Implementation of Lua Coroutines
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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. -
Bringing GNU Emacs to Native Code
Bringing GNU Emacs to Native Code Andrea Corallo Luca Nassi Nicola Manca [email protected] [email protected] [email protected] CNR-SPIN Genoa, Italy ABSTRACT such a long-standing project. Although this makes it didactic, some Emacs Lisp (Elisp) is the Lisp dialect used by the Emacs text editor limitations prevent the current implementation of Emacs Lisp to family. GNU Emacs can currently execute Elisp code either inter- be appealing for broader use. In this context, performance issues preted or byte-interpreted after it has been compiled to byte-code. represent the main bottleneck, which can be broken down in three In this work we discuss the implementation of an optimizing com- main sub-problems: piler approach for Elisp targeting native code. The native compiler • lack of true multi-threading support, employs the byte-compiler’s internal representation as input and • garbage collection speed, exploits libgccjit to achieve code generation using the GNU Com- • code execution speed. piler Collection (GCC) infrastructure. Generated executables are From now on we will focus on the last of these issues, which con- stored as binary files and can be loaded and unloaded dynamically. stitutes the topic of this work. Most of the functionality of the compiler is written in Elisp itself, The current implementation traditionally approaches the prob- including several optimization passes, paired with a C back-end lem of code execution speed in two ways: to interface with the GNU Emacs core and libgccjit. Though still a work in progress, our implementation is able to bootstrap a func- • Implementing a large number of performance-sensitive prim- tional Emacs and compile all lexically scoped Elisp files, including itive functions (also known as subr) in C. -
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. -
Stackwalkerapi Programmer's Guide
Paradyn Parallel Performance Tools StackwalkerAPI Programmer’s Guide 9.2 Release June 2016 Computer Sciences Department University of Wisconsin–Madison Madison, WI 53706 Computer Science Department University of Maryland College Park, MD 20742 Email [email protected] Web www.dyninst.org Contents 1 Introduction 3 2 Abstractions 4 2.1 Stackwalking Interface . .5 2.2 Callback Interface . .5 3 API Reference 6 3.1 Definitions and Basic Types . .6 3.1.1 Definitions . .6 3.1.2 Basic Types . .9 3.2 Namespace StackwalkerAPI . 10 3.3 Stackwalking Interface . 10 3.3.1 Class Walker . 10 3.3.2 Class Frame . 14 3.4 Accessing Local Variables . 18 3.5 Callback Interface . 19 3.5.1 Default Implementations . 19 3.5.2 Class FrameStepper . 19 3.5.3 Class StepperGroup . 22 3.5.4 Class ProcessState . 24 3.5.5 Class SymbolLookup . 27 4 Callback Interface Default Implementations 27 4.1 Debugger Interface . 28 4.1.1 Class ProcDebug . 29 4.2 FrameSteppers . 31 4.2.1 Class FrameFuncStepper . 31 4.2.2 Class SigHandlerStepper . 32 4.2.3 Class DebugStepper . 33 1 4.2.4 Class AnalysisStepper . 33 4.2.5 Class StepperWanderer . 33 4.2.6 Class BottomOfStackStepper . 33 2 1 Introduction This document describes StackwalkerAPI, an API and library for walking a call stack. The call stack (also known as the run-time stack) is a stack found in a process that contains the currently active stack frames. Each stack frame is a record of an executing function (or function-like object such as a signal handler or system call). -
Procedures & the Stack
Procedures & The Stack Spring 2016 Procedures & The Stack Announcements ¢ Lab 1 graded § Late days § Extra credit ¢ HW 2 out ¢ Lab 2 prep in section tomorrow § Bring laptops! ¢ Slides HTTP://XKCD.COM/1270/ 1 Procedures & The Stack Spring 2016 Memory & data Roadmap Integers & floats C: Java: Machine code & C x86 assembly car *c = malloc(sizeof(car)); Car c = new Car(); Procedures & stacks c->miles = 100; c.setMiles(100); Arrays & structs c->gals = 17; c.setGals(17); float mpg = get_mpg(c); float mpg = Memory & caches free(c); c.getMPG(); Processes Virtual memory Assembly get_mpg: Memory allocation pushq %rbp Java vs. C language: movq %rsp, %rbp ... popq %rbp ret OS: Machine 0111010000011000 100011010000010000000010 code: 1000100111000010 110000011111101000011111 Computer system: 2 Procedures & The Stack Spring 2016 Mechanisms required for procedures ¢ Passing control P(…) { § To beginning oF procedure code • • § Back to return point y = Q(x); print(y) ¢ Passing data • § Procedure arguments } § Return value ¢ Memory management int Q(int i) § Allocate during procedure execution { § Deallocate upon return int t = 3*i; int v[10]; ¢ All implemented with machine • instructions • § An x86-64 procedure uses only those return v[t]; mechanisms required For that procedure } 3 Procedures & The Stack Spring 2016 Questions to answer about procedures ¢ How do I pass arguments to a procedure? ¢ How do I get a return value from a procedure? ¢ Where do I put local variables? ¢ When a function returns, how does it know where to return? ¢ To answer some of -
Hop Client-Side Compilation
