Should Your Specification Language Be Typed?
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A Polymorphic Type System for Extensible Records and Variants
A Polymorphic Typ e System for Extensible Records and Variants Benedict R. Gaster and Mark P. Jones Technical rep ort NOTTCS-TR-96-3, November 1996 Department of Computer Science, University of Nottingham, University Park, Nottingham NG7 2RD, England. fbrg,[email protected] Abstract b oard, and another indicating a mouse click at a par- ticular p oint on the screen: Records and variants provide exible ways to construct Event = Char + Point : datatyp es, but the restrictions imp osed by practical typ e systems can prevent them from b eing used in ex- These de nitions are adequate, but they are not par- ible ways. These limitations are often the result of con- ticularly easy to work with in practice. For example, it cerns ab out eciency or typ e inference, or of the di- is easy to confuse datatyp e comp onents when they are culty in providing accurate typ es for key op erations. accessed by their p osition within a pro duct or sum, and This pap er describ es a new typ e system that reme- programs written in this way can b e hard to maintain. dies these problems: it supp orts extensible records and To avoid these problems, many programming lan- variants, with a full complement of p olymorphic op era- guages allow the comp onents of pro ducts, and the al- tions on each; and it o ers an e ective type inference al- ternatives of sums, to b e identi ed using names drawn gorithm and a simple compilation metho d. -
On-The-Fly Garbage Collection: an Exercise in Cooperation
8. HoIn, B.K.P. Determining lightness from an image. Comptr. Graphics and Image Processing 3, 4(Dec. 1974), 277-299. 9. Huffman, D.A. Impossible objects as nonsense sentences. In Machine Intelligence 6, B. Meltzer and D. Michie, Eds., Edinburgh U. Press, Edinburgh, 1971, pp. 295-323. 10. Mackworth, A.K. Consistency in networks of relations. Artif. Intell. 8, 1(1977), 99-118. I1. Marr, D. Simple memory: A theory for archicortex. Philos. Trans. Operating R.S. Gaines Roy. Soc. B. 252 (1971), 23-81. Systems Editor 12. Marr, D., and Poggio, T. Cooperative computation of stereo disparity. A.I. Memo 364, A.I. Lab., M.I.T., Cambridge, Mass., 1976. On-the-Fly Garbage 13. Minsky, M., and Papert, S. Perceptrons. M.I.T. Press, Cambridge, Mass., 1968. Collection: An Exercise in 14. Montanari, U. Networks of constraints: Fundamental properties and applications to picture processing. Inform. Sci. 7, 2(April 1974), Cooperation 95-132. 15. Rosenfeld, A., Hummel, R., and Zucker, S.W. Scene labelling by relaxation operations. IEEE Trans. Systems, Man, and Cybernetics Edsger W. Dijkstra SMC-6, 6(June 1976), 420-433. Burroughs Corporation 16. Sussman, G.J., and McDermott, D.V. From PLANNER to CONNIVER--a genetic approach. Proc. AFIPS 1972 FJCC, Vol. 41, AFIPS Press, Montvale, N.J., pp. 1171-1179. Leslie Lamport 17. Sussman, G.J., and Stallman, R.M. Forward reasoning and SRI International dependency-directed backtracking in a system for computer-aided circuit analysis. A.I. Memo 380, A.I. Lab., M.I.T., Cambridge, Mass., 1976. A.J. Martin, C.S. -
Arxiv:1909.05204V3 [Cs.DC] 6 Feb 2020
Cogsworth: Byzantine View Synchronization Oded Naor, Technion and Calibra Mathieu Baudet, Calibra Dahlia Malkhi, Calibra Alexander Spiegelman, VMware Research Most methods for Byzantine fault tolerance (BFT) in the partial synchrony setting divide the local state of the nodes into views, and the transition from one view to the next dictates a leader change. In order to provide liveness, all honest nodes need to stay in the same view for a sufficiently long time. This requires view synchronization, a requisite of BFT that we extract and formally define here. Existing approaches for Byzantine view synchronization incur quadratic communication (in n, the number of parties). A cascade of O(n) view changes may thus result in O(n3) communication complexity. This paper presents a new Byzantine view synchronization algorithm named Cogsworth, that has optimistically linear communication complexity and constant latency. Faced with benign failures, Cogsworth has expected linear communication and constant latency. The result here serves as an important step towards reaching solutions that have overall quadratic communication, the known lower bound on Byzantine fault tolerant consensus. Cogsworth is particularly useful for a family of BFT protocols that already exhibit linear communication under various circumstances, but suffer quadratic overhead due to view synchro- nization. 1. INTRODUCTION Logical synchronization is a requisite for progress to be made in asynchronous state machine repli- cation (SMR). Previous Byzantine fault tolerant (BFT) synchronization mechanisms incur quadratic message complexities, frequently dominating over the linear cost of the consensus cores of BFT so- lutions. In this work, we define the view synchronization problem and provide the first solution in the Byzantine setting, whose latency is bounded and communication cost is linear, under a broad set of scenarios. -
Mathematical Writing by Donald E. Knuth, Tracy Larrabee, and Paul M
