Linguaggi Di Programmazione Non OOP

Total Page:16

File Type:pdf, Size:1020Kb

Linguaggi Di Programmazione Non OOP Ingegneria del Software Linguaggi di programmazione non OOP Barlini Davide-Carta Daniele-Casiero Fabio-Mascia Cristiano Abstract Scopo principale del lavoro è quello di riportare, nelle schede, una classificazione dei linguaggi di programmazione non orientati agli oggetti. Per far ciò, si è pensato di procedere gradualmente andando a focalizzare via via l’obiettivo. Si introduce il concetto di linguaggio di programmazione andando ad elencare le cinque diverse generazioni di evoluzione degli stessi. Cercando di fornire una classificazione accettabile, si discute dei paradigmi di programmazione citando il paradigma procedurale ed il paradigma dichiarativo e le loro ulteriori articolazioni. La classificazione riportata è successivamente arricchita da nuovi tipi come i “paralleli, concorrenti, distribuiti, applicativi, scripting, markup”. Per ognuno di essi si sono spese due parole di introduzione. Sono infine presentati i linguaggi trovati, ognuno dei quali ha una sua introduzione ed una scheda riassuntiva che ne individua la posizione nella classificazione proposta. 1 Indice Linguaggi di programmazione ......................................................................3 Generazioni ...................................................................................................4 Paradigma di programmazione ...................................................................5 Classificazione..............................................................................................7 I vari linguaggi................................................................................................ 15 Links nel web ................................................................................................ 37 Appendice: le schede.................................................................................... 42 2 Linguaggi di programmazione L'attività di un programmatore è quella di risolvere un problema sotto forma di algoritmo e di tradurlo in programma in un dato linguaggio1. Il termine algoritmo entrato in uso negli anni ’50 sostituì la parola algorismo, (processo di calcolare con i numeri arabi), derivato da una deformazione del nome di un matematico arabo Abu Ja’far Mohammed ibn Mˆ usˆ a al- Khowˆ arizmˆ ý (825 d. C.), ma la definizione del matematico Markov appare più appropriata. "L'insieme delle regole precise che definiscono un procedimento di calcolo destinato ad ottenere un risultato determinato a partire da dati iniziali certi". I linguaggi di programmazione costituiscono l'unico formalismo mediante il quale l'uomo può dialogare con i sistemi informatici, siano questi hardware che software. L'area dei linguaggi è in continua evoluzione e molto attiva anche dal punto di vista della ricerca poiché ogni nuova applicazione ed ogni nuova architettura (sia fisica che logica come il W.W.W.) pongono nuovi problemi e sfide ai progettisti che devono individuare i costrutti e le strutture più naturali per il tipo di problema che si vuole risolvere e per gestire e sfruttare in modo semplice le nuove tecnologie. L'aumento delle potenzialità degli strumenti di calcolo ha permesso il passaggio tra elaborazione numerica e simbolica e lo sviluppo di diverse famiglie di linguaggi di programmazione (imperativi, funzionali, logici). Ciascuna di queste può a sua volta essere utilizzata mediante diverse filosofie: sequenziale, concorrente, orientata agli oggetti. Dalla teoria dei linguaggi formali sono ereditate le tecniche automatiche che permettono di tradurre in modo equivalente il codice scritto in un dato linguaggio in un altro linguaggio (tipicamente di livello più "vicino" alla macchina). I LINGUAGGI DI PROGRAMMAZIONE Un