DOCSLIB.ORG

9. Distributed Processing Exception and Exception Handlers Type of Bugs

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
9. Distributed Processing Exception and Exception Handlers Type of Bugs 9. Distributed Processing The same exception may be thrown multiple times in the try block. Exception and Exception Handlers There may be many different exceptions thrown from the same try block. There can be multiple catch blocks Type of Bugs - following the same try block handling different exceptions thrown. The same block can handle all possible types of Logic Errors – Errors in program logic due to poor exceptions. understanding of the problem and solution procedure. catch(…) Syntax Errors – Errors arise due to poor understanding of { the language. // Statements for processing all exceptions } Exceptions are runtime anomalies or unusual conditions that a program may encounter while executing. E.g. divide Propagating an Exception: If a handler for an exception by zero, access to an array out of bounds, running out of is not defined at the place where an exception occurs then memory or disk space. it is propagated further so it could be handled in the calling subprogram. If not handled there it is propagated When a program encounters an exceptional condition, it further. should be Identified and dealt with effectively. If no subprogram/program provides a handler, the entire program is terminated and standard language-defined Exception Handling: It is a mechanism to detect and handler is invoked. report an ‗exceptional circumstance‖ so that appropriate action can be taken. It involves the following tasks. COROUTINES: Coroutines are subprogram components that generalize subroutines to allow multiple entry points 1. Find the problem (Hit the exception) and suspending and resuming of execution at certain 2. Inform that an error has occurred (Throw the locations. exception) 3. Receive the error information (catch the expression) Here we allow subprograms to return to their calling 4. Take corrective action (Handle the exception) program before completion of execution. Such subprograms are termed coroutines. When a coroutine main() receives control from another subprogram, it executes { partially and then is suspended when it returns control. At int x, y; a later point, the calling program may resume execution of cout << ―Enter values of x and y‖; the coroutine from the point at which execution was cin >>x>>y; previously suspended. If A calls Subprogram B as a try { coroutine, B executes awhile and returns control to A, just if (x != 0) as any ordinary subprogram would do. When A again cout ―y/x is =―<<y/x; passes control to B via a resume B, B again executes else awhile and returns control to A, just as an ordinary throw(x); subprogram. Thus, to A, B appears as an ordinary } subprogram. However, the situation is similar when catch (int i) viewed from Subprogram B. B, in the middle of { execution, resumes execution of A. A executes awhile and cout << ―Divide by zero exception caught‖; returns control to B. B continues execution awhile and } returns control to A. A executes awhile and returns control } to B. From Subprogram B, A appears much like an ordinary subprogram. The name coroutine derives from this symmetry. Rather than having a parent-child or caller- try – Block contains sequence of statements which may callee relationship between the two subprograms, the two generate exception. programs appear more as equals—two subprograms throw – When an exception is detected, it is thrown using swapping control back and forth as each executes, with throw statement neither clearly controlling the other (Figure 11.1). catch – It‘s a block that catches the exception thrown by throw statement and handles it appropriately. catch block immediately follows the try block. Execution of resume B in coroutine A will involve the following steps: The current value of CIP is saved in the resume point location of activation record for A. The ip value in the resume point location is fetched from B‘s activation record and assigned to CIP so that subprogram B resume at proper location. Subprogram Scheduling Normally execution of subprogram is assumed to be initiated immediately upon its call Subprogram scheduling relaxes the above condition. Comparison with Subroutines Scheduling Techniques: 1. The lifespan of subroutines is dictated by last in, first 1. Schedule subprogram to be executed before or after out (the last subroutine called is the first to return); other subprograms. lifespan of coroutines is dictated by their use and need, call B after A 2. The start of the subroutine is the only point entry. There 2. Schedule subprogram to be executed when given might be multiple entries in coroutines. Boolean expression is true 3. The subroutine has to complete execution before it call X when Y = 7 and Z > 0 returns the control. Coroutines may suspend execution and 3. Schedule subprograms on basis of a simulated time return control to caller. scale. call B at time = Currenttime + 50 Example: Let there be a consumer-producer relationship 4. Schedule subprograms according to a priority where one routine creates items and adds to the queue and designation the other removes from the queue and uses them. call B with priority 5 Comparison of Coroutines with Subroutines Languages : GPSS, SIMULA 1. The lifespan of subroutines is dictated by last in, first out (the last subroutine called is the first to return); Parallel Programming lifespan of coroutines is dictated by their use and need, Computer systems capable of executing several programs 2. The start of the subroutine is the only point entry. There concurrently are now quite common. A multiprocessor might be multiple entries in coroutines. system has several central processing units (CPU) sharing 3. The subroutine has to complete execution before it a common memory. A distributed or parallel computer returns the control. Coroutines may suspend execution and system has several computers (possibly hundreds), each return control to caller. with its own memory and CPU, connected with communication links into a network in which each can Example: Let there be