SDL - the Iot Language Edel Sherratt, Ileana Ober, Emmanuel Gaudin, Pau Fonseca I Casas, Finn Kristoffersen
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Chapter 1 Introduction to Computers, Programs, and Java
Chapter 1 Introduction to Computers, Programs, and Java 1.1 Introduction • The central theme of this book is to learn how to solve problems by writing a program . • This book teaches you how to create programs by using the Java programming languages . • Java is the Internet program language • Why Java? The answer is that Java enables user to deploy applications on the Internet for servers , desktop computers , and small hand-held devices . 1.2 What is a Computer? • A computer is an electronic device that stores and processes data. • A computer includes both hardware and software. o Hardware is the physical aspect of the computer that can be seen. o Software is the invisible instructions that control the hardware and make it work. • Computer programming consists of writing instructions for computers to perform. • A computer consists of the following hardware components o CPU (Central Processing Unit) o Memory (Main memory) o Storage Devices (hard disk, floppy disk, CDs) o Input/Output devices (monitor, printer, keyboard, mouse) o Communication devices (Modem, NIC (Network Interface Card)). Bus Storage Communication Input Output Memory CPU Devices Devices Devices Devices e.g., Disk, CD, e.g., Modem, e.g., Keyboard, e.g., Monitor, and Tape and NIC Mouse Printer FIGURE 1.1 A computer consists of a CPU, memory, Hard disk, floppy disk, monitor, printer, and communication devices. CMPS161 Class Notes (Chap 01) Page 1 / 15 Kuo-pao Yang 1.2.1 Central Processing Unit (CPU) • The central processing unit (CPU) is the brain of a computer. • It retrieves instructions from memory and executes them. -
Attachment A
Board of Governors, State University System of Florida Request to Offer a New Degree Program (Please do not revise this proposal format without prior approval from Board staff) University of West Florida Fall 2018 University Submitting Proposal Proposed Implementation Term Hal Marcus College of Science and Engineering Computer Science Name of College(s) or School(s) Name of Department(s)/ Division(s) Bachelor of Science in Computer Computer Science Science Academic Specialty or Field Complete Name of Degree 11.0701 Proposed CIP Code The submission of this proposal constitutes a commitment by the university that, if the proposal is approved, the necessary financial resources and the criteria for establishing new programs have been met prior to the initiation of the program. Date Approved by the University Board of President Date Trustees Signature of Chair, Board of Date Provost and Senior Vice Date Trustees President Provide headcount (HC) and full-time equivalent (FTE) student estimates of majors for Years 1 through 5. HC and FTE estimates should be identical to those in Table 1 in Appendix A. Indicate the program costs for the first and the fifth years of implementation as shown in the appropriate columns in Table 2 in Appendix A. Calculate an Educational and General (E&G) cost per FTE for Years 1 and 5 (Total E&G divided by FTE). Projected Implementation Projected Program Costs Enrollment Timeframe (From Table 2) (From Table 1) E&G Contract E&G Auxiliary Total HC FTE Cost per & Grants Funds Funds Cost FTE Funds Year 1 150 96.87 3,241 313,960 0 0 313,960 Year 2 150 96.87 Year 3 160 103.33 Year 4 160 103.33 Year 5 170 109.79 3,426 376,087 0 0 376,087 1 Note: This outline and the questions pertaining to each section must be reproduced within the body of the proposal to ensure that all sections have been satisfactorily addressed. -
The Circle Meta-Model
Document:P2062R0 Revises: (original) Date: 01-11-2020 Audience: SG7 Authors: Wyatt Childers ([email protected]) Andrew Sutton ([email protected]) Faisal Vali ([email protected]) Daveed Vandevoorde ([email protected]) The Circle Meta-model Introduction During the November 2019 meeting in Belfast, some of the SG7 participants enthusiastically mentioned Circle1 as providing a more intuitive compile-time programming model and suggested that SG7 investigate overhauling the de-facto SG7 approach (P1240+P17332) to follow Circle's general approach (to reflection and metaprogramming). This paper describes a framework for understanding metaprogramming systems and provides a high-level overview of some of Circle's main characteristics, contrasting them to P1240's approach augmented with an injection mechanism along the lines of P1717. While we appreciate some of Circle’s powerful capabilities, we also raise some concerns with its underlying model and provide arguments in support of P1240’s choices as being a more suitable fit for C++’s evolution. The Dimensions of Reflective Programming In P0633, we identified three “dimensions” of compile-time reflective metaprogramming: 1. Control: How are compile-time computations effected/interpreted? What are metaprograms? 2. Reflection: How are source constructs are made available as data for use in metaprograms? 3. Synthesis: How can “code” be generated from a programmatic representation? 1 https://www.circle-lang.org/ Circle is an impressive project: Sean Baxter developed a brand new C++17-like front end on top of LLVM, incorporating a variety of new compile-time capabilities that align closely with SG7's goals. For Sean’s motivations, see https://github.com/seanbaxter/circle/blob/master/examples/README.md#why-i-wrote-circle. -