linguaggio di programmazione è un insieme di simboli (alfabeto) e stringhe di simboli (vocabolario) che possono essere connessi tra loro seguendo regole formali predefinite e precise. Le regole per la costruzione delle frasi di un linguaggio sono espresse come produzioni di un sistema formale denominato grammatica. Le regole grammaticali descrivono solo come sono fatte le frasi di un linguaggio, cioè la sintassi, e di norma non descrivono il significato delle frasi. Le regole grammaticali devono essere concepite in modo da garantire la decidibilità del linguaggio. I programmatori inesperti tendono ad "aggrovigliare" il programma introducendo numerosi salti privi di regole (spaghetti programming). E' stato dimostrato (Teorema fondamentale della programmazione strutturata di Jacopini e Böhm) che ogni programma può essere codificato attenendosi esclusivamente a tre strutture fondamentali: 1. Sequenziale 2. Iterativa 3. Condizionale Queste tre strutture possono essere concatenate una di seguito all'altra oppure nidificate una dentro l'altra (non possono essere "intrecciate" o "accavallate"). Dopo aver scritto il sorgente attraverso un linguaggio di programmazione, è necessario che sia tradotto in codice binario. Tale azione può avvenire prima della fase vera e propria di esecuzione, come accade con il compilatore o durante la fase stessa di avanzamento, come accade con l'interprete. L'interprete traduce istruzione per istruzione dal codice sorgente al linguaggio macchina, mentre il compilatore traduce esattamente le istruzioni del programma sorgente nelle corrispondenti istruzioni in linguaggio macchina. 1 Secondo l’approccio procedurale, vedasi in PARADIGMA DI PROGRAMMAZIONE. 3 Il linguaggio macchina è diverso a seconda del microprocessore (il tipo di CPU) presente nel calcolatore, per cui i programmi eseguibili (in linguaggio macchina) sono strettamente dipendenti dalla piattaforma hardware (oltre che dal particolare sistema operativo adottato). GENERAZIONI Teoricamente si è dimostrato che tutti i linguaggi non banali sono, dal punto di vista della capacità computazionale, equivalenti; in pratica un programma scritto in un certo linguaggio può sempre essere codificato in qualsiasi altro linguaggio. Il linguaggio deve essere non troppo difficile da imparare, deve essere possibile creare applicazioni in tempi ragionevoli, deve produrre eseguibili efficienti. I linguaggi di programmazione sono un sottoinsieme di quelli formali, essi possono essere definiti come il mezzo che ci permette di comunicare al computer la sequenza di operazioni da effettuare per raggiungere un obiettivo prefissato. Una prima distinzione tra i linguaggi di programmazione possiamo farla tra i linguaggi a basso e quelli ad alto livello. In genere si parla di programmazione a basso livello quando si utilizza un linguaggio molto vicino al funzionamento interno della macchina, mentre di programmazione di alto livello quando si utilizzano linguaggi più sofisticati ed astratti, slegati dal funzionamento fisico dello stesso elaboratore. Si viene così a creare una gerarchia di linguaggi, dai meno evoluti (il linguaggio macchina e l'assembler) a quelli più evoluti (PASCAL, FORTRAN, COBOL, PERL); I linguaggi di alto livello sono simili (esistono delle differenze) tra piattaforme differenti. Un grande problema è la portabilità del software da un piattaforma ad un'altra: Ø se le piattaforme sono uguali o compatibili si potrà distribuire il programma in formato eseguibile; Ø se le piattaforme sono incompatibili si dovrà distribuire il programma in formato sorgente. Si parla di “Generazioni di Linguaggi di Programmazione” col tacito consenso che un linguaggio di, p.es., terza generazione deve per forza essere “migliore” di uno di seconda: o I generazione: vi appartengono i cosiddetti