Obfuscating Java Programs by Translating Selected Portions of Bytecode to Native Libraries
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The LLVM Instruction Set and Compilation Strategy
The LLVM Instruction Set and Compilation Strategy Chris Lattner Vikram Adve University of Illinois at Urbana-Champaign lattner,vadve ¡ @cs.uiuc.edu Abstract This document introduces the LLVM compiler infrastructure and instruction set, a simple approach that enables sophisticated code transformations at link time, runtime, and in the field. It is a pragmatic approach to compilation, interfering with programmers and tools as little as possible, while still retaining extensive high-level information from source-level compilers for later stages of an application’s lifetime. We describe the LLVM instruction set, the design of the LLVM system, and some of its key components. 1 Introduction Modern programming languages and software practices aim to support more reliable, flexible, and powerful software applications, increase programmer productivity, and provide higher level semantic information to the compiler. Un- fortunately, traditional approaches to compilation either fail to extract sufficient performance from the program (by not using interprocedural analysis or profile information) or interfere with the build process substantially (by requiring build scripts to be modified for either profiling or interprocedural optimization). Furthermore, they do not support optimization either at runtime or after an application has been installed at an end-user’s site, when the most relevant information about actual usage patterns would be available. The LLVM Compilation Strategy is designed to enable effective multi-stage optimization (at compile-time, link-time, runtime, and offline) and more effective profile-driven optimization, and to do so without changes to the traditional build process or programmer intervention. LLVM (Low Level Virtual Machine) is a compilation strategy that uses a low-level virtual instruction set with rich type information as a common code representation for all phases of compilation. -
Scala: a Functional, Object-Oriented Language COEN 171 Darren Atkinson What Is Scala? Scala Stands for Scalable Language It Was Created in 2004 by Martin Odersky
Scala: A Functional, Object-Oriented Language COEN 171 Darren Atkinson What is Scala? Scala stands for Scalable Language It was created in 2004 by Martin Odersky. It was designed to grow with the demands of its users. It was designed to overcome many criticisms of Java. It is compiled to Java bytecode and is interoperable with existing Java classes and libraries. It is more of a high-level language than Java, having higher- order containers and iteration constructs built-in. It encourages a functional programming style, much like ML and Scheme. It also has advanced object-oriented features, much like Java and C++. Using Scala Using Scala is much like using Python or ML, and is not as unwieldy as using Java. The Scala interpreter can be invoked directly from the command line: $ scala Welcome to Scala 2.11.8 scala> println("Hi!") The Scala interpreter can also be given a file on the command line to execute: $ scala foo.scala Scala Syntax Scala has a Java-like syntax with braces. The assignment operator is simply =. Strings are built-in and use + for concatenation. Indexing is done using ( ) rather than [ ]. The first index is index zero. Parameterized types use [ ] rather than < >. A semicolon is inferred at the end of a line. However, since it is functional, everything is an expression and there are no “statements”. Scala Types In Java, the primitive types are not objects and wrapper classes must be used. Integer for int, Boolean for bool, etc. In Scala, everything is an object including the more “primitive” types. The Scala types are Int, Boolean, String, etc. -
The Interplay of Compile-Time and Run-Time Options for Performance Prediction Luc Lesoil, Mathieu Acher, Xhevahire Tërnava, Arnaud Blouin, Jean-Marc Jézéquel