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 . -
Sub-Method Structural and Behavioral Reflection Marcus Denker
Sub-method Structural and Behavioral Reflection Marcus Denker To cite this version: Marcus Denker. Sub-method Structural and Behavioral Reflection. Computer Science [cs]. Universität Bern, 2008. English. tel-00555937 HAL Id: tel-00555937 https://tel.archives-ouvertes.fr/tel-00555937 Submitted on 14 Jan 2011 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. Sub-method Structural and Behavioral Reflection Inauguraldissertation der Philosophisch-naturwissenschaftlichen Fakultät der Universität Bern vorgelegt von Marcus Denker von Deutschland Leiter der Arbeit: Prof. Dr. O. Nierstrasz Institut für Informatik und angewandte Mathematik Von der Philosophisch-naturwissenschaftlichen Fakultät angenommen. Bern, 26.05.2008 Der Dekan: Prof. Dr. P. Messerli This dissertation is available as a free download from http://scg.unibe.ch Copyright © 2008 Marcus Denker. The contents of this dissertation are protected under Creative Commons Attribution-ShareAlike 3.0 Unported license. You are free: to Share — to copy, distribute and transmit the work to Remix — to adapt the work Under the following conditions: Attribution. You must attribute the work in the manner specified by the author or licensor (but not in any way that suggests that they endorse you or your use of the work). -
Language Translators
Student Notes Theory LANGUAGE TRANSLATORS A. HIGH AND LOW LEVEL LANGUAGES Programming languages Low – Level Languages High-Level Languages Example: Assembly Language Example: Pascal, Basic, Java Characteristics of LOW Level Languages: They are machine oriented : an assembly language program written for one machine will not work on any other type of machine unless they happen to use the same processor chip. Each assembly language statement generally translates into one machine code instruction, therefore the program becomes long and time-consuming to create. Example: 10100101 01110001 LDA &71 01101001 00000001 ADD #&01 10000101 01110001 STA &71 Characteristics of HIGH Level Languages: They are not machine oriented: in theory they are portable , meaning that a program written for one machine will run on any other machine for which the appropriate compiler or interpreter is available. They are problem oriented: most high level languages have structures and facilities appropriate to a particular use or type of problem. For example, FORTRAN was developed for use in solving mathematical problems. Some languages, such as PASCAL were developed as general-purpose languages. Statements in high-level languages usually resemble English sentences or mathematical expressions and these languages tend to be easier to learn and understand than assembly language. Each statement in a high level language will be translated into several machine code instructions. Example: number:= number + 1; 10100101 01110001 01101001 00000001 10000101 01110001 B. GENERATIONS OF PROGRAMMING LANGUAGES 4th generation 4GLs 3rd generation High Level Languages 2nd generation Low-level Languages 1st generation Machine Code Page 1 of 5 K Aquilina Student Notes Theory 1. MACHINE LANGUAGE – 1ST GENERATION In the early days of computer programming all programs had to be written in machine code. -
Complete Code Generation from UML State Machine
Complete Code Generation from UML State Machine Van Cam Pham, Ansgar Radermacher, Sebastien´ Gerard´ and Shuai Li CEA, LIST, Laboratory of Model Driven Engineering for Embedded Systems, P.C. 174, Gif-sur-Yvette, 91191, France Keywords: UML State Machine, Code Generation, Semantics-conformance, Efficiency, Events, C++. Abstract: An event-driven architecture is a useful way to design and implement complex systems. The UML State Machine and its visualizations are a powerful means to the modeling of the logical behavior of such an archi- tecture. In Model Driven Engineering, executable code can be automatically generated from state machines. However, existing generation approaches and tools from UML State Machines are still limited to simple cases, especially when considering concurrency and pseudo states such as history, junction, and event types. This paper provides a pattern and tool for complete and efficient code generation approach from UML State Ma- chine. It extends IF-ELSE-SWITCH constructions of programming languages with concurrency support. The code generated with our approach has been executed with a set of state-machine examples that are part of a test-suite described in the recent OMG standard Precise Semantics Of State Machine. The traced execution results comply with the standard and are a good hint that the execution is semantically correct. The generated code is also efficient: it supports multi-thread-based concurrency, and the (static and dynamic) efficiency of generated code is improved compared to considered approaches. 1 INTRODUCTION Completeness: Existing tools and approaches mainly focus on the sequential aspect while the concurrency The UML State Machine (USM) (Specification and of state machines is limitedly supported. -