a consumer-producer relationship communicate with the others. In such systems, many tasks where one routine creates items and adds to the queue and may execute concurrently. Operating systems that support the other removes from the queue and uses them. multiprogramming and time sharing provide this sort of concurrent execution for separate user programs. Principles of Parallel Programming Languages Parallel programming constructs add complexity to the language design because several processors may be accessing the same data simultaneously. To consider parallelism in programming languages, the following five concepts must be addressed: 1. Variable definitions: Variables may be either mutable or definitional Mutable variables are the common Implementation of Coroutine variables declared in most sequential languages. Values Only one activation of each coroutine exists at a time. A may be assigned to the variables and changed during single location, called resume point is reserved in the program execution. A definitional variable may be activation record to save the old ip value of CIP when a assigned a value only once. The virtue of such a variable resume instruction transfer control to another subroutine. is that there is no synchronization problem. Once assigned a value, any task may access the variable and obtain the execution is resumed; if not zero or if the queue is empty, correct value. then the counter is incremented by one (indicating a signal 2. Parallel composition: Execution proceeds from one has been sent but not yet received). In either case, statement to the next. In addition to the sequential and execution of Task A continues after the signal operation is conditional statements of sequential programming complete. languages, we need to add the parallel statement, which wait(P): When executed by a task B, this operation tests causes additional threads of control to begin executing. the value of the counter in P; if nonzero, then the counter 3. Program structure: Parallel programs generally follow value is decremented by one (indicating that B has one of the following two execution models: received a signal) and Task B continues execution; if zero, (a) They may be transformational, where the goal then Task B is inserted at the end of the task queue for P is to transform the input data into an appropriate and execution of B is suspended (indicating that B is output value. Parallelism is applied to speed up waiting for a signal to be sent). the process, such as multiplying a matrix rapidly by multiplying several sections of it in parallel, signal and wait both have simple semantics that require (b) They may be reactive, where the program the principle of atomicity. Each operation completes reacts to external stimuli called events. Real-time execution before any other concurrent operation can and command- and-control systems are examples access its data. Atomicity prevents certain classes of of reactive systems. An operating system and a undesirable nondeterministic events to occur. transaction processing system, such as a reservation system, are typical examples of such Software Architecture reactive systems. They are characterized by Most programming languages are based on a discrete generally having nondeterministic behavior model of execution, That is, the program begins because it is never explicit exactly when an event execution, and then, in some order, will occur. 1. Reads relevant data from the local file system, 4. Communication: Parallel programs must communicate 2. Produces some answers, with one another. Such communication will typically be 3. Writes data to the local file system. via shared memory with common data objects accessed by This description clearly shows the presence of two classes each parallel program or via messages where each parallel of data: temporary or transient data, which have a lifetime program has its own copy of the data object and passes being the execution of the program, and persistent data, data values among the other parallel programs.
Load more

Recommended publications
  • The Early History of Smalltalk
    The Early History of Smalltalk http://www.accesscom.com/~darius/EarlyHistoryS... The Early History of Smalltalk Alan C. Kay Apple Computer [email protected]# Permission to copy without fee all or part of this material is granted provided that the copies are not made or distributed for direct commercial advantage, the ACM copyright notice and the title of the publication and its date appear, and notice is given that copying is by permission of the Association for Computing Machinery. To copy otherwise, or to republish, requires a fee and/or specific permission. HOPL-II/4/93/MA, USA © 1993 ACM 0-89791-571-2/93/0004/0069...$1.50 Abstract Most ideas come from previous ideas. The sixties, particularly in the ARPA community, gave rise to a host of notions about "human-computer symbiosis" through interactive time-shared computers, graphics screens and pointing devices. Advanced computer languages were invented to simulate complex systems such as oil refineries and semi-intelligent behavior. The soon-to- follow paradigm shift of modern personal computing, overlapping window interfaces, and object-oriented design came from seeing the work of the sixties as something more than a "better old thing." This is, more than a better way: to do mainframe computing; for end-users to invoke functionality; to make data structures more abstract. Instead the promise of exponential growth in computing/$/volume demanded that the sixties be regarded as "almost a new thing" and to find out what the actual "new things" might be. For example, one would compute with a handheld "Dynabook" in a way that would not be possible on a shared mainframe; millions of potential users meant that the user interface would have to become a learning environment along the lines of Montessori and Bruner; and needs for large scope, reduction in complexity, and end-user literacy would require that data and control structures be done away with in favor of a more biological scheme of protected universal cells interacting only through messages that could mimic any desired behavior.