Mathematical Writing by Donald E. Knuth, Tracy Larrabee, and Paul M. Roberts This report is based on a course of the same name given at Stanford University during autumn quarter, 1987. Here's the catalog description: CS 209. Mathematical Writing|Issues of technical writing and the ef- fective presentation of mathematics and computer science. Preparation of theses, papers, books, and \literate" computer programs. A term paper on a topic of your choice; this paper may be used for credit in another course. The first three lectures were a \minicourse" that summarized the basics. About two hundred people attended those three sessions, which were devoted primarily to a discussion of the points in x1 of this report. An exercise (x2) and a suggested solution (x3) were also part of the minicourse. The remaining 28 lectures covered these and other issues in depth. We saw many examples of \before" and \after" from manuscripts in progress. We learned how to avoid excessive subscripts and superscripts. We discussed the documentation of algorithms, com- puter programs, and user manuals. We considered the process of refereeing and editing. We studied how to make effective diagrams and tables, and how to find appropriate quota- tions to spice up a text. Some of the material duplicated some of what would be discussed in writing classes offered by the English department, but the vast majority of the lectures were devoted to issues that are specific to mathematics and/or computer science. Guest lectures by Herb Wilf (University of Pennsylvania), Jeff Ullman (Stanford), Leslie Lamport (Digital Equipment Corporation), Nils Nilsson (Stanford), Mary-Claire van Leunen (Digital Equipment Corporation), Rosalie Stemer (San Francisco Chronicle), and Paul Halmos (University of Santa Clara), were a special highlight as each of these outstanding authors presented their own perspectives on the problems of mathematical communication. -
Generic Programming
Generic Programming July 21, 1998 A Dagstuhl Seminar on the topic of Generic Programming was held April 27– May 1, 1998, with forty seven participants from ten countries. During the meeting there were thirty seven lectures, a panel session, and several problem sessions. The outcomes of the meeting include • A collection of abstracts of the lectures, made publicly available via this booklet and a web site at http://www-ca.informatik.uni-tuebingen.de/dagstuhl/gpdag.html. • Plans for a proceedings volume of papers submitted after the seminar that present (possibly extended) discussions of the topics covered in the lectures, problem sessions, and the panel session. • A list of generic programming projects and open problems, which will be maintained publicly on the World Wide Web at http://www-ca.informatik.uni-tuebingen.de/people/musser/gp/pop/index.html http://www.cs.rpi.edu/˜musser/gp/pop/index.html. 1 Contents 1 Motivation 3 2 Standards Panel 4 3 Lectures 4 3.1 Foundations and Methodology Comparisons ........ 4 Fundamentals of Generic Programming.................. 4 Jim Dehnert and Alex Stepanov Automatic Program Specialization by Partial Evaluation........ 4 Robert Gl¨uck Evaluating Generic Programming in Practice............... 6 Mehdi Jazayeri Polytypic Programming........................... 6 Johan Jeuring Recasting Algorithms As Objects: AnAlternativetoIterators . 7 Murali Sitaraman Using Genericity to Improve OO Designs................. 8 Karsten Weihe Inheritance, Genericity, and Class Hierarchies.............. 8 Wolf Zimmermann 3.2 Programming Methodology ................... 9 Hierarchical Iterators and Algorithms................... 9 Matt Austern Generic Programming in C++: Matrix Case Study........... 9 Krzysztof Czarnecki Generative Programming: Beyond Generic Programming........ 10 Ulrich Eisenecker Generic Programming Using Adaptive and Aspect-Oriented Programming . -
A Classification and Comparison Framework for Software Architecture Description Languages
A Classification and Comparison Framework for Software Architecture Description Languages Neno Medvidovic Technical Report UCI-ICS-97-02 Department of Information and Computer Science University of California, Irvine Irvine, California 92697-3425 [email protected] February 1996 Abstract Software architectures shift the focus of developers from lines-of-code to coarser- grained architectural elements and their overall interconnection structure. Architecture description languages (ADLs) have been proposed as modeling notations to support architecture-based development. There is, however, little consensus in the research community on what is an ADL, what aspects of an architecture should be modeled in an ADL, and which of several possible ADLs is best suited for a particular problem. Furthermore, the distinction is rarely made between ADLs on one hand and formal specification, module interconnection, simulation, and programming languages on the other. This paper attempts to provide an answer to these questions. It motivates and presents a definition and a classification framework for ADLs. The utility of the definition is demonstrated by using it to differentiate ADLs from other modeling notations. The framework is also used to classify and compare several existing ADLs. One conclusion is that, although much research has been done in this area, no single ADL fulfills all of the identified needs. I. Introduction Software architecture research is directed at reducing costs of developing applications and increasing the potential for commonality between different members of a closely related product family [GS93, PW92]. Software development based on common architectural idioms has its focus shifted from lines-of-code to coarser-grained architectural elements (software components and connectors) and their overall interconnection structure. -