The Interplay of Compile-time and Run-time Options for Performance Prediction Luc Lesoil, Mathieu Acher, Xhevahire Tërnava, Arnaud Blouin, Jean-Marc Jézéquel To cite this version: Luc Lesoil, Mathieu Acher, Xhevahire Tërnava, Arnaud Blouin, Jean-Marc Jézéquel. The Interplay of Compile-time and Run-time Options for Performance Prediction. SPLC 2021 - 25th ACM Inter- national Systems and Software Product Line Conference - Volume A, Sep 2021, Leicester, United Kingdom. pp.1-12, 10.1145/3461001.3471149. hal-03286127 HAL Id: hal-03286127 https://hal.archives-ouvertes.fr/hal-03286127 Submitted on 15 Jul 2021 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. The Interplay of Compile-time and Run-time Options for Performance Prediction Luc Lesoil, Mathieu Acher, Xhevahire Tërnava, Arnaud Blouin, Jean-Marc Jézéquel Univ Rennes, INSA Rennes, CNRS, Inria, IRISA Rennes, France [email protected] ABSTRACT Both compile-time and run-time options can be configured to reach Many software projects are configurable through compile-time op- specific functional and performance goals. tions (e.g., using ./configure) and also through run-time options (e.g., Existing studies consider either compile-time or run-time op- command-line parameters, fed to the software at execution time). -
Design and Implementation of Generics for the .NET Common Language Runtime
Design and Implementation of Generics for the .NET Common Language Runtime Andrew Kennedy Don Syme Microsoft Research, Cambridge, U.K. fakeÒÒ¸d×ÝÑeg@ÑicÖÓ×ÓfغcÓÑ Abstract cally through an interface definition language, or IDL) that is nec- essary for language interoperation. The Microsoft .NET Common Language Runtime provides a This paper describes the design and implementation of support shared type system, intermediate language and dynamic execution for parametric polymorphism in the CLR. In its initial release, the environment for the implementation and inter-operation of multiple CLR has no support for polymorphism, an omission shared by the source languages. In this paper we extend it with direct support for JVM. Of course, it is always possible to “compile away” polymor- parametric polymorphism (also known as generics), describing the phism by translation, as has been demonstrated in a number of ex- design through examples written in an extended version of the C# tensions to Java [14, 4, 6, 13, 2, 16] that require no change to the programming language, and explaining aspects of implementation JVM, and in compilers for polymorphic languages that target the by reference to a prototype extension to the runtime. JVM or CLR (MLj [3], Haskell, Eiffel, Mercury). However, such Our design is very expressive, supporting parameterized types, systems inevitably suffer drawbacks of some kind, whether through polymorphic static, instance and virtual methods, “F-bounded” source language restrictions (disallowing primitive type instanti- type parameters, instantiation at pointer and value types, polymor- ations to enable a simple erasure-based translation, as in GJ and phic recursion, and exact run-time types. -
Adding Self-Healing Capabilities to the Common Language Runtime
Adding Self-healing capabilities to the Common Language Runtime Rean Griffith Gail Kaiser Columbia University Columbia University [email protected] [email protected] Abstract systems can leverage to maintain high system availability is to perform repairs in a degraded mode of operation[23, 10]. Self-healing systems require that repair mechanisms are Conceptually, a self-managing system is composed of available to resolve problems that arise while the system ex- four (4) key capabilities [12]; Monitoring to collect data ecutes. Managed execution environments such as the Com- about its execution and operating environment, performing mon Language Runtime (CLR) and Java Virtual Machine Analysis over the data collected from monitoring, Planning (JVM) provide a number of application services (applica- an appropriate course of action and Executing the plan. tion isolation, security sandboxing, garbage collection and Each of the four functions participating in the Monitor- structured exception handling) which are geared primar- Analyze-Plan-Execute (MAPE) loop consumes and pro- ily at making managed applications more robust. How- duces knowledgewhich is integral to the correct functioning ever, none of these services directly enables applications of the system. Over its execution lifetime the system builds to perform repairs or consistency checks of their compo- and refines a knowledge-base of its behavior and environ- nents. From a design and implementation standpoint, the ment. Information in the knowledge-base could include preferred way to enable repair in a self-healing system is patterns of resource utilization and a “scorecard” tracking to use an externalized repair/adaptation architecture rather the success of applying specific repair actions to detected or than hardwiring adaptation logic inside the system where it predicted problems. -
Nashorn Architecture and Performance Improvements in the Upcoming JDK 8U40 Release
