Why Nominal-Typing Matters in Mainstream
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Proof-Carrying Authentication∗
Proof-Carrying Authentication∗ Andrew W. Appel and Edward W. Felten Secure Internet Programming Laboratory Department of Computer Science Princeton University Princeton, NJ 08544 USA August 9, 1999 Abstract Statements in these frameworks are represented as data structures that are often digitally signed We have designed and implemented a general to ensure their integrity. and powerful distributed authentication frame- work based on higher-order logic. Authenti- Several authentication frameworks exist; we cation frameworks — including Taos, SPKI, mention a few here as examples. The Taos SDSI, and X.509 — have been explained using operating system provided support for secure logic. We show that by starting with the logic, remote procedure call and data structures to we can implement these frameworks, all in the represent authority and identity [6]. X.509 [15] same concise and efficient system. Because our is a widely-used standard for expressing and us- logic has no decision procedure — although ing digital certificates. SPKI [4] and SDSI [14] proof checking is simple — users of the frame- (since merged under the joint name SPKI) work must submit proofs with their requests. were reactions to the perceived complexity of X.509; in both cases the ‘S’ stands for ‘simple.’ 1 Introduction PolicyMaker [3] is a language for expressing se- curity policies; it can be applied to distributed Distributed authentication frameworks allow security policies. Kerberos [12], unlike the other sharing of access to resources across adminis- frameworks, uses symmetric-key encryption to trative boundaries in a distributed system. The authenticate users. Each framework has a main abstractions they support are name-to- differerent semantics and offers a different kind key bindings, access control, and delegation. -
Safe, Fast and Easy: Towards Scalable Scripting Languages
Safe, Fast and Easy: Towards Scalable Scripting Languages by Pottayil Harisanker Menon A dissertation submitted to The Johns Hopkins University in conformity with the requirements for the degree of Doctor of Philosophy. Baltimore, Maryland Feb, 2017 ⃝c Pottayil Harisanker Menon 2017 All rights reserved Abstract Scripting languages are immensely popular in many domains. They are char- acterized by a number of features that make it easy to develop small applications quickly - flexible data structures, simple syntax and intuitive semantics. However they are less attractive at scale: scripting languages are harder to debug, difficult to refactor and suffers performance penalties. Many research projects have tackled the issue of safety and performance for existing scripting languages with mixed results: the considerable flexibility offered by their semantics also makes them significantly harder to analyze and optimize. Previous research from our lab has led to the design of a typed scripting language built specifically to be flexible without losing static analyzability. Inthis dissertation, we present a framework to exploit this analyzability, with the aim of producing a more efficient implementation Our approach centers around the concept of adaptive tags: specialized tags attached to values that represent how it is used in the current program. Our frame- work abstractly tracks the flow of deep structural types in the program, and thuscan ii ABSTRACT efficiently tag them at runtime. Adaptive tags allow us to tackle key issuesatthe heart of performance problems of scripting languages: the framework is capable of performing efficient dispatch in the presence of flexible structures. iii Acknowledgments At the very outset, I would like to express my gratitude and appreciation to my advisor Prof. -
Comparative Studies of Programming Languages; Course Lecture Notes
