Sound Invariant Checking Using Type Modifiers and Object Capabilities
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Assertions, Pre/Post- Conditions and Invariants
9/14/12 Assertions, pre/post- conditions and invariants Section 2.1 in Walls and Mirrors Section 4.5 Rosen Programming as a contract n Specifying what each method does q Specify it in a comment before method's header n Precondition q What is assumed to be true before the method is executed q Caller obligation n Postcondition q Specifies what will happen if the preconditions are met q Method obligation 1 9/14/12 Class Invariants n A class invariant is a condition that all objects of that class must satisfy while it can be observed by clients n What about Points in Cloud? q boundaries? q center? What is an assertion? n An assertion is a statement that says something about the state of your program n Should be true if there are no mistakes in the program //n == 1 while (n < limit) { n = 2 * n; } // what could you state here? 2 9/14/12 What is an assertion? n An assertion is a statement that says something about the state of your program n Should be true if there are no mistakes in the program //n == 1 while (n < limit) { n = 2 * n; } //n >= limit //more? What is an assertion? n An assertion is a statement that says something about the state of your program n Should be true if there are no mistakes in the program //n == 1 while (n < limit) { n = 2 * n; } //n >= limit //n is the smallest power of 2 >= limit 3 9/14/12 assert Using assert: assert n == 1; while (n < limit) { n = 2 * n; } assert n >= limit; When to use Assertions n We can use assertions to guarantee the behavior. -
Method Proxy-Based AOP in Scala
Vol. 0, No. 0, Z Method Proxy-Based AOP in Scala Daniel Spiewak and Tian Zhao University of Wisconsin – Milwaukee, fdspiewak,[email protected] This paper describes a fully-functional Aspect-Oriented Programming framework in Scala – a statically typed programming language with object-oriented and func- tional features. This framework is implemented as internal domain-specific lan- guages with syntax that is both intuitive and expressive. The implementation also enforces some static type safety in aspect definitions. 1 INTRODUCTION Aspect-Oriented Programming (AOP) implementations such as AspectJ provide language extensions of pointcuts and advices to insert code of crosscutting concerns into the base program through bytecode transformation. In this paper, we describe a framework to implement an AOP extension to the Scala language [13] using higher-order functions as AOP proxies 1. This framework allows programmers to specify pointcuts and aspects using a Domain Specific Language (DSL) [5] embedded within Scala. Our technique uses Scala’s higher-order functions to intercept method calls with minimal syntactic overhead imposed on the base program. This framework allows developers to define pointcuts by specifying class types and method signatures. The framework also allows access to context variables, while aspects can insert advice code before or after the advised body. The rest of the paper is organized as follows: In Section2, we present the main idea using an example. Section3 explains the syntax of pointcuts and advices. Section4 ex- plains the implementation details. We discuss the benefits and tradeoffs of our framework in Section5. and related works are in Section6. 2 EXAMPLE AOP enables developers to write code that is modularized to a point beyond the capabil- ities of vanilla object-oriented design. -
AP Computer Science Basic OOP — Implementing Classes
AP Computer Science Basic OOP — Implementing Classes ORIENTATION Object-oriented programming (OOP) refers to the organization of data into classes, categories that represent a given type of “object.” An object can be a model of a real-life thing like a car, a six-sided die, or a person, or it can be a representation of something more abstract like a point in space, a menu item, or a digital clipboard. An object that belongs to a given class is called an instance of that class, and any instance of a class keeps track of its state using instance variables, or attributes. The object is created when its constructor is called, and can be interacted with by calling its methods, which may access data (accessor methods, or “getters”) or alter the object’s data (mutator methods, or “setters”). There are two important theoretical concepts in OOP: abstraction and encapsulation. Objects and the classes they belong to act as abstractions of the things they represent: a Java class called Person isn’t actually a person, of course, but a simplified representation of a person in terms of a limited number of qualities (name and age, perhaps). Other details such as hair color, nationality, and gender identity aren’t included in our abstraction of a person. Encapsulation refers to the way that a class and its methods hide away the details of a process. Someone using a QuadraticFormula class can call the hasSolutions() method to find out whether their equation has solutions without knowing what a discriminant is. The programmer and the class she has written have hidden that information away in a metaphorical “black box.” Basic OOP consists primarily of implementing classes: writing the JavaDocs, class header, constructors, attributes, and methods for an object as specified. -