Chapter 1 Hop Client-Side Compilation Florian Loitsch1, Manuel Serrano1 Abstract: Hop is a new language for programming interactive Web applications. It aims to replace HTML, JavaScript, and server-side scripting languages (such as PHP, JSP) with a unique language that is used for client-side interactions and server-side computations. A Hop execution platform is made of two compilers: one that compiles the code executed by the server, and one that compiles the code executed by the client. This paper presents the latter. In order to ensure compatibility of Hop graphical user interfaces with popular plain Web browsers, the client-side Hop compiler has to generate regular HTML and JavaScript code. The generated code runs roughly at the same speed as hand- written code. Since the Hop language is built on top of the Scheme program- ming language, compiling Hop to JavaScript is nearly equivalent to compiling Scheme to JavaScript. SCM2JS, the compiler we have designed, supports the whole Scheme core language. In particular, it features proper tail recursion. How- ever complete proper tail recursion may slow down the generated code. Despite an optimization which eliminates up to 40% of instrumentation for tail call in- tensive benchmarks, worst case programs were more than two times slower. As a result Hop only uses a weaker form of tail-call optimization which simplifies recursive tail-calls to while-loops. The techniques presented in this paper can be applied to most strict functional languages such as ML and Lisp. SCM2JS can be downloaded at http://www-sop.inria.fr/mimosa/person- nel/Florian.Loitsch/scheme2js/. -
MIPS Calling Convention
MIPS Calling Convention CS 64: Computer Organization and Design Logic Lecture #9 Fall 2018 Ziad Matni, Ph.D. Dept. of Computer Science, UCSB Administrative • Lab #5 this week – due on Friday • Grades will be up on GauchoSpace today by noon! – If you want to review your exams, see your TAs: LAST NAMES A thru Q See Bay-Yuan (Th. 12:30 – 2:30 pm) LAST NAMES R thru Z See Harmeet (Th. 9:30 – 11:30 am) • Mid-quarter evaluations for T.As – Links on the last slide and will put up on Piazza too – Optional to do, but very appreciated by us all! 11/5/2018 Matni, CS64, Fa18 2 CS 64, Fall 18, Midterm Exam Average = 86.9% Median = 87% 26 22 8 5 3 11/5/2018 Matni, CS64, Fa18 3 Lecture Outline • MIPS Calling Convention – Functions calling functions – Recursive functions 11/5/2018 Matni, CS64, Fa18 4 Function Calls Within Functions… Given what we’ve said so far… • What about this code makes our previously discussed setup break? – You would need multiple copies of $ra • You’d have to copy the value of $ra to another register (or to mem) before calling another function • Danger: You could run out of registers! 11/5/2018 Matni, CS64, Fa18 5 Another Example… What about this code makes this setup break? • Can’t fit all variables in registers at the same time! • How do I know which registers are even usable without looking at the code? 11/5/2018 Matni, CS64, Fa18 6 Solution??!! • Store certain information in memory only at certain times • Ultimately, this is where the call stack comes from • So what (registers/memory) save what??? 11/5/2018 Matni, CS64, Fa18 -
SI 413, Unit 3: Advanced Scheme
SI 413, Unit 3: Advanced Scheme Daniel S. Roche ([email protected]) Fall 2018 1 Pure Functional Programming Readings for this section: PLP, Sections 10.7 and 10.8 Remember there are two important characteristics of a “pure” functional programming language: • Referential Transparency. This fancy term just means that, for any expression in our program, the result of evaluating it will always be the same. In fact, any referentially transparent expression could be replaced with its value (that is, the result of evaluating it) without changing the program whatsoever. Notice that imperative programming is about as far away from this as possible. For example, consider the C++ for loop: for ( int i = 0; i < 10;++i) { /∗ some s t u f f ∗/ } What can we say about the “stuff” in the body of the loop? Well, it had better not be referentially transparent. If it is, then there’s no point in running over it 10 times! • Functions are First Class. Another way of saying this is that functions are data, just like any number or list. Functions are values, in fact! The specific privileges that a function earns by virtue of being first class include: 1) Functions can be given names. This is not a big deal; we can name functions in pretty much every programming language. In Scheme this just means we can do (define (f x) (∗ x 3 ) ) 2) Functions can be arguments to other functions. This is what you started to get into at the end of Lab 2. For starters, there’s the basic predicate procedure?: (procedure? +) ; #t (procedure? 10) ; #f (procedure? procedure?) ; #t 1 And then there are “higher-order functions” like map and apply: (apply max (list 5 3 10 4)) ; 10 (map sqrt (list 16 9 64)) ; '(4 3 8) What makes the functions “higher-order” is that one of their arguments is itself another function. -
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. -
UNDERSTANDING STACK ALIGNMENT in 64-BIT CALLING CONVENTIONS for X86-64 Assembly Programmers