Comparative Studies of Programming Languages, COMP6411 Lecture Notes, Revision 1.9 Joey Paquet Serguei A. Mokhov (Eds.) August 5, 2010 arXiv:1007.2123v6 [cs.PL] 4 Aug 2010 2 Preface Lecture notes for the Comparative Studies of Programming Languages course, COMP6411, taught at the Department of Computer Science and Software Engineering, Faculty of Engineering and Computer Science, Concordia University, Montreal, QC, Canada. These notes include a compiled book of primarily related articles from the Wikipedia, the Free Encyclopedia [24], as well as Comparative Programming Languages book [7] and other resources, including our own. The original notes were compiled by Dr. Paquet [14] 3 4 Contents 1 Brief History and Genealogy of Programming Languages 7 1.1 Introduction . 7 1.1.1 Subreferences . 7 1.2 History . 7 1.2.1 Pre-computer era . 7 1.2.2 Subreferences . 8 1.2.3 Early computer era . 8 1.2.4 Subreferences . 8 1.2.5 Modern/Structured programming languages . 9 1.3 References . 19 2 Programming Paradigms 21 2.1 Introduction . 21 2.2 History . 21 2.2.1 Low-level: binary, assembly . 21 2.2.2 Procedural programming . 22 2.2.3 Object-oriented programming . 23 2.2.4 Declarative programming . 27 3 Program Evaluation 33 3.1 Program analysis and translation phases . 33 3.1.1 Front end . 33 3.1.2 Back end . 34 3.2 Compilation vs. interpretation . 34 3.2.1 Compilation . 34 3.2.2 Interpretation . 36 3.2.3 Subreferences . 37 3.3 Type System . 38 3.3.1 Type checking . 38 3.4 Memory management . -
A Model of Inheritance for Declarative Visual Programming Languages
An Abstract Of The Dissertation Of Rebecca Djang for the degree of Doctor of Philosophy in Computer Science presented on December 17, 1998. Title: Similarity Inheritance: A Model of Inheritance for Declarative Visual Programming Languages. Abstract approved: Margaret M. Burnett Declarative visual programming languages (VPLs), including spreadsheets, make up a large portion of both research and commercial VPLs. Spreadsheets in particular enjoy a wide audience, including end users. Unfortunately, spreadsheets and most other declarative VPLs still suffer from some of the problems that have been solved in other languages, such as ad-hoc (cut-and-paste) reuse of code which has been remedied in object-oriented languages, for example, through the code-reuse mechanism of inheritance. We believe spreadsheets and other declarative VPLs can benefit from the addition of an inheritance-like mechanism for fine-grained code reuse. This dissertation first examines the opportunities for supporting reuse inherent in declarative VPLs, and then introduces similarity inheritance and describes a prototype of this model in the research spreadsheet language Forms/3. Similarity inheritance is very flexible, allowing multiple granularities of code sharing and even mutual inheritance; it includes explicit representations of inherited code and all sharing relationships, and it subsumes the current spreadsheet mechanisms for formula propagation, providing a gradual migration from simple formula reuse to more sophisticated uses of inheritance among objects. Since the inheritance model separates inheritance from types, we investigate what notion of types is appropriate to support reuse of functions on different types (operation polymorphism). Because it is important to us that immediate feedback, which is characteristic of many VPLs, be preserved, including feedback with respect to type errors, we introduce a model of types suitable for static type inference in the presence of operation polymorphism with similarity inheritance. -
Static Analyses for Stratego Programs
Static analyses for Stratego programs BSc project report June 30, 2011 Author name Vlad A. Vergu Author student number 1195549 Faculty Technical Informatics - ST track Company Delft Technical University Department Software Engineering Commission Ir. Bernard Sodoyer Dr. Eelco Visser 2 I Preface For the successful completion of their Bachelor of Science, students at the faculty of Computer Science of the Technical University of Delft are required to carry out a software engineering project. The present report is the conclusion of this Bachelor of Science project for the student Vlad A. Vergu. The project has been carried out within the Software Language Design and Engineering Group of the Computer Science faculty, under the direct supervision of Dr. Eelco Visser of the aforementioned department and Ir. Bernard Sodoyer. I would like to thank Dr. Eelco Visser for his past and ongoing involvment and support in my educational process and in particular for the many opportunities for interesting and challenging projects. I further want to thank Ir. Bernard Sodoyer for his support with this project and his patience with my sometimes unconvential way of working. Vlad Vergu Delft; June 30, 2011 II Summary Model driven software development is gaining momentum in the software engi- neering world. One approach to model driven software development is the design and development of domain-specific languages allowing programmers and users to spend more time on their core business and less on addressing non problem- specific issues. Language workbenches and support languages and compilers are necessary for supporting development of these domain-specific languages. One such workbench is the Spoofax Language Workbench. -