The Contract Pattern Permission Granted to Copy for Plop ’97 Conference
Copyright 1997, Michel de Champlain The Contract Pattern Permission granted to copy for PLoP ’97 Conference. All other rights reserved. Michel de Champlain Department of Computer Science University of Canterbury, Christchurch, New Zealand [email protected] http://www.cosc.canterbury.ac.nz/~michel 12 August 1997 Abstract This paper describes the Contract pattern, an idiom that lets you apply assertions to guarantee pre-conditions and post-conditions of methods and invariants on the state of objects. This pattern can be used to develop reliable classes by making the Design by Contract methodology—introduced by Meyer in the specific context of the Eiffel language—available in Java and possibly other object-oriented languages. Intent Provide an implementation of the Design by contract methodology [Meyer88] for developing reliable classes and create robust objects in Java. This programming pattern lets you apply assertions to guarantee the pre-conditions and post-conditions of methods and invariants on the state of objects. Also Known As Design by contract Motivation Sometimes it’s necessary to restrict a class interface because you don’t want to provide all the possible input combinations for all collaborators. One way to achieve this goal is to make minimal and consistent methods that impose pre-conditions on input parameters. Moreover, you might want to ensure the class behavior by imposing post-conditions before methods return. You might also need to make sure that the class is always in a stable state. Such an approach can result in reliable classes to create robust objects. Consider for example a bounded counter that has both a lower and upper bound. -
Safely Creating Correct Subclasses Without Superclass Code Clyde Dwain Ruby Iowa State University
Iowa State University Capstones, Theses and Retrospective Theses and Dissertations Dissertations 2006 Modular subclass verification: safely creating correct subclasses without superclass code Clyde Dwain Ruby Iowa State University Follow this and additional works at: https://lib.dr.iastate.edu/rtd Part of the Computer Sciences Commons Recommended Citation Ruby, Clyde Dwain, "Modular subclass verification: safely creating correct subclasses without superclass code " (2006). Retrospective Theses and Dissertations. 1877. https://lib.dr.iastate.edu/rtd/1877 This Dissertation is brought to you for free and open access by the Iowa State University Capstones, Theses and Dissertations at Iowa State University Digital Repository. It has been accepted for inclusion in Retrospective Theses and Dissertations by an authorized administrator of Iowa State University Digital Repository. For more information, please contact [email protected]. Modular subclass verification: Safely creating correct subclasses without superclass code by Clyde Dwain Ruby A dissertation submitted to the graduate faculty in partial fulfillment of the requirements for the degree of DOCTOR OF PHILOSOPHY Major: Computer Science Program of Study Committee Gary T. Leavens, Major Professor Samik Basu Clifford Bergman Shashi K. Gadia Jonathan D. H. Smith Iowa State University Ames, Iowa 2006 Copyright © Clyde Dwain Ruby, 2006. All rights reserved. UMI Number: 3243833 Copyright 2006 by Ruby, Clyde Dwain All rights reserved. UMI Microform 3243833 Copyright 2007 by ProQuest Information and Learning Company. All rights reserved. This microform edition is protected against unauthorized copying under Title 17, United States Code. ProQuest Information and Learning Company 300 North Zeeb Road P.O. Box 1346 Ann Arbor, MI 48106-1346 ii TABLE OF CONTENTS ACKNOWLEDGEMENTS . -
3. Design by Contract
3. Design by Contract Oscar Nierstrasz Design by Contract Bertrand Meyer, Touch of Class — Learning to Program Well with Objects and Contracts, Springer, 2009. 2 Bertrand Meyer is a French computer scientist who was a Professor at ETH Zürich (successor of Niklaus Wirth) from 2001-2015. He is best known as the inventor of “Design by Contract”, and as the designer of the Eiffel programming language, which provides built-in for DbC. DbC was first described in a technical report by Meyer in 1986: https://en.wikipedia.org/wiki/Design_by_contract Who’s to blame? The components fit but the system does not work. Who’s to blame? The component developer or the system integrator? 3 DbC makes clear the “contract” between a supplier (an object or “component”) and its client. When something goes wrong, the contract states whose fault it is. This simplifies both design and debugging. Why DbC? > Design by Contract —documents assumptions (what do objects expect?) —simplifies code (no special actions for failure) —aids debugging (identifies who’s to blame) 4 As we shall see, DbC improves your OO design in several ways. First, contracts make explicit the assumptions under which an object (supplier) will work correctly. Second, they simplify your code, since no special action is required when things go wrong — the exception handling framework provides the necessary tools. Third, contracts help in debugging since errors are caught earlier, when contracts are violated, not when your program crashes because of an invalid state, and it is clear where to lay the blame for the violation (i.e., in the object or its client). -
