331 Winter 2018 Homework 1 Directions: - Due Wednesday, January 10 by 11 pm. - Turn in your work online using gradescope. You should turn in a single pdf file. You can have more than one answer per page, but please try to avoid

More information

CS 336. We use the principle of inclusion and exclusion. Let B. = {five digit decimal numbers ending with a 5}, and

CS 336. We use the principle of inclusion and exclusion. Let B. = {five digit decimal numbers ending with a 5}, and CS 336 1. The important issue is the logic you used to arrive at your answer. 2. Use extra paper to determine your solutions then neatly transcribe them onto these sheets. 3. Do not submit the scratch

More information

Probabilistic Guarded Commands Mechanized in HOL

Probabilistic Guarded Commands Mechanized in HOL Probabilistic Guarded Commands Mechanized in HOL Joe Hurd joe.hurd@comlab.ox.ac.uk Oxford University Joint work with Annabelle McIver (Macquarie University) and Carroll Morgan (University of New South

More information

Axiomatic Semantics. Stansifer Ch 2.4, Ch. 9 Winskel Ch.6 Slonneger and Kurtz Ch. 11 CSE

Axiomatic Semantics. Stansifer Ch 2.4, Ch. 9 Winskel Ch.6 Slonneger and Kurtz Ch. 11 CSE Axiomatic Semantics Stansifer Ch 2.4, Ch. 9 Winskel Ch.6 Slonneger and Kurtz Ch. 11 CSE 6341 1 Outline Introduction What are axiomatic semantics? First-order logic & assertions about states Results (triples)

More information

Verifying Properties of Parallel Programs: An Axiomatic Approach

Verifying Properties of Parallel Programs: An Axiomatic Approach Verifying Properties of Parallel Programs: An Axiomatic Approach By Susan Owicki and David Gries (1976) Nathan Wetzler nwetzler@cs.utexas.edu University of Texas, Austin November 3, 2009 Outline Introduction

More information

Foundations of Quantum Programming

Foundations of Quantum Programming Foundations of Quantum Programming Mingsheng Ying University of Technology Sydney, Australia Institute of Software, Chinese Academy of Sciences Tsinghua University, China Outline Introduction Syntax of

More information

Marie Farrell Supervisors: Dr Rosemary Monahan & Dr James Power Principles of Programming Research Group

Marie Farrell Supervisors: Dr Rosemary Monahan & Dr James Power Principles of Programming Research Group EXAMINING REFINEMENT: THEORY, TOOLS AND MATHEMATICS Marie Farrell Supervisors: Dr Rosemary Monahan & Dr James Power Principles of Programming Research Group PROBLEM Different formalisms do not integrate

More information

Program Construction and Reasoning

Program Construction and Reasoning Program Construction and Reasoning Shin-Cheng Mu Institute of Information Science, Academia Sinica, Taiwan 2010 Formosan Summer School on Logic, Language, and Computation June 28 July 9, 2010 1 / 97 Introduction:

More information

Complexity and algorithms for monomial and clausal predicate abstraction

Complexity and algorithms for monomial and clausal predicate abstraction Complexity and algorithms for monomial and clausal predicate abstraction Shuvendu K. Lahiri and Shaz Qadeer Microsoft Research Abstract. In this paper, we investigate the asymptotic complexity of various

More information

Axiomatic Verification II

Axiomatic Verification II Axiomatic Verification II Software Testing and Verification Lecture Notes 18 Prepared by Stephen M. Thebaut, Ph.D. University of Florida Axiomatic Verification II Reasoning about iteration (while loops)

More information

CSC 7101: Programming Language Structures 1. Axiomatic Semantics. Stansifer Ch 2.4, Ch. 9 Winskel Ch.6 Slonneger and Kurtz Ch. 11.

CSC 7101: Programming Language Structures 1. Axiomatic Semantics. Stansifer Ch 2.4, Ch. 9 Winskel Ch.6 Slonneger and Kurtz Ch. 11. Axiomatic Semantics Stansifer Ch 2.4, Ch. 9 Winskel Ch.6 Slonneger and Kurtz Ch. 11 1 Overview We ll develop proof rules, such as: { I b } S { I } { I } while b do S end { I b } That allow us to verify

More information

Extending the theory of Owicki and Gries with a logic of progress

Extending the theory of Owicki and Gries with a logic of progress Extending the theory of Owicki and Gries with a logic of progress Brijesh Dongol Doug Goldson August 2005 Technical Report SSE-2005-03 Division of Systems and Software Engineering Research School of Information