linguaggi macchina espressi con sequenza di zeri e uni (es : 001011011011). Sono fortemente dipendenti dal particolare computer, infatti ogni processore utilizza un suo diverso linguaggio macchina. o II generazione è rappresentata dal cosiddetto linguaggio assembler , che sostituisce le sequenze binarie del linguaggio della prima generazione con lettere dell'alfabeto e numeri esadecimali (es : ADD 235H). Anche questo tipo di linguaggio rimane comunque molto dipendente dal tipo di processore e sempre di difficile comprensione per il programmatore. o III generazione sono linguaggi ad alto livello che godono di una certa indipendenza dal processore ( FORTRAN, COBOL, C, PASCAL ). All'interno di questa generazione si sono create alcune tendenze partite da linguaggi non molto strutturati a linguaggi più evoluti; tali linguaggi usano delle variabili per indicare la zona di memoria. o IV generazione - caratterizzati da una somiglianza ancora più spinta con il linguaggio naturale, la minore rigidità formale, l'uso di un'interfaccia utente- elaboratore più trasparente dei compilatori. Sono metalinguaggi che usano un insieme di programmi o altri metaprogrammi integrati in un tutto armonico e funzionale a certi scopi ristretti: Shell di UNIX, FORTH, ecc. 4 o V generazione - vi appartengono i linguaggi per l'intelligenza artificiale, sono quelli più vicini al linguaggio del programmatore (es: PROLOG). Generalmente, quando si parla di linguaggi di programmazione, si intende quelli di III generazione. Sembra che vi siano stati tre ambienti originanti, che hanno avuto pochi successi e molti fallimenti: o ambiente universitario tecnico/matematico: FORTRAN, ma anche ALGOL o ambiente universitario informatico: C, ma anche LISP, SNOBOL o comitati commerciali e militari: COBOL, ma anche PL/1. Sulla base dell'ambito in cui è necessario risolvere il problema di programmazione, è opportuno adottare un linguaggio piuttosto che un altro: Ø Calcolo scientifico: FORTRAN, C Ø Intelligenza Artificiale: PROLOG, LISP Ø Applicazioni gestionali: COBOL, SQL, C Ø Sistemi, device driver: ASSEMBLER,
Recommended publications
  • The Effect of Compression and Expansion on Stochastic Reaction Networks
    IMT School for Advanced Studies, Lucca Lucca, Italy The Effect of Compression and Expansion on Stochastic Reaction Networks PhD Program in Institutions, Markets and Technologies Curriculum in Computer Science and Systems Engineering (CSSE) XXXI Cycle By Tabea Waizmann 2021 The dissertation of Tabea Waizmann is approved. Program Coordinator: Prof. Rocco De Nicola, IMT Lucca Supervisor: Prof. Mirco Tribastone, IMT Lucca The dissertation of Tabea Waizmann has been reviewed by: Dr. Catia Trubiani, Gran Sasso Science Institute Prof. Michele Loreti, University of Camerino IMT School for Advanced Studies, Lucca 2021 To everyone who believed in me. Contents List of Figures ix List of Tables xi Acknowledgements xiii Vita and Publications xv Abstract xviii 1 Introduction 1 2 Background 6 2.1 Multisets . .6 2.2 Reaction Networks . .7 2.3 Ordinary Lumpability . 11 2.4 Layered Queuing Networks . 12 2.5 PEPA . 16 3 Coarse graining mass-action stochastic reaction networks by species equivalence 19 3.1 Species Equivalence . 20 3.1.1 Species equivalence as a generalization of Markov chain ordinary lumpability . 27 3.1.2 Characterization of SE for mass-action networks . 27 3.1.3 Computation of the maximal SE and reduced net- work . 28 vii 3.2 Applications . 31 3.2.1 Computational systems biology . 31 3.2.2 Epidemic processes in networks . 33 3.3 Discussion . 36 4 DiffLQN: Differential Equation Analysis of Layered Queuing Networks 37 4.1 DiffLQN .............................. 38 4.1.1 Architecture . 38 4.1.2 Capabilities . 38 4.1.3 Syntax . 39 4.2 Case Study: Client-Server dynamics . 41 4.3 Discussion .