Blossom: a Language Built to Grow
Macalester College DigitalCommons@Macalester College Mathematics, Statistics, and Computer Science Honors Projects Mathematics, Statistics, and Computer Science 4-26-2016 Blossom: A Language Built to Grow Jeffrey Lyman Macalester College Follow this and additional works at: https://digitalcommons.macalester.edu/mathcs_honors Part of the Computer Sciences Commons, Mathematics Commons, and the Statistics and Probability Commons Recommended Citation Lyman, Jeffrey, "Blossom: A Language Built to Grow" (2016). Mathematics, Statistics, and Computer Science Honors Projects. 45. https://digitalcommons.macalester.edu/mathcs_honors/45 This Honors Project - Open Access is brought to you for free and open access by the Mathematics, Statistics, and Computer Science at DigitalCommons@Macalester College. It has been accepted for inclusion in Mathematics, Statistics, and Computer Science Honors Projects by an authorized administrator of DigitalCommons@Macalester College. For more information, please contact [email protected]. In Memory of Daniel Schanus Macalester College Department of Mathematics, Statistics, and Computer Science Blossom A Language Built to Grow Jeffrey Lyman April 26, 2016 Advisor Libby Shoop Readers Paul Cantrell, Brett Jackson, Libby Shoop Contents 1 Introduction 4 1.1 Blossom . .4 2 Theoretic Basis 6 2.1 The Potential of Types . .6 2.2 Type basics . .6 2.3 Subtyping . .7 2.4 Duck Typing . .8 2.5 Hindley Milner Typing . .9 2.6 Typeclasses . 10 2.7 Type Level Operators . 11 2.8 Dependent types . 11 2.9 Hoare Types . 12 2.10 Success Types . 13 2.11 Gradual Typing . 14 2.12 Synthesis . 14 3 Language Description 16 3.1 Design goals . 16 3.2 Type System . 17 3.3 Hello World . -
Unifying Theories of Objects
Unifying Theories of Objects Michael Anthony Smith1;2 and Jeremy Gibbons1 1 Oxford University, UK. 2 Systems Assurance Group, QinetiQ, UK. [email protected] [email protected] Abstract. We present an approach to modelling Abadi{Cardelli-style object calculi as Unifying Theories of Programming (UTP) designs. Here we provide a core object calculus with an operational small-step evalua- tion rule semantics, and a corresponding UTP model with a denotational relational predicate semantics. For clarity, the UTP model is defined in terms of an operand stack, which is used to store the results of sub- programs. Models of a less operational nature are briefly discussed. The consistency of the UTP model is demonstrated by a structural induction proof over the operations of the core object calculus. Overall, our UTP model is intended to provide facilities for encoding both object-based and class-based languages. 1 Introduction Hoare and He's Unifying Theories of Programming (UTP) [6] can be used to formally define how results produced in one formal model can be translated as assumptions to another formal model. Essentially, programs are considered to be predicates that relate the values of their observable input and output variables (their alphabet). For example, the increment program x := x + 1 is typically defined by the relational predicate x 0 = x + 1, where predicate variables x and x 0 denote the input and output values of the program variable x. In general, the alphabet of a program P is denoted by αP; it is the disjoint union of P's input and output sets (inαP and outαP respectively), which in the case of the example is the set fx; x 0g. -
BEGINNING OBJECT-ORIENTED PROGRAMMING with JAVASCRIPT Build up Your Javascript Skills and Embrace PRODUCT Object-Oriented Development for the Modern Web INFORMATION