FORTH-ICS / TR 381 July 2006 'An Informal Proof on the Contradictory
FORTH-ICS / TR 381 July 2006 ‘An Informal Proof on the Contradictory Role of Finalizers in a Garbage Collection Context’ Anthony Savidis ABSTRACT Garbage collection in OOP languages provides facilities to hook code that is executed upon object finalization. Semantically, the point in time that finalizer code is executed is not determined by the application logic, but by the garbage collection system. This fact renders a potential mismatch, since application-specific code, i.e. the finalizer implementation, normally affecting program state and control flow, is called automatically at a point in time that is indifferent to the application semantics. Although an analogous situation is observed in event-based systems, since event processors are called-back asynchronously by the underlying system, there is a fundamental difference: while event generation is essentially nondeterministic, originated from external event sources, object destruction is a semantic action that is always decided by applications. In summary, the mismatch is that although applications decide if and when destruction occurs, the garbage collector is responsible to commit the relevant code. We prove that this mismatch is due to the contradictory presence of finalizers in a garbage collection context. Page 1 Introduction Preface This technical report has been also motivated by requests from colleagues to report the informal proof for the contradictory role of finalizers in garbage collection, simply relying on informal common software engineering principles. Additionally, the reporting has been also motivated by arguments that came to my attention via personal communication that either the claim cannot be proved (I assume that “cannot prove” arguments are subject to formal proofs, so such arguments are more weak than the claim they attack), or that the claim is trivial requiring essentially no proof (intuitively true, but does not explain why Java, C#, Python, just to name a few languages, still adopt finalizers). -
A Machine-Checked Proof for a Translation of Event-B Machines to JML
A Machine-Checked Proof for a Translation of Event-B Machines to JML N´estorCata~no1,Camilo Rueda2, and Tim Wahls3 1 EAFIT Unviersity [email protected] 2 Camilo Rueda Pontificia Universidad Javeriana [email protected] 3 Tim Wahls Dickinson College [email protected] Abstract. We present a machine-checked soundness proof of a trans- lation of Event-B to the Java Modeling Language (JML). The transla- tion is based on an operator EB2Jml that maps Event-B events to JML method specifications, and deterministic and non-deterministic assign- ments to JML method post-conditions. This translation has previously been implemented as the EventB2Jml tool. We adopted a taking our own medicine approach in the formalisation of our proof so that Event-B as well as JML are formalised in Event-B and the proof is discharged with the Rodin platform. Hence, for any Event-B substitution (whether an event or an assignment) and for the JML method specification obtained by applying EventB2Jml to the substitution, we prove that the semantics of the JML method specification is simulated by the semantics of the sub- stitution. Therefore, the JML specification obtained as translation from the Event-B substitution is a refinement of the substitution. Our proof includes invariants and the standard Event-B initialising event, but it does not include full machines or Event-B contexts. We assume that the semantics of JML and Event-B operate both on the same initial and final states, and we justify our assumption. Keywords: Event-B, JML, EventB2Jml, Formal Proof, Translation, Rodin 1 Introduction arXiv:1309.2339v1 [cs.SE] 9 Sep 2013 In an earlier work [14], we have proposed a design methodology that combines the use of design-by-contract techniques with JML [36,29,33] and correctness-by- construction techniques with Event-B [1]. -
Verification of Object Oriented Programs Using Class Invariants
Verification of Object Oriented Programs Using Class Invariants Kees Huizing and Ruurd Kuiper and SOOP?? Eindhoven University of Technology, PO Box 513, 5600 MB Eindhoven, The Netherlands, [email protected], [email protected] Abstract A proof system is presented for the verification and derivation of object oriented pro- grams with as main features strong typing, dynamic binding, and inheritance. The proof system is inspired on Meyer’s system of class invariants [12] and remedies its unsound- ness, which is already recognized by Meyer. Dynamic binding is treated in a flexible way: when throughout the class hierarchy overriding methods respect the pre- and post- conditions of the overridden methods, very simple proof rules for method calls suffice; more powerful proof rules are supplied for cases where one cannot or does not want to follow this restriction. The proof system is complete relative to proofs for properties of pointers and the data domain. 1 Introduction Although formal verification is not very common in the discipline of object oriented programming, the importance of formal specification is generally ac- knowledged ([12]). With the increased interest in component based develop- ment, it becomes even more important that components are specified in an un- ambiguous manner, since users or buyers of components often have no other knowledge about a component than its specification and at the same time rely heavily on its correct functioning in their framework. The specification of a class, sometimes called contract, usually contains at least pre- and postcondi- tions for the public mehtods and a class invariant. A class invariant expresses which states of the objects of the class are consis- tent, or “legal”. -