    [Show full text]
  • Type Checking Physical Frames of Reference for Robotic Systems
    PhysFrame: Type Checking Physical Frames of Reference for Robotic Systems Sayali Kate Michael Chinn Hongjun Choi Purdue University University of Virginia Purdue University USA USA USA [email protected] [email protected] [email protected] Xiangyu Zhang Sebastian Elbaum Purdue University University of Virginia USA USA [email protected] [email protected] ABSTRACT Engineering (ESEC/FSE ’21), August 23–27, 2021, Athens, Greece. ACM, New A robotic system continuously measures its own motions and the ex- York, NY, USA, 16 pages. https://doi.org/10.1145/3468264.3468608 ternal world during operation. Such measurements are with respect to some frame of reference, i.e., a coordinate system. A nontrivial 1 INTRODUCTION robotic system has a large number of different frames and data Robotic systems have rapidly growing applications in our daily life, have to be translated back-and-forth from a frame to another. The enabled by the advances in many areas such as AI. Engineering onus is on the developers to get such translation right. However, such systems becomes increasingly important. Due to the unique this is very challenging and error-prone, evidenced by the large characteristics of such systems, e.g., the need of modeling the phys- number of questions and issues related to frame uses on developers’ ical world and satisfying the real time and resource constraints, forum. Since any state variable can be associated with some frame, robotic system engineering poses new challenges to developers. reference frames can be naturally modeled as variable types. We One of the prominent challenges is to properly use physical frames hence develop a novel type system that can automatically infer of reference.
    [Show full text]
  • Dynamic Extension of Typed Functional Languages
    Dynamic Extension of Typed Functional Languages Don Stewart PhD Dissertation School of Computer Science and Engineering University of New South Wales 2010 Supervisor: Assoc. Prof. Manuel M. T. Chakravarty Co-supervisor: Dr. Gabriele Keller Abstract We present a solution to the problem of dynamic extension in statically typed functional languages with type erasure. The presented solution re- tains the benefits of static checking, including type safety, aggressive op- timizations, and native code compilation of components, while allowing extensibility of programs at runtime. Our approach is based on a framework for dynamic extension in a stat- ically typed setting, combining dynamic linking, runtime type checking, first class modules and code hot swapping. We show that this framework is sufficient to allow a broad class of dynamic extension capabilities in any statically typed functional language with type erasure semantics. Uniquely, we employ the full compile-time type system to perform run- time type checking of dynamic components, and emphasize the use of na- tive code extension to ensure that the performance benefits of static typing are retained in a dynamic environment. We also develop the concept of fully dynamic software architectures, where the static core is minimal and all code is hot swappable. Benefits of the approach include hot swappable code and sophisticated application extension via embedded domain specific languages. We instantiate the concepts of the framework via a full implementation in the Haskell programming language: providing rich mechanisms for dy- namic linking, loading, hot swapping, and runtime type checking in Haskell for the first time. We demonstrate the feasibility of this architecture through a number of novel applications: an extensible text editor; a plugin-based network chat bot; a simulator for polymer chemistry; and xmonad, an ex- tensible window manager.
    [Show full text]
  • Introduction to the Literature on Programming Language Design Gary T
    Computer Science Technical Reports Computer Science 7-1999 Introduction to the Literature On Programming Language Design Gary T. Leavens Iowa State University Follow this and additional works at: http://lib.dr.iastate.edu/cs_techreports Part of the Programming Languages and Compilers Commons Recommended Citation Leavens, Gary T., "Introduction to the Literature On Programming Language Design" (1999). Computer Science Technical Reports. 59. http://lib.dr.iastate.edu/cs_techreports/59 This Article is brought to you for free and open access by the Computer Science at Iowa State University Digital Repository. It has been accepted for inclusion in Computer Science Technical Reports by an authorized administrator of Iowa State University Digital Repository. For more information, please contact [email protected]. Introduction to the Literature On Programming Language Design Abstract This is an introduction to the literature on programming language design and related topics. It is intended to cite the most important work, and to provide a place for students to start a literature search. Keywords programming languages, semantics, type systems, polymorphism, type theory, data abstraction, functional programming, object-oriented programming, logic programming, declarative programming, parallel and distributed programming languages Disciplines Programming Languages and Compilers This article is available at Iowa State University Digital Repository: http://lib.dr.iastate.edu/cs_techreports/59 Intro duction to the Literature On Programming Language Design Gary T. Leavens TR 93-01c Jan. 1993, revised Jan. 1994, Feb. 1996, and July 1999 Keywords: programming languages, semantics, typ e systems, p olymorphism, typ e theory, data abstrac- tion, functional programming, ob ject-oriented programming, logic programming, declarative programming, parallel and distributed programming languages.