Data Types and Variables
Color profile: Generic CMYK printer profile Composite Default screen Complete Reference / Visual Basic 2005: The Complete Reference / Petrusha / 226033-5 / Chapter 2 2 Data Types and Variables his chapter will begin by examining the intrinsic data types supported by Visual Basic and relating them to their corresponding types available in the .NET Framework’s Common TType System. It will then examine the ways in which variables are declared in Visual Basic and discuss variable scope, visibility, and lifetime. The chapter will conclude with a discussion of boxing and unboxing (that is, of converting between value types and reference types). Visual Basic Data Types At the center of any development or runtime environment, including Visual Basic and the .NET Common Language Runtime (CLR), is a type system. An individual type consists of the following two items: • A set of values. • A set of rules to convert every value not in the type into a value in the type. (For these rules, see Appendix F.) Of course, every value of another type cannot always be converted to a value of the type; one of the more common rules in this case is to throw an InvalidCastException, indicating that conversion is not possible. Scalar or primitive types are types that contain a single value. Visual Basic 2005 supports two basic kinds of scalar or primitive data types: structured data types and reference data types. All data types are inherited from either of two basic types in the .NET Framework Class Library. Reference types are derived from System.Object. Structured data types are derived from the System.ValueType class, which in turn is derived from the System.Object class. -
Verification and Specification of Concurrent Programs
Verification and Specification of Concurrent Programs Leslie Lamport 16 November 1993 To appear in the proceedings of a REX Workshop held in The Netherlands in June, 1993. Verification and Specification of Concurrent Programs Leslie Lamport Digital Equipment Corporation Systems Research Center Abstract. I explore the history of, and lessons learned from, eighteen years of assertional methods for specifying and verifying concurrent pro- grams. I then propose a Utopian future in which mathematics prevails. Keywords. Assertional methods, fairness, formal methods, mathemat- ics, Owicki-Gries method, temporal logic, TLA. Table of Contents 1 A Brief and Rather Biased History of State-Based Methods for Verifying Concurrent Systems .................. 2 1.1 From Floyd to Owicki and Gries, and Beyond ........... 2 1.2Temporal Logic ............................ 4 1.3 Unity ................................. 5 2 An Even Briefer and More Biased History of State-Based Specification Methods for Concurrent Systems ......... 6 2.1 Axiomatic Specifications ....................... 6 2.2 Operational Specifications ...................... 7 2.3 Finite-State Methods ........................ 8 3 What We Have Learned ........................ 8 3.1 Not Sequential vs. Concurrent, but Functional vs. Reactive ... 8 3.2Invariance Under Stuttering ..................... 8 3.3 The Definitions of Safety and Liveness ............... 9 3.4 Fairness is Machine Closure ..................... 10 3.5 Hiding is Existential Quantification ................ 10 3.6 Specification Methods that Don’t Work .............. 11 3.7 Specification Methods that Work for the Wrong Reason ..... 12 4 Other Methods ............................. 14 5 A Brief Advertisement for My Approach to State-Based Ver- ification and Specification of Concurrent Systems ....... 16 5.1 The Power of Formal Mathematics ................. 16 5.2Specifying Programs with Mathematical Formulas ........ 17 5.3 TLA ................................. -
Static Typing Where Possible, Dynamic Typing When Needed: the End of the Cold War Between Programming Languages
Intended for submission to the Revival of Dynamic Languages Static Typing Where Possible, Dynamic Typing When Needed: The End of the Cold War Between Programming Languages Erik Meijer and Peter Drayton Microsoft Corporation Abstract Advocates of dynamically typed languages argue that static typing is too rigid, and that the softness of dynamically lan- This paper argues that we should seek the golden middle way guages makes them ideally suited for prototyping systems with between dynamically and statically typed languages. changing or unknown requirements, or that interact with other systems that change unpredictably (data and application in- tegration). Of course, dynamically typed languages are indis- 1 Introduction pensable for dealing with truly dynamic program behavior such as method interception, dynamic loading, mobile code, runtime <NOTE to="reader"> Please note that this paper is still very reflection, etc. much work in progress and as such the presentation is unpol- In the mother of all papers on scripting [16], John Ousterhout ished and possibly incoherent. Obviously many citations to argues that statically typed systems programming languages related and relevant work are missing. We did however do our make code less reusable, more verbose, not more safe, and less best to make it provocative. </NOTE> expressive than dynamically typed scripting languages. This Advocates of static typing argue that the advantages of static argument is parroted literally by many proponents of dynami- typing include earlier detection of programming mistakes (e.g. cally typed scripting languages. We argue that this is a fallacy preventing adding an integer to a boolean), better documenta- and falls into the same category as arguing that the essence of tion in the form of type signatures (e.g. -