The Fields and the Class Invariant /** B[0..Size-1] Is a Min-Heap, I.E
Heaps with priorities We previously studied the max-heap, which implements a bag of integers with insertion of a value and extraction (polling) of a maximum value in O(log n) time for a heap of size n. Min-heaps are similar. We now extend the idea to implement a min-heap of a set of distinct values each with a priority. The priority will be a double value. The separation of value from priority is needed in several different situations. Here are two: • Consider finding the shortest route from Ithaca, NY, to Washington, D.C. A heap will contain points along the way, and the priorities will be the shortest distances found thus far from Ithaca to those points. • In a discrete event simulation, pending events can be kept in a heap, with the priority being the time at which an event is to occur. Keeping the set in a min-heap makes it easy to extract the next event to process. We will define all the methods needed, but we won’t show many of the method bodies, since they are fairly easy to write based on the earlier discussion of max- and min-heaps. Class Heap and inner class Item /** A heap of elements of type E. */ We will implement a generic min-heap with priorities. The public class Heap<E> { start of class Heap appears to the right. An object of this class implements a heap of elements of type E. For example, E could private class Item { be a point on a map or an event to be simulated. -
Weaving Aspects Into C++ Applications for Validation of Temporal Invariants
Weaving Aspects into C++ Applications for Validation of Temporal Invariants Tanton H. Gibbs and Brian A. Malloy Computer Science Department Clemson University Clemson, SC 29634, USA thgibbs, malloy @cs.clemson.edu f g Abstract [5]. During maintenance, invariants have proven invaluable for disclosing locations in the program In this paper, we describe temporal invariants, where the maintainer may have introduced a fault which are class invariants that are qualified by the [10]. operators eventually, always, never, or already. Tem- The problem with class invariants is that some poral invariants can capture assertions that may not important assertions about a class are initially in- be valid initially but, as the program continues, must valid, due to circular dependencies or the monoton- eventually become valid. Moreover, temporal invari- ically increasing nature of the system under con- ants can indicate references to memory that should struction [8]. For example, during compilation of eventually be deallocated. To facilitate incorporation a program, a name object is constructed to facil- of temporal invariants as a maintenance or reengi- itate name lookup. However, certain fields in the neering activity, we weave invariants into the sys- name object, such as the corresponding scope of the tem as aspects. In our case study of a C++ sys- name, may not be known until after name lookup tem, the aspects are woven into join points using has occurred [24]. Moreover, assertions about a policies. We investigate the effectiveness of tem- class may have an important impact on memory poral invariants and we compare the performance management. For example, some heap-based ob- of our aspect-oriented implementation with several jects of a class must be eventually deleted or system other approaches. -
Learn Objective–C on The
CYAN YELLOW SPOT MATTE MAGENTA BLACK PANTONE 123 C BOOKS FOR PROFESSIONALS BY PROFESSIONALS® Companion eBook Available Learn Objective-CLearn • Learn the native programming language for Mac OS X, Everything You Need to Know as well as the iPhone! to Become an Objective-C Guru • Get up and running quickly with Objective-C. We don’t waste time teaching you basic programming; instead, we focus on what makes Objective-C di!erent and cool. • Learn about sophisticated programming concepts, including object-oriented programming, the Open-Closed Principle, refactoring, key-value coding, and predicates. n this book, you’ll !nd a full exploration of the Objective-C programming Ilanguage, the primary language for creating Mac OS X and iPhone applica- tions. There are goodies here for everyone, whether you’re just starting out as a Mac developer or a grizzled programmer coming from another language. You’ll discover all of the object-oriented purity and Smalltalk heritage coolness of Objective-C—such as instantiation, protocols for multiple inheritance, dynamic typing, and message forwarding. Along the way, you’ll meet Xcode, the Mac development environment, and you’ll learn about Apple’s Cocoa toolkit. on the Nearly everyone wants to be able to develop for Mac OS X or the iPhone these days, and it’s no wonder. The Mac is a fun and powerful platform, and Objective-C is a wonderful language for writing code. You can have a great time programming the Mac in Objective-C. We do, and want you to join us! Mark Dalrymple is a longtime Mac and Unix programmer who has Mac code running all over the world.