    [Show full text]
  • Incremental Type Inference for Software Engineering
    Incremental Type Inference for Software Engineering Jonathan Aldrich University of Washington [email protected] Abstract The desire to use high-level language constructs while Software engineering focused type inference can enhance preserving a static type-safe guarantee drives programmer productivity in statically typed object- programmers to ask for ever-more powerful type systems. oriented languages. Type inference is a system of However, specifying a type that may be almost as long automatically inferring the argument and return types of and complicated as the function it describes can be a function. It provides considerable programming impractical. convenience, because the programmer can realize the benefits of a statically typed language without manually 1.2. Type Inference in ML entering the type annotations. We study the problem of type inference in object-oriented languages and propose In ML, it is possible for the compiler to analyze the an incremental, programmer-aided approach. Code is body of a function and infer the type of that function. For added one method at a time and missing types are example, a function that squares each of its arguments and inferred if possible. We present a specification and returns the sum of the squares clearly takes several algorithm for inferring simple object-oriented types in arguments of type int and yields an int in return (see this kind of incremental development environment. figure 1). - fun sumsqrs (x, y) = x*x + y*y; 1. Introduction val sumsqrs = fn : int * int -> int Type inference was popularized by the ML language [Milner et al., 1990]. ML is made up of functions and Figure 1.
    [Show full text]
  • Luca Cardelli • Curriculum Vitae • 2014
    Luca Cardelli • Curriculum Vitae • 2014 Short Bio Luca Cardelli was born near Montecatini Terme, Italy, studied at the University of Pisa (until 1978-07- 12), and has a Ph.D. in computer science from the University of Edinburgh(1982-04-01). He worked at Bell Labs, Murray Hill, from 1982-04-05 to 1985-09-20, and at Digital Equipment Corporation, Systems Research Center in Palo Alto, from 1985-09-30 to 1997-10-31, before assuming a position on 1997-11-03 at Microsoft Research, in Cambridge UK, where he was head of the Programming Principles and Tools andSecurity groups until 2012, and is currently a Principal Researcher. His main interests are in type theory and operational semantics (for applications to language design, semantics, and implementation), and in concurrency theory (for applications to computer networks and to modeling biological systems). He implemented the first compiler for ML (one of the most popular typed functional language, whose recent incarnations are Caml and F#) and one of the earliest direct-manipulation user-interface editors. He was a member of the Modula-3 design committee, and has designed a few experimental languages, including Obliq: a distributed higher- order scripting language (voted most influential POPL'95 paper 10 years later), and Polyphonic C#, a distributed extension of C#. His more protracted research activity has been in establishing the semantic and type-theoretic foundations of object-oriented languages, resulting in the 1996 book "A Theory of Objects" with Martin Abadi. More recently he has focused on modeling global and mobile computation, via the Ambient Calculus andSpatial Logics, which indirectly led to a current interest in Systems Biology , Molecular Programming, and Stochastic Systems.
    [Show full text]
  • An Imperative Object Calculus
    An Imperative Object Calculus Mart’n Abadi and Luca Cardelli Digital Equipment Corporation, Systems Research Center Abstract. We develop an imperative calculus of objects. Its main type con- structor is the one for object types, which incorporate variance annotations and Self types. A subtyping relation between object types supports object subsumption. The type system for objects relies on unusual but beneficial as- sumptions about the possible subtypes of an object type. With the addition of polymorphism, the calculus can express classes and inheritance. 1 Introduction Object calculi are formalisms at the same level of abstraction as λ-calculi, but based exclusively on objects rather than functions. Unlike λ-calculi, object calculi are de- signed specifically for clarifying features of object-oriented languages. There is a wide spectrum of relevant object calculi, just as there is a wide spectrum of λ-calculi. One can investigate untyped, simply-typed, and polymorphic calculi, as well as functional and imperative calculi. In object calculi, as in λ-calculi, a small untyped kernel is enriched with derived constructions and with increasingly sophisticated type systems, until language fea- tures can be realistically modeled. The compactness of the initial kernel gives concep- tual unity to the calculi, and enables formal analysis. In this paper we introduce a tiny but expressive imperative calculus. It provides a minimal setting in which to study the imperative operational semantics and the deli- cate typing rules of practical object-oriented languages. The calculus comprises objects, method invocation, method update, object cloning, and local definitions. In a quest for minimality, we take objects to be just collections of methods.