The Specification Language TLA+
Leslie Lamport: The Speci¯cation Language TLA+ This is an addendum to a chapter by Stephan Merz in the book Logics of Speci¯cation Languages by Dines Bj¿rner and Martin C. Henson (Springer, 2008). It appeared in that book as part of a \reviews" chapter. Stephan Merz describes the TLA logic in great detail and provides about as good a description of TLA+ and how it can be used as is possible in a single chapter. Here, I give a historical account of how I developed TLA and TLA+ that explains some of the design choices, and I briefly discuss how TLA+ is used in practice. Whence TLA The logic TLA adds three things to the very simple temporal logic introduced into computer science by Pnueli [4]: ² Invariance under stuttering. ² Temporal existential quanti¯cation. ² Taking as atomic formulas not just state predicates but also action for- mulas. Here is what prompted these additions. When Pnueli ¯rst introduced temporal logic to computer science in the 1970s, it was clear to me that it provided the right logic for expressing the simple liveness properties of concurrent algorithms that were being considered at the time and for formalizing their proofs. In the early 1980s, interest turned from ad hoc properties of systems to complete speci¯cations. The idea of speci- fying a system as a conjunction of the temporal logic properties it should satisfy seemed quite attractive [5]. However, it soon became obvious that this approach does not work in practice. It is impossible to understand what a conjunction of individual properties actually speci¯es. -
Software II: Principles of Programming Languages
Software II: Principles of Programming Languages Lecture 6 – Data Types Some Basic Definitions • A data type defines a collection of data objects and a set of predefined operations on those objects • A descriptor is the collection of the attributes of a variable • An object represents an instance of a user- defined (abstract data) type • One design issue for all data types: What operations are defined and how are they specified? Primitive Data Types • Almost all programming languages provide a set of primitive data types • Primitive data types: Those not defined in terms of other data types • Some primitive data types are merely reflections of the hardware • Others require only a little non-hardware support for their implementation The Integer Data Type • Almost always an exact reflection of the hardware so the mapping is trivial • There may be as many as eight different integer types in a language • Java’s signed integer sizes: byte , short , int , long The Floating Point Data Type • Model real numbers, but only as approximations • Languages for scientific use support at least two floating-point types (e.g., float and double ; sometimes more • Usually exactly like the hardware, but not always • IEEE Floating-Point Standard 754 Complex Data Type • Some languages support a complex type, e.g., C99, Fortran, and Python • Each value consists of two floats, the real part and the imaginary part • Literal form real component – (in Fortran: (7, 3) imaginary – (in Python): (7 + 3j) component The Decimal Data Type • For business applications (money) -
Using Lamport Clocks to Reason About Relaxed Memory Models
Using Lamport Clocks to Reason About Relaxed Memory Models Anne E. Condon, Mark D. Hill, Manoj Plakal, Daniel J. Sorin Computer Sciences Department University of Wisconsin - Madison {condon,markhill,plakal,sorin}@cs.wisc.edu Abstract industrial product groups spend more time verifying their Cache coherence protocols of current shared-memory mul- system than actually designing and optimizing it. tiprocessors are difficult to verify. Our previous work pro- To verify a system, engineers should unambiguously posed an extension of Lamport’s logical clocks for showing define what “correct” means. For a shared-memory sys- that multiprocessors can implement sequential consistency tem, “correct” is defined by a memory consistency model. (SC) with an SGI Origin 2000-like directory protocol and a A memory consistency model defines for programmers the Sun Gigaplane-like split-transaction bus protocol. Many allowable behavior of hardware. A commonly-assumed commercial multiprocessors, however, implement more memory consistency model requires a shared-memory relaxed models, such as SPARC Total Store Order (TSO), a multiprocessor to appear to software as a multipro- variant of processor consistency, and Compaq (DEC) grammed uniprocessor. This model was formalized by Alpha, a variant of weak consistency. Lamport as sequential consistency (SC) [12]. Assume that This paper applies Lamport clocks to both a TSO and an each processor executes instructions and memory opera- Alpha implementation. Both implementations are based on tions in a dynamic execution order called program order. the same Sun Gigaplane-like split-transaction bus protocol An execution is SC if there exists a total order of memory we previously used, but the TSO implementation places a operations (reads and writes) in which (a) the program first-in-first-out write buffer between a processor and its orders of all processors are respected and (b) a read returns cache, while the Alpha implementation uses a coalescing the value of the last write (to the same address) in this write buffer.