More information

Static Program Analysis

Static Program Analysis Static Program Analysis Lecture 16: Abstract Interpretation VI (Counterexample-Guided Abstraction Refinement) Thomas Noll Lehrstuhl für Informatik 2 (Software Modeling and Verification) noll@cs.rwth-aachen.de

More information

Verifying Java-KE Programs

Verifying Java-KE Programs Verifying Java-KE Programs A Small Case Study Arnd Poetzsch-Heffter July 22, 2014 Abstract This report investigates the specification and verification of a simple list class. The example was designed such

More information

Formal Specification and Verification. Specifications

Formal Specification and Verification. Specifications Formal Specification and Verification Specifications Imprecise specifications can cause serious problems downstream Lots of interpretations even with technicaloriented natural language The value returned

More information

Formal Methods in Software Engineering

Formal Methods in Software Engineering Formal Methods in Software Engineering An Introduction to Model-Based Analyis and Testing Vesal Vojdani Department of Computer Science University of Tartu Fall 2014 Vesal Vojdani (University of Tartu)

More information

AN INTRODUCTION TO SEPARATION LOGIC. 2. Assertions

AN INTRODUCTION TO SEPARATION LOGIC. 2. Assertions AN INTRODUCTION TO SEPARATION LOGIC 2. Assertions John C. Reynolds Carnegie Mellon University January 7, 2011 c 2011 John C. Reynolds Pure Assertions An assertion p is pure iff, for all stores s and all

More information

Formal Methods for Probabilistic Systems

Formal Methods for Probabilistic Systems 1 Formal Methods for Probabilistic Systems Annabelle McIver Carroll Morgan Source-level program logic Introduction to probabilistic-program logic Systematic presentation via structural induction Layout

More information

Program Verification as Probabilistic Inference

Program Verification as Probabilistic Inference Program Verification as Probabilistic Inference Sumit Gulwani Microsoft Research, Redmond sumitg@microsoft.com Nebojsa Jojic Microsoft Research, Redmond jojic@microsoft.com Abstract In this paper, we propose

More information

Control Predicates Are Better Than Dummy Variables For Reasoning About Program Control

Control Predicates Are Better Than Dummy Variables For Reasoning About Program Control Control Predicates Are Better Than Dummy Variables For Reasoning About Program Control LESLIE LAMPORT Digital Equipment Corporation When explicit control predicates rather than dummy variables are used,

More information

Lecture Notes on Software Model Checking

Lecture Notes on Software Model Checking 15-414: Bug Catching: Automated Program Verification Lecture Notes on Software Model Checking Matt Fredrikson André Platzer Carnegie Mellon University Lecture 19 1 Introduction So far we ve focused on

More information

ICS141: Discrete Mathematics for Computer Science I

ICS141: Discrete Mathematics for Computer Science I ICS141: Discrete Mathematics for Computer Science I Dept. Information & Computer Sci., Jan Stelovsky based on slides by Dr. Baek and Dr. Still Originals by Dr. M. P. Frank and Dr. J.L. Gross Provided by

More information

Lectures on Separation Logic. Lecture 2: Foundations

Lectures on Separation Logic. Lecture 2: Foundations Lectures on Separation Logic. Lecture 2: Foundations Peter O Hearn Queen Mary, University of London Marktoberdorf Summer School, 2011 Outline for this lecture Part I : Assertions and Their Semantics Part

More information

n Empty Set:, or { }, subset of all sets n Cardinality: V = {a, e, i, o, u}, so V = 5 n Subset: A B, all elements in A are in B

n Empty Set:, or { }, subset of all sets n Cardinality: V = {a, e, i, o, u}, so V = 5 n Subset: A B, all elements in A are in B Discrete Math Review Discrete Math Review (Rosen, Chapter 1.1 1.7, 5.5) TOPICS Sets and Functions Propositional and Predicate Logic Logical Operators and Truth Tables Logical Equivalences and Inference

More information

CS156: The Calculus of Computation Zohar Manna Autumn 2008

CS156: The Calculus of Computation Zohar Manna Autumn 2008 Page 3 of 52 Page 4 of 52 CS156: The Calculus of Computation Zohar Manna Autumn 2008 Lecturer: Zohar Manna (manna@cs.stanford.edu) Office Hours: MW 12:30-1:00 at Gates 481 TAs: Boyu Wang (wangboyu@stanford.edu)

More information