    [Show full text]
  • Exact Maximal Reduction of Stochastic Reaction Networks by Species
    Bioinformatics, 2021, 1–8 doi: 10.1093/bioinformatics/btab081 Advance Access Publication Date: 3 February 2021 Original Paper Downloaded from https://academic.oup.com/bioinformatics/advance-article/doi/10.1093/bioinformatics/btab081/6126804 by DTU Library user on 06 July 2021 Systems Biology Exact maximal reduction of stochastic reaction networks by species lumping Luca Cardelli,1 Isabel Cristina Perez-Verona,2 Mirco Tribastone ,2,* Max Tschaikowski,3 Andrea Vandin 4 and Tabea Waizmann2 1Department of Computer Science, University of Oxford, Oxford 34127, OX1 3QD, UK, 2IMT School for Advanced Studies, Lucca 55100, Italy, 3Department of Computer Science, University of Aalborg, Aalborg 34127, 9220, Denmark and 4Sant’Anna School of Advanced Studies, Pisa 56127, Italy *To whom correspondence should be addressed. Associtate Editor: Alfonso Valencia Received on October 16, 2020; revised on January 9, 2021; editorial decision on January 27, 2021; accepted on January 28, 2021 Abstract Motivation: Stochastic reaction networks are a widespread model to describe biological systems where the pres- ence of noise is relevant, such as in cell regulatory processes. Unfortunately, in all but simplest models the resulting discrete state-space representation hinders analytical tractability and makes numerical simulations expensive. Reduction methods can lower complexity by computing model projections that preserve dynamics of interest to the user. Results: We present an exact lumping method for stochastic reaction networks with mass-action kinetics. It hinges on an equivalence relation between the species, resulting in a reduced network where the dynamics of each macro- species is stochastically equivalent to the sum of the original species in each equivalence class, for any choice of the initial state of the system.
    [Show full text]
  • Two-Domain DNA Strand Displacement
    Two-Domain DNA Strand Displacement Luca Cardelli Microsoft Research Cambridge, UK [email protected] We investigate the computing power of a restricted class of DNA strand displacement structures: those that are made of double strands with nicks (interruptions) in the top strand. To preserve this structural invariant, we impose restrictions on the single strands they interact with: we consider only two-domain single strands consisting of one toehold domain and one recognition domain. We study fork and join signal-processing gates based on these structures, and we show that these systems are amenable to formalization and to mechanical verification. 1 Introduction Among the many techniques being developed for molecular computing [5], DNA strand displacement has been proposed as mechanism for performing computation with DNA strands [8, 3]. In most schemes, single-stranded DNA acts as signals and double-stranded (or more complex) DNA structures act as gates. Various circuits have been demonstrated experimentally [10]. The strand displacement mechanism is appealing because it is autonomous [4]: once signals and gates are mixed together, computation proceeds on its own without further intervention until the gates or signals are depleted (output is often read by fluorescence). The energy for computation is provided by the gate structures themselves, which are turned into inactive waste in the process. Moreover, the mechanism requires only DNA molecules: no organic sources, enzymes, or transcription/translation ingredients are required, and the whole apparatus can be chemically synthesized and run in basic wet labs. The main aims of this approach are to harness computational mechanisms that can operate at the molecular level and produce nano-scale structures under program control, and somewhat separately that can intrinsically interface to biological entities [2].