UNDERSTANDING STACK ALIGNMENT IN 64-BIT CALLING CONVENTIONS For x86-64 Assembly Programmers This article is part of CPU2.0 presentation Soffian Abdul Rasad Date : Oct 2nd, 2017 Updated: 2019 Note: This article is released in conjunction with CPU2.0 to enable users to use CPU2.0 correctly in regards to stack alignment. It does not present full stack programming materials. MS 64-bit Application Binary Interface (ABI) defines an x86_64 software calling convention known as the fastcall. System V also introduces similar software calling convention known as AMD64 calling convention. These calling conventions specify the standards and the requirements of the 64-bit APIs to enable codes to access and use them in a standardized and uniform fashion. This is the standard convention being employed by Win64 APIs and Linux64 respectively. While the two are radically different, they share similar stack alignment policy – the stack must be well-aligned to 16-byte boundaries prior to calling a 64-bit API. A memory address is said to be aligned to 16 if it is evenly divisible by 16, or if the last digit is 0, in hexadecimal notation. Please note that to simplify discussions, we ignore the requirement for shadow space or red zone when calling the 64-bit APIs for now. But still with or without the shadow space, the discussion below applies. Also note that the CPU honors no calling convention. Align 16 Ecosystem This requirement specifies that for the 64-bit APIs to function correctly it must work in an ecosystem or runtime environment in which the stack memory is always aligned to 16-byte boundaries. -
Protecting Against Unexpected System Calls
Protecting Against Unexpected System Calls C. M. Linn, M. Rajagopalan, S. Baker, C. Collberg, S. K. Debray, J. H. Hartman Department of Computer Science University of Arizona Tucson, AZ 85721 {linnc,mohan,bakers,collberg,debray,jhh}@cs.arizona.edu Abstract writing the return address on the stack with the address of the attack code). This then causes the various actions This paper proposes a comprehensive set of techniques relating to the attack to be carried out. which limit the scope of remote code injection attacks. These techniques prevent any injected code from mak- In order to do any real damage, e.g., create a root ing system calls and thus restrict the capabilities of an shell, change permissions on a file, or access proscribed attacker. In defending against the traditional ways of data, the attack code needs to execute one or more sys- harming a system these techniques significantly raise the tem calls. Because of this, and the well-defined system bar for compromising the host system forcing the attack call interface between application code and the underly- code to take extraordinary steps that may be impractical ing operating system kernel, many researchers have fo- in the context of a remote code injection attack. There cused on the system call interface as a convenient point are two main aspects to our approach. The first is to for detecting and disrupting such attacks (see, for exam- embed semantic information into executables identify- ple, [5, 13, 17, 19, 29, 32, 35, 38]; Section 7 gives a more ing the locations of legitimate system call instructions; extensive discussion). -
Protecting the Stack with Metadata Policies and Tagged Hardware
2018 IEEE Symposium on Security and Privacy Protecting the Stack with Metadata Policies and Tagged Hardware Nick Roessler Andre´ DeHon University of Pennsylvania University of Pennsylvania [email protected] [email protected] Abstract—The program call stack is a major source of ex- stack data, or hijack the exposed function call mechanism in ploitable security vulnerabilities in low-level, unsafe languages a host of other malicious ways. like C. In conventional runtime implementations, the underlying Consequently, protecting the stack abstraction is critical stack data is exposed and unprotected, allowing programming errors to turn into security violations. In this work, we design for application security. Currently deployed defenses such as W X and stack canaries [2] make attacks more difficult to novel metadata-tag based, stack-protection security policies for ⊕ a general-purpose tagged architecture. Our policies specifically conduct, but do not protect against more sophisticated attack exploit the natural locality of dynamic program call graphs to techniques. Full memory safety can be retrofitted onto existing achieve cacheability of the metadata rules that they require. C/C++ code through added software checks, but at a high cost Our simple Return Address Protection policy has a performance overhead of 1.2% but just protects return addresses. The two of 100% or more in runtime overhead [3]. These expensive richer policies we present, Static Authorities and Depth Isola- solutions are unused in practice due to their unacceptably high tion, provide object-level protection for all stack objects. When overheads [4]. enforcing memory safety, our Static Authorities policy has a There is a long history of accelerating security policies with performance overhead of 5.7% and our Depth Isolation policy hardware to bring their overheads to more bearable levels has a performance overhead of 4.5%.