    [Show full text]
  • Object-Oriented Programming in the Beta Programming Language
    OBJECT-ORIENTED PROGRAMMING IN THE BETA PROGRAMMING LANGUAGE OLE LEHRMANN MADSEN Aarhus University BIRGER MØLLER-PEDERSEN Ericsson Research, Applied Research Center, Oslo KRISTEN NYGAARD University of Oslo Copyright c 1993 by Ole Lehrmann Madsen, Birger Møller-Pedersen, and Kristen Nygaard. All rights reserved. No part of this book may be copied or distributed without the prior written permission of the authors Preface This is a book on object-oriented programming and the BETA programming language. Object-oriented programming originated with the Simula languages developed at the Norwegian Computing Center, Oslo, in the 1960s. The first Simula language, Simula I, was intended for writing simulation programs. Si- mula I was later used as a basis for defining a general purpose programming language, Simula 67. In addition to being a programming language, Simula1 was also designed as a language for describing and communicating about sys- tems in general. Simula has been used by a relatively small community for many years, although it has had a major impact on research in computer sci- ence. The real breakthrough for object-oriented programming came with the development of Smalltalk. Since then, a large number of programming lan- guages based on Simula concepts have appeared. C++ is the language that has had the greatest influence on the use of object-oriented programming in industry. Object-oriented programming has also been the subject of intensive research, resulting in a large number of important contributions. The authors of this book, together with Bent Bruun Kristensen, have been involved in the BETA project since 1975, the aim of which is to develop con- cepts, constructs and tools for programming.
    [Show full text]
  • CPS323 Lecture: Concurrency Materials: 1. Coroutine Projectables
    CPS323 Lecture: Concurrency Materials: 1. Coroutine Projectables 2. Handout for Ada Concurrency + Executable form (simple_tasking.adb, producer_and_consumer.adb) I. Introduction - ------------ A. Most of our attention throughout the CS curricum has been focussed on _sequential_ programming, in which a program does exactly one thing at a time, following a predictable order of steps. In particular, we expect a given program will always follow the exact same sequence of steps when run on a given set of data. B. An alternative is to think in terms of _concurrent_ programming, in which a "program" (at least in principle) does multiple things at the same time, following an order of steps that is not predictable and may differ between runs even if the same program is run on exactly the same data. C. Concurrency has long been an interest in CS, but has become of particular interest as we move into a situation in which raw hardware speeds have basically plateaued and multicore processors are coming to dominate the hardware scene. There are at least three reasons why this topic is of great interest. 1. Achieving maximum performance using technologies such as multicore processors. 2. Systems that inherently require multiple processors working together cooperatively on a single task - e.g. distributed or embedded systems. 3. Some problems are more naturally addressed by thinking in terms of multiple concurrrent components, rather than a single monolithic program. D. There are two broad approaches that might be taken to concurrency: 1. Make use of system libraries, without directly supporting parallelism in the language. (The approach taken by most languages - e.g.
    [Show full text]
  • A Low-Cost Implementation of Coroutines for C
    University of Wollongong Research Online Department of Computing Science Working Faculty of Engineering and Information Paper Series Sciences 1983 A low-cost implementation of coroutines for C Paul A. Bailes University of Wollongong Follow this and additional works at: https://ro.uow.edu.au/compsciwp Recommended Citation Bailes, Paul A., A low-cost implementation of coroutines for C, Department of Computing Science, University of Wollongong, Working Paper 83-9, 1983, 24p. https://ro.uow.edu.au/compsciwp/76 Research Online is the open access institutional repository for the University of Wollongong. For further information contact the UOW Library: [email protected] A LOW-COST IMPLEMENTATION OF COROUTINES FOR C Paul A. Bailes Department of Computing Science University of Wollongong Preprint No. 83-9 November 16, 1983 P.O. Box 1144, WOLLONGONG N.S.W. 2500, AUSTRALIA tel (042)-282-981 telex AA29022 A Low-Cost Implementation of Coroutines for C Paul A. Bailes Department of Computing Science University of Wollongong Wollongong N.S.W. 2500 Australia ABSTRACT We identify a set of primitive operations supporting coroutines, and demonstrate their usefulness. We then address their implementation in C accord­ ing to a set of criteria aimed at maintaining simplicity, and achieve a satisfactory compromise between it and effectiveness. Our package for the PDP-II under UNIXt allows users of coroutines in C programs to gain access to the primitives via an included definitions file and an object library; no penalty is imposed upon non-coroutine users. October 6, 1983 tUNIX is a Trademark of Bell Laboratories. A Low-Cost Implementation of Coroutines for C Paul A.