Chapter 1 Introduction to Computers, Programs, and Java
Chapter 1 Introduction to Computers, Programs, and Java 1.1 Introduction • Java is the Internet program language • Why Java? The answer is that Java enables user to deploy applications on the Internet for servers, desktop computers, and small hand-held devices. 1.2 What is a Computer? • A computer is an electronic device that stores and processes data. • A computer includes both hardware and software. o Hardware is the physical aspect of the computer that can be seen. o Software is the invisible instructions that control the hardware and make it work. • Programming consists of writing instructions for computers to perform. • A computer consists of the following hardware components o CPU (Central Processing Unit) o Memory (Main memory) o Storage Devices (hard disk, floppy disk, CDs) o Input/Output devices (monitor, printer, keyboard, mouse) o Communication devices (Modem, NIC (Network Interface Card)). Memory Disk, CD, and Storage Input Keyboard, Tape Devices Devices Mouse CPU Modem, and Communication Output Monitor, NIC Devices Devices Printer FIGURE 1.1 A computer consists of a CPU, memory, Hard disk, floppy disk, monitor, printer, and communication devices. 1.2.1 Central Processing Unit (CPU) • The central processing unit (CPU) is the brain of a computer. • It retrieves instructions from memory and executes them. • The CPU usually has two components: a control Unit and Arithmetic/Logic Unit. • The control unit coordinates the actions of the other components. • The ALU unit performs numeric operations (+ - / *) and logical operations (comparison). • The CPU speed is measured by clock speed in megahertz (MHz), with 1 megahertz equaling 1 million pulses per second. -
Directly Reflective Meta-Programming
Directly Reflective Meta-Programming ∗ Aaron Stump Computer Science and Engineering Washington University in St. Louis St. Louis, Missouri, USA [email protected] Abstract Existing meta-programming languages operate on encodings of pro- grams as data. This paper presents a new meta-programming language, based on an untyped lambda calculus, in which structurally reflective pro- gramming is supported directly, without any encoding. The language fea- tures call-by-value and call-by-name lambda abstractions, as well as novel reflective features enabling the intensional manipulation of arbitrary pro- gram terms. The language is scope safe, in the sense that variables can neither be captured nor escape their scopes. The expressiveness of the language is demonstrated by showing how to implement quotation and evaluation operations, as proposed by Wand. The language's utility for meta-programming is further demonstrated through additional represen- tative examples. A prototype implementation is described and evaluated. Keywords: lambda calculus, reflection, meta-programming, Church en- coding, Mogensen-Scott encoding, Wand-style fexprs, alpha equivalence, language implementation. 1 Introduction This paper presents a new meta-programming language called Archon, in which programs can operate directly on other programs as data. Existing meta- programming languages suffer from defects such as encoding programs at too low a level of abstraction, or in a way that bloats the encoded program terms. Other issues include the possibility for variables either to be captured or escape their static scopes. Archon rectifies these defects by trading the complexity of the reflective encoding for additional programming constructs. We adopt ∗This work is supported by funding from the U.S. -
[Lirmm-00862477, V1] Bridging the Gap Between Component-Based Design and Implementation with a Reflective Programming Language
Design and Implementation of a reflective Component-based programming and modeling language Bridging the Gap between Component-based Design and Implementation with a Reflective Programming Language Petr Spacek Christophe Dony Luc Fabresse Chouki Tibermacine Universite´ Lille Nord de France LIRMM, CNRS and Montpellier II University Ecole des Mines de Douai 161, rue Ada 941 rue Charles Bourseul 34392 Montpellier Cedex 5 France 59508 DOUAI Cedex France spacek,dony,tibermacin @lirmm.fr [email protected] { } Abstract General Terms Languages, Reflection, Metamodeling Component-based Software Engineering studies the design, Keywords Component, Programming, Modeling, Archi- development and maintenance of software constructed upon tecture, Reflection, Reflexive, Meta-model, Constraints, sets of connected components. Existing