    [Show full text]
  • Type Systems.Fm
    Type Systems Luca Cardelli Microsoft Research 1 Introduction The fundamental purpose of a type system is to prevent the occurrence of execution errors dur- ing the running of a program. This informal statement motivates the study of type systems, but requires clarification. Its accuracy depends, first of all, on the rather subtle issue of what consti- tutes an execution error, which we will discuss in detail. Even when that is settled, the absence of execution errors is a nontrivial property. When such a property holds for all of the program runs that can be expressed within a programming language, we say that the language is type sound. It turns out that a fair amount of careful analysis is required to avoid false and embar- rassing claims of type soundness for programming languages. As a consequence, the classifica- tion, description, and study of type systems has emerged as a formal discipline. The formalization of type systems requires the development of precise notations and defi- nitions, and the detailed proof of formal properties that give confidence in the appropriateness of the definitions. Sometimes the discipline becomes rather abstract. One should always remem- ber, though, that the basic motivation is pragmatic: the abstractions have arisen out of necessity and can usually be related directly to concrete intuitions. Moreover, formal techniques need not be applied in full in order to be useful and influential. A knowledge of the main principles of type systems can help in avoiding obvious and not so obvious pitfalls, and can inspire regularity and orthogonality in language design. When properly developed, type systems provide conceptual tools with which to judge the adequacy of important aspects of language definitions.
    [Show full text]
  • The Early History of F
    The Early History of F# DON SYME, Microsoft, United Kingdom Shepherd: Philip Wadler, University of Edinburgh, UK This paper describes the genesis and early history of the F# programming language. I start with the origins of strongly-typed functional programming (FP) in the 1970s, 80s and 90s. During the same period, Microsoft was founded and grew to dominate the software industry. In 1997, as a response to Java, Microsoft initiated internal projects which eventually became the .NET programming framework and the C# language. From 1997 the worlds of academic functional programming and industry combined at Microsoft Research, Cambridge. The researchers engaged with the company through Project 7, the initial effort to bring multiple languages to .NET, leading to the initiation of .NET Generics in 1998 and F# in 2002. F# was one of several responses by advocates of strongly-typed functional programming to the “object-oriented tidal wave” of the mid-1990s. The 75 development of the core features of F# 1.0 happened from 2004-2007, and I describe the decision-making process that led to the “productization” of F# by Microsoft in 2007-10 and the release of F# 2.0. The origins of F#’s characteristic features are covered: object programming, quotations, statically resolved type parameters, active patterns, computation expressions, async, units-of-measure and type providers. I describe key developments in F# since 2010, including F# 3.0-4.5, and its evolution as an open source, cross-platform language with multiple delivery channels. I conclude by examining some uses of F# and the influence F# has had on other languages so far.
    [Show full text]
  • Mobility and Security
    Mobility and Security Luca Cardelli Microsoft Research Lecture Notes for the Marktoberdorf Summer School 1999, from works by Luca Cardelli and Andrew D. Gordon Abstract. We discuss the computational aspects of wide area networks, and we describe var- ious facets of a process calculus devised to embody mobility, security, and wide area network semantics. These lecture notes are an abridged version of [8, 11, 27, 12, 13]. Part I: Wide Area Computation 1 Introduction The Internet and the World-Wide-Web provide a computational infrastructure that spans the planet. It is appealing to imagine writing programs that exploit this global infrastructure. Un- fortunately, the Web violates many familiar assumptions about the behavior of distributed systems, and demands novel and specialized programming techniques. In particular, three phenomena that remain largely hidden in local area network architectures become readily ob- servable on the Web: • (A) Virtual locations. Because of the presence of potential attackers, barriers are erect- ed between mutually distrustful administrative domains. Therefore, a program must be aware of where it is, and of how to move or communicate between different domains. The existence of separate administrative domains induces a notion of virtual locations and of virtual distance between locations. • (B) Physical locations. On a planet-size structure, the speed of light becomes tangible. For example, a procedure call to the antipodes requires at least 1/10 of a second, inde- pendently of future improvements in networking technology. This absolute lower bound to latency induces a notion of physical locations and physical distance between locations. • (C) Bandwidth fluctuations. A global network is susceptible to unpredictable conges- tion and partitioning, which result in fluctuations or temporary interruptions of band- width.
    [Show full text]