    [Show full text]
  • Kotlin Coroutines Deep Dive Into Bytecode #Whoami
    Kotlin Coroutines Deep Dive into Bytecode #whoami ● Kotlin compiler engineer @ JetBrains ● Mostly working on JVM back-end ● Responsible for (almost) all bugs in coroutines code Agenda I will talk about ● State machines ● Continuations ● Suspend and resume I won’t talk about ● Structured concurrency and cancellation ● async vs launch vs withContext ● and other library related stuff Agenda I will talk about Beware, there will be code. A lot of code. ● State machines ● Continuations ● Suspend and resume I won’t talk about ● Structured concurrency and cancellation ● async vs launch vs withContext ● and other library related stuff Why coroutines ● No dependency on a particular implementation of Futures or other such rich library; ● Cover equally the "async/await" use case and "generator blocks"; ● Make it possible to utilize Kotlin coroutines as wrappers for different existing asynchronous APIs (such as Java NIO, different implementations of Futures, etc). via coroutines KEEP Getting Lazy With Kotlin Pythagorean Triples fun printPythagoreanTriples() { for (i in 1 until 100) { for (j in 1 until i) { for (k in i until 100) { if (i * i + j * j < k * k) { break } if (i * i + j * j == k * k) { println("$i^2 + $j^2 == $k^2") } } } } } Pythagorean Triples fun printPythagoreanTriples() { for (i in 1 until 100) { for (j in 1 until i) { for (k in i until 100) { if (i * i + j * j < k * k) { break } if (i * i + j * j == k * k) { println("$i^2 + $j^2 == $k^2") } } } } } Pythagorean Triples fun printPythagoreanTriples() { for (i in 1 until 100) { for (j
    [Show full text]
  • Csc 520 Principles of Programming Languages Coroutines Coroutines
    Coroutines Coroutines are supported by Simula and Modula-2. CSc 520 They are similar to Java’s threads, except the programmer has to explicitly transfer control from one Principles of Programming execution context to another. Languages Thus, like threads several coroutines can exist simultaneously but unlike threads there is no central 36: Procedures — Coroutines scheduler that decides which coroutine should run next. Christian Collberg A coroutine is represented by a closure. [email protected] A special operation transfer(C) shifts control to the coroutine C, at the location where C last left off. Department of Computer Science University of Arizona Copyright c 2005 Christian Collberg 520—Spring 2005—36 [1] 520—Spring 2005—36 [2] Coroutines. Coroutines. The next slide shows an example from Scott where two var us, cfs: coroutine; coroutines execute “concurrently”, by explicitly transferring control between each other. coroutine update_screen() { ... In the example one coroutine displays a moving detach screen-saver, the other walks the file-system to check loop { for corrupt files. ... transfer(cfs) ... } } coroutine check_file_system() { ... } main () { ... } 520—Spring 2005—36 [3] 520—Spring 2005—36 [4] Coroutines. Coroutines in Modula-2 coroutine check_file_system() { Modula-2's system module provides two functions to create and transfer ... between coroutines: detach for all files do { PROCEDURE NEWPROCESS( proc: PROC; (* The procedure *) ... transfer(cfs) addr: ADDRESS; (* The stack *) ... transfer(cfs) size: CARDINAL; (* The stack size *) ... transfer(cfs) ... VAR new: ADDRESS); (* The coroutine *) } PROCEDURE TRANSFER( } VAR source: ADDRESS; (* Current coroutine *) VAR destination: ADDRESS); (* New coroutine *) main () { us := new update_screen(); The ®rst time TRANSFER is called source will be instantiated to cfs := new check_file_system(); the main (outermost) coroutine.