component-based Transformations models are frequently transformed into non-component- based programs, most of the time object-oriented, for run- time execution and then many component-related concepts, 1. Introduction e.g. explicit architecture, vanish at the implementation stage. Research works on component-based software engineering The main reason why is that with objects the component- (CBSE) have brought many advances on how to achieve related concepts are treated implicitly and therefore the orig- complex software development by reusing and assembling inal intentions and qualities of the component-based design components. The current trend is to explicitly express ar- are hidden. This paper presents a reflective component-based chitectures of software solutions, to reason about them, to programming and modeling language, which proposes the verify them and to transform them. However it appears following original contributions: 1) Components are seen that component-orientation has been more studied at de- as objects in which requirements, architecture descriptions, sign stage, with modeling languages and ADLs [10, 16, 22] connection points, etc. -
Open Programming Language Interpreters
Open Programming Language Interpreters Walter Cazzolaa and Albert Shaqiria a Università degli Studi di Milano, Italy Abstract Context: This paper presents the concept of open programming language interpreters, a model to support them and a prototype implementation in the Neverlang framework for modular development of programming languages. Inquiry: We address the problem of dynamic interpreter adaptation to tailor the interpreter’s behaviour on the task to be solved and to introduce new features to fulfil unforeseen requirements. Many languages provide a meta-object protocol (MOP) that to some degree supports reflection. However, MOPs are typically language-specific, their reflective functionality is often restricted, and the adaptation and application logic are often mixed which hardens the understanding and maintenance of the source code. Our system overcomes these limitations. Approach: We designed a model and implemented a prototype system to support open programming language interpreters. The implementation is integrated in the Neverlang framework which now exposes the structure, behaviour and the runtime state of any Neverlang-based interpreter with the ability to modify it. Knowledge: Our system provides a complete control over interpreter’s structure, behaviour and its runtime state. The approach is applicable to every Neverlang-based interpreter. Adaptation code can potentially be reused across different language implementations. Grounding: Having a prototype implementation we focused on feasibility evaluation. The paper shows that our approach well addresses problems commonly found in the research literature. We have a demon- strative video and examples that illustrate our approach on dynamic software adaptation, aspect-oriented programming, debugging and context-aware interpreters. Importance: Our paper presents the first reflective approach targeting a general framework for language development. -
1. with Examples of Different Programming Languages Show How Programming Languages Are Organized Along the Given Rubrics: I
AGBOOLA ABIOLA CSC302 17/SCI01/007 COMPUTER SCIENCE ASSIGNMENT 1. With examples of different programming languages show how programming languages are organized along the given rubrics: i. Unstructured, structured, modular, object oriented, aspect oriented, activity oriented and event oriented programming requirement. ii. Based on domain requirements. iii. Based on requirements i and ii above. 2. Give brief preview of the evolution of programming languages in a chronological order. 3. Vividly distinguish between modular programming paradigm and object oriented programming paradigm. Answer 1i). UNSTRUCTURED LANGUAGE DEVELOPER DATE Assembly Language 1949 FORTRAN John Backus 1957 COBOL CODASYL, ANSI, ISO 1959 JOSS Cliff Shaw, RAND 1963 BASIC John G. Kemeny, Thomas E. Kurtz 1964 TELCOMP BBN 1965 MUMPS Neil Pappalardo 1966 FOCAL Richard Merrill, DEC 1968 STRUCTURED LANGUAGE DEVELOPER DATE ALGOL 58 Friedrich L. Bauer, and co. 1958 ALGOL 60 Backus, Bauer and co. 1960 ABC CWI 1980 Ada United States Department of Defence 1980 Accent R NIS 1980 Action! Optimized Systems Software 1983 Alef Phil Winterbottom 1992 DASL Sun Micro-systems Laboratories 1999-2003 MODULAR LANGUAGE DEVELOPER DATE ALGOL W Niklaus Wirth, Tony Hoare 1966 APL Larry Breed, Dick Lathwell and co. 1966 ALGOL 68 A. Van Wijngaarden and co. 1968 AMOS BASIC FranÇois Lionet anConstantin Stiropoulos 1990 Alice ML Saarland University 2000 Agda Ulf Norell;Catarina coquand(1.0) 2007 Arc Paul Graham, Robert Morris and co. 2008 Bosque Mark Marron 2019 OBJECT-ORIENTED LANGUAGE DEVELOPER DATE C* Thinking Machine 1987 Actor Charles Duff 1988 Aldor Thomas J. Watson Research Center 1990 Amiga E Wouter van Oortmerssen 1993 Action Script Macromedia 1998 BeanShell JCP 1999 AngelScript Andreas Jönsson 2003 Boo Rodrigo B.