BEGINNING OBJECT-ORIENTED PROGRAMMING WITH JAVASCRIPT Build up your JavaScript skills and embrace PRODUCT object-oriented development for the modern web INFORMATION FORMAT DURATION PUBLISHED ON Instructor-Led Training 3 Days 22nd November, 2017 DESCRIPTION OUTLINE JavaScript has now become a universal development Diving into Objects and OOP Principles language. Whilst offering great benefits, the complexity Creating and Managing Object Literals can be overwhelming. Defining Object Constructors Using Object Prototypes and Classes In this course we show attendees how they can write Checking Abstraction and Modeling Support robust and efficient code with JavaScript, in order to Analyzing OOP Principles in JavaScript create scalable and maintainable web applications that help developers and businesses stay competitive. Working with Encapsulation and Information Hiding Setting up Strategies for Encapsulation LEARNING OUTCOMES Using the Meta-Closure Approach By completing this course, you will: Using Property Descriptors Implementing Information Hiding in Classes • Cover the new object-oriented features introduced as a part of ECMAScript 2015 Inheriting and Creating Mixins • Build web applications that promote scalability, Implementing Objects, Inheritance, and Prototypes maintainability and usability Using and Controlling Class Inheritance • Learn about key principles like object inheritance and Implementing Multiple Inheritance JavaScript mixins Creating and Using Mixins • Discover how to skilfully develop asynchronous code Defining Contracts with Duck Typing within larger JS applications Managing Dynamic Typing • Complete a variety of hands-on activities to build Defining Contracts and Interfaces up your experience of real-world challenges and Implementing Duck Typing problems Comparing Duck Typing and Polymorphism WHO SHOULD ATTEND Advanced Object Creation Mastering Patterns, Object Creation, and Singletons This course is for existing developers who are new to Implementing an Object Factory object-oriented programming in the JavaScript language. -
4500/6500 Programming Languages What Are Types? Different Definitions
What are Types? ! Denotational: Collection of values from domain CSCI: 4500/6500 Programming » integers, doubles, characters ! Abstraction: Collection of operations that can be Languages applied to entities of that type ! Structural: Internal structure of a bunch of data, described down to the level of a small set of Types fundamental types ! Implementers: Equivalence classes 1 Maria Hybinette, UGA Maria Hybinette, UGA 2 Different Definitions: Types versus Typeless What are types good for? ! Documentation: Type for specific purposes documents 1. "Typed" or not depends on how the interpretation of the program data representations is determined » Example: Person, BankAccount, Window, Dictionary » When an operator is applied to data objects, the ! Safety: Values are used consistent with their types. interpretation of their values could be determined either by the operator or by the data objects themselves » Limit valid set of operation » Languages in which the interpretation of a data object is » Type Checking: Prevents meaningless operations (or determined by the operator applied to it are called catch enough information to be useful) typeless languages; ! Efficiency: Exploit additional information » those in which the interpretation is determined by the » Example: a type may dictate alignment at at a multiple data object itself are called typed languages. of 4, the compiler may be able to use more efficient 2. Sometimes it just means that the object does not need machine code instructions to be explicitly declared (Visual Basic, Jscript -
Multiparadigm Programming with Python 3 Chapter 5
Multiparadigm Programming with Python 3 Chapter 5 H. Conrad Cunningham 7 September 2018 Contents 5 Python 3 Types 2 5.1 Chapter Introduction . .2 5.2 Type System Concepts . .2 5.2.1 Types and subtypes . .2 5.2.2 Constants, variables, and expressions . .2 5.2.3 Static and dynamic . .3 5.2.4 Nominal and structural . .3 5.2.5 Polymorphic operations . .4 5.2.6 Polymorphic variables . .5 5.3 Python 3 Type System . .5 5.3.1 Objects . .6 5.3.2 Types . .7 5.4 Built-in Types . .7 5.4.1 Singleton types . .8 5.4.1.1 None .........................8 5.4.1.2 NotImplemented ..................8 5.4.2 Number types . .8 5.4.2.1 Integers (int)...................8 5.4.2.2 Real numbers (float)...............9 5.4.2.3 Complex numbers (complex)...........9 5.4.2.4 Booleans (bool)..................9 5.4.2.5 Truthy and falsy values . 