    [Show full text]
  • Practical Perl Tools Parallel Asynchronicity, Part 2
    COLUMNS Practical Perl Tools Parallel Asynchronicity, Part 2 DAVID N. BLANK-EDELMAN David Blank-Edelman is elcome back for Part 2 of this mini-series on modern methods the Technical Evangelist at for doing multiple things at once in Perl. In the first part (which I Apcera (the comments/ highly recommend that you read first before reading this sequel), views here are David’s alone W and do not represent Apcera/ we talked about some of the simpler methods for multi-tasking like the use Ericsson) . He has spent close to thirty years of fork() and Parallel::ForkManager. We had just begun to explore using the in the systems administration/DevOps/SRE Coro module as the basis for using threads in Perl (since the native stuff is so field in large multiplatform environments ucky) when we ran out of time. Let’s pick up the story roughly where we left it. including Brandeis University, Cambridge Technology Group, MIT Media Laboratory, Coro and Northeastern University. He is the author As a quick reminder, Coro offers an implementation of coroutines that we are going to use as of the O’Reilly Otter book Automating System just a pleasant implementation of cooperative threading (see the previous column for more Administration with Perl and is a frequent invited picayune details around the definition of a coroutine). By cooperative, we mean that each speaker/organizer for conferences in the field. thread gets queued up to run, but can only do so after another thread has explicitly signaled David is honored to serve on the USENIX that it is ready to cede its time in the interpreter.
    [Show full text]
  • Coroutines and Generators Chapter Three
    Coroutines and Generators Coroutines and Generators Chapter Three 3.1 Chapter Overview This chapter discusses two special types of program units known as coroutines and generators. A coroutine is similar to a procedure and a generator is similar to a function. The principle difference between these program units and procedures/functions is that the call/return mechanism is different. Coroutines are especially useful for multiplayer games and other program flow where sections of code "take turns" execut- ing. Generators, as their name implies, are useful for generating a sequence of values; in many respects generators are quite similar to HLA’s iterators without all the restrictions of the iterators (i.e., you can only use iterators within a FOREACH loop). 3.2 Coroutines A common programming paradigm is for two sections of code to swap control of the CPU back and forth while executing. There are two ways to achieve this: preemptive and cooperative. In a preemptive sys- tem, two or more processes or threads take turns executing with the task switch occurring independently of the executing code. A later volume in this text will consider preemptive multitasking, where the Operating System takes responsibility for interrupting one task and transferring control to some other task. In this chapter we’ll take a look at coroutines that explicitly transfer control to another section of the code1 When discussing coroutines, it is instructive to review how HLA’s iterators work, since there is a strong correspondence between iterators and coroutines. Like iterators, there are four types of entries and returns associated with a coroutine: • Initial entry.
    [Show full text]
  • Deriving Type Systems and Implementations for Coroutines
    Deriving Type Systems and Implementations for Coroutines Konrad Anton and Peter Thiemann Institut f¨urInformatik, Universit¨atFreiburg {anton,thiemann}@informatik.uni-freiburg.de Abstract. Starting from reduction semantics for several styles of corou- tines from the literature, we apply Danvy’s method to obtain equivalent functional implementations (definitional interpreters) for them. By ap- plying existing type systems for programs with continuations, we obtain sound type systems for coroutines through the translation. The resulting type systems are similar to earlier hand-crafted ones. As a side product, we obtain implementations for these styles of coroutines in OCaml. 1 Introduction Coroutines are an old programming construct, dating back to the 1960s [5]. They have been neglected for a while, but are currently enjoying a renaissance (e.g. in Lua [12]), sometimes in the limited form of generators (Python [20], C# [17]) and sometimes under different names (e.g., fibers in .NET). Type systems for coroutines have not been considered in the past. Coroutines without parameters and return values (Simula, Modula 2 [21]), coroutine opera- tions whose effects are tied to the static structure of the program (ACL, [16]), or coroutines lexically limited to the body of one function (C#), could be integrated into said languages without special support in the type system. In an earlier paper [1], we developed the first type system for a simply-typed λ-calculus with coroutines. This development was done in an ad-hoc style for a feature-rich calculus and resulted in a type and effect system with a simple notion of subeffecting to capture the control effects of coroutine operations.