10 5.4.3 Sequence types . 10 5.4.3.1 Immutable sequences . 10 5.4.3.2 Mutable sequences . 12 5.4.4 Mapping types . 13 5.4.5 Set Types . 14 5.4.5.1 set ......................... 14 5.4.5.2 frozenset ..................... 14 5.4.6 Other object types . 15 1 5.5 What Next? . 15 5.6 Exercises . 15 5.7 Acknowledgements . 15 5.8 References . 16 5.9 Terms and Concepts . 16 Copyright (C) 2018, H. Conrad Cunningham Professor of Computer and Information Science University of Mississippi 211 Weir Hall P.O. Box 1848 University, MS 38677 (662) 915-5358 Browser Advisory: The HTML version of this textbook requires a browser that supports the display of MathML. -
Reducing Costs with Structural Typing.Key
Reducing Costs with StructuralDuck Typing 1 “Duck Typing” In computer programming with object-oriented programming languages, duck typing is a layer of programming language and design rules on top of typing. Typing is concerned withvacuous! assigning a type to any object. Duckunnecessary! typing is concerned with establishing the suitability of an object for some purpose. With normalclass typing, suitability is assumed to be determined by an object’s typeclass only. With nominal typing, suitability is assumed to depend on the claims made when the object was created In contrast in duck typing, an object's suitability is determined by the presence of certain methods and properties (with appropriate meaning), rather than the actual type of the object. The name of the concept refers to the duck test, attributed to James Whitcomb Riley, which may be phrased as follows: When I see a bird that walks like a duck and swims like a duck and quacks like a duck, I call that bird a duck.[1] Some confusion present here 2 Metz: • Duck types are public interfaces that are not tied to any specific class • A Ruby object is like a partygoer at a masquerade ballGrace that changes masks to suit the theme. It can expose a different face to every viewer; it can implement many different interfaces. • … an object’s type is in the eye of the beholder. Users of an object need not, and should not, be concerned about its class. • It’s not what an object is that matters, it’s what it does. 3 Structural vs. Nominal • Structural typing (Duck Typing) ✦ a type T describes a set of properties (so, it’s like a predicate). -
Admission Control for Independently-Authored Realtime Applications
Admission Control for Independently-authored Realtime Applications by Robert Kroeger Athesis presented to the University of Waterloo in fulfilment of the thesis requirement for the degree of Doctor of Philosophy in Computer Science Waterloo, Ontario, Canada, 2004 c Robert Kroeger 2004 AUTHOR’S DECLARATION FOR ELECTRONIC SUBMISSION OF A THESIS I hereby declare that I am the sole author of this thesis. This is a true copy of the thesis, including any required final revisions, as accepted by my examiners. I understand that my thesis may be made electronically available to the public. ii Abstract This thesis presents the LiquiMedia operating system architecture. LiquiMedia is specialized to schedule multimedia applications. Because they generate output for a human observer, multimedia applications such as video games, video conferencing and video players have both unique scheduling requirements and unique allowances: a multimedia stream must synchro- nize sub-streams generated for different sensory modalities within 20 milliseconds, it is not successfully segregated until it has existed for over 200 milliseconds and tolerates occasional scheduling failures. LiquiMedia is specialized around these requirements and allowances. First, LiquiMedia synchronizes multimedia tasks by invoking them from a shared realtime timer interrupt. Sec- ond, owing to multimedia’s tolerance of scheduling failures, LiquiMedia schedules tasks based on a probabilistic model of their running times. Third, LiquiMedia can infer per-task models while a user is segregating the streams that the tasks generate. These specializations provide novel capabilities: up to 2.5 times higher utilization than RMS scheduling, use of an atomic task primitive 9.5 times more efficient than preemptive threading, and most importantly, the ability to schedule arbitrary tasks to a known probability of realtime execution without a priori knowledge of their running times.