    [Show full text]
  • CS164: Introduction to Programming Languages and Compilers, Spring 2012 Thibaud Hottelier UC Berkeley
    Lecture 5 Implementing Coroutines compile AST to bytecode, bytecode interpreter Ras Bodik Hack Your Language! Shaon Barman CS164: Introduction to Programming Thibaud Hottelier Languages and Compilers, Spring 2012 UC Berkeley 1 What you will learn today Implement Asymmetric Coroutines – why a recursive interpreter with implicit stack won’t do Compiling AST to bytecode - this is your first compiler; compiles AST to “flat” code Bytecode Interpreter - bytecode can be interpreted without recursion - hence no need to keep interpreter state on the call stack 2 PA2 PA2 was released today, due Sunday – bytecode interpreter of coroutines – after PA2, you will be able to implement iterators – in PA3, you will build Prolog on top of your coroutines – extra credit: cool use of coroutines (see L4 reading) HW3 has been assigned: cool uses of coroutines This homework is not graded. While it is optional, you are expected to know the homework material: 1) lazy list concatenation 2) regexes Solve at least the lazy list problem before you start on PA2 3 Code 4 Cal Hackathon Friday, February 3, 9:00pm to Saturday, February 4 5:00pm Soda Hall Wozniak Lounge Grand Prize: $1,500!!! Register @ http://code4cal.eventbrite.com/ More information about the event at http://stc.berkeley.edu. The Student Technology Council (STC), an advisory council for the UC Berkeley CIO, Shel Waggener, is hosting Code 4 Cal, a hackathon for students to create innovative, sustainable, and most of all, useful applications or widgets for Cal students. Student-developed app could be adopted by the University! Cash prizes start at $1,500. 4 Review of L4: Why Coroutines Loop calls iterator function to get the next item eg the next token from the input The iterator maintains state between two such calls eg pointer to the input stream.
    [Show full text]
  • Specialising Dynamic Techniques for Implementing the Ruby Programming Language
    SPECIALISING DYNAMIC TECHNIQUES FOR IMPLEMENTING THE RUBY PROGRAMMING LANGUAGE A thesis submitted to the University of Manchester for the degree of Doctor of Philosophy in the Faculty of Engineering and Physical Sciences 2015 By Chris Seaton School of Computer Science This published copy of the thesis contains a couple of minor typographical corrections from the version deposited in the University of Manchester Library. [email protected] chrisseaton.com/phd 2 Contents List of Listings7 List of Tables9 List of Figures 11 Abstract 15 Declaration 17 Copyright 19 Acknowledgements 21 1 Introduction 23 1.1 Dynamic Programming Languages.................. 23 1.2 Idiomatic Ruby............................ 25 1.3 Research Questions.......................... 27 1.4 Implementation Work......................... 27 1.5 Contributions............................. 28 1.6 Publications.............................. 29 1.7 Thesis Structure............................ 31 2 Characteristics of Dynamic Languages 35 2.1 Ruby.................................. 35 2.2 Ruby on Rails............................. 36 2.3 Case Study: Idiomatic Ruby..................... 37 2.4 Summary............................... 49 3 3 Implementation of Dynamic Languages 51 3.1 Foundational Techniques....................... 51 3.2 Applied Techniques.......................... 59 3.3 Implementations of Ruby....................... 65 3.4 Parallelism and Concurrency..................... 72 3.5 Summary............................... 73 4 Evaluation Methodology 75 4.1 Evaluation Philosophy
    [Show full text]
  • Language Design and Implementation Using Ruby and the Interpreter Pattern
    Language Design and Implementation using Ruby and the Interpreter Pattern Ariel Ortiz Information Technology Department Tecnológico de Monterrey, Campus Estado de México Atizapán de Zaragoza, Estado de México, Mexico. 52926 [email protected] ABSTRACT to explore different language concepts and programming styles. In this paper, the S-expression Interpreter Framework (SIF) is Section 4 describes briefly how the SIF has been used in class. presented as a tool for teaching language design and The conclusions are found in section 5. implementation. The SIF is based on the interpreter design pattern and is written in the Ruby programming language. Its core is quite 1.1 S-Expressions S-expressions (symbolic expressions) are a parenthesized prefix small, but it can be easily extended by adding primitive notation, mainly used in the Lisp family languages. They were procedures and special forms. The SIF can be used to demonstrate selected as the framework’s source language notation because advanced language concepts (variable scopes, continuations, etc.) they offer important advantages: as well as different programming styles (functional, imperative, and object oriented). • Both code and data can be easily represented. Adding a new language construct is pretty straightforward. • Categories and Subject Descriptors The number of program elements is minimal, thus a parser is − relatively easy to write. D.3.4 [Programming Languages]: Processors interpreters, • run-time environments. The arity of operators doesn’t need to be fixed, so, for example, the + operator can be defined to accept any number of arguments. General Terms • There are no problems regarding operator precedence or Design, Languages. associativity, because every operator has its own pair of parentheses.
    [Show full text]