Oracle Blogs Home Products & Services Downloads Support Partners Communities About Login Oracle Blog Nashorn JavaScript for the JVM. Nashorn architecture and performance improvements in the upcoming JDK 8u40 release By lagergren on Dec 12, 2014 Hello everyone! We've been bad att blogging here for a while. Apologizes for that. I thought it would be prudent to talk a little bit about OpenJDK 8u40 which is now code frozen, and what enhancements we have made for Nashorn. 8u40 includes a total rewrite of the Nashorn code generator, which now contains the optimistic type system. JavaScript, or any dynamic language for that matter, doesn't have enough statically available type information to provide performant code, just by doing compile time analysis. That's why we have designed the new type system to get around this performance bottleneck. While Java bytecode, which is the output of the Nashorn JIT, is strongly typed and JavaScript isn't, there are problems translating the AST to optimal bytecode. Attila Szegedi, Hannes Wallnöfer and myself have spent significant time researching and implementing this the last year. Background: Conservatively, when implementing a JavaScript runtime in Java, anything known to be a number can be represented in Java as a double, and everything else can be represented as an Object. This includes numbers, ints, longs and other primitive types that aren't statically provable. Needless to say, this approach leads to a lot of internal boxing, which is quite a bottleneck for dynamic language execution speed on the JVM. The JVM is very good at optimizing Java-like bytecode, and this is not Java-like bytecode. -
Java in Embedded Linux Systems
Java in Embedded Linux Systems Java in Embedded Linux Systems Thomas Petazzoni / Michael Opdenacker Free Electrons http://free-electrons.com/ Created with OpenOffice.org 2.x Java in Embedded Linux Systems © Copyright 2004-2007, Free Electrons, Creative Commons Attribution-ShareAlike 2.5 license http://free-electrons.com Sep 15, 2009 1 Rights to copy Attribution ± ShareAlike 2.5 © Copyright 2004-2008 You are free Free Electrons to copy, distribute, display, and perform the work [email protected] to make derivative works to make commercial use of the work Document sources, updates and translations: Under the following conditions http://free-electrons.com/articles/java Attribution. You must give the original author credit. Corrections, suggestions, contributions and Share Alike. If you alter, transform, or build upon this work, you may distribute the resulting work only under a license translations are welcome! identical to this one. For any reuse or distribution, you must make clear to others the license terms of this work. Any of these conditions can be waived if you get permission from the copyright holder. Your fair use and other rights are in no way affected by the above. License text: http://creativecommons.org/licenses/by-sa/2.5/legalcode Java in Embedded Linux Systems © Copyright 2004-2007, Free Electrons, Creative Commons Attribution-ShareAlike 2.5 license http://free-electrons.com Sep 15, 2009 2 Best viewed with... This document is best viewed with a recent PDF reader or with OpenOffice.org itself! Take advantage of internal -
18Mca42c .Net Programming (C#)
18MCA42C .NET PROGRAMMING (C#) Introduction to .NET Framework .NET is a software framework which is designed and developed by Microsoft. The first version of .Net framework was 1.0 which came in the year 2002. It is a virtual machine for compiling and executing programs written in different languages like C#, VB.Net etc. It is used to develop Form-based applications, Web-based applications, and Web services. There is a variety of programming languages available on the .Net platform like VB.Net and C# etc.,. It is used to build applications for Windows, phone, web etc. It provides a lot of functionalities and also supports industry standards. .NET Framework supports more than 60 programming languages in which 11 programming languages are designed and developed by Microsoft. 11 Programming Languages which are designed and developed by Microsoft are: C#.NET VB.NET C++.NET J#.NET F#.NET JSCRIPT.NET WINDOWS POWERSHELL IRON RUBY IRON PYTHON C OMEGA ASML(Abstract State Machine Language) Main Components of .NET Framework 1.Common Language Runtime(CLR): CLR is the basic and Virtual Machine component of the .NET Framework. It is the run-time environment in the .NET Framework that runs the codes and helps in making the development process easier by providing the various services such as remoting, thread management, type-safety, memory management, robustness etc.. Basically, it is responsible for managing the execution of .NET programs regardless of any .NET programming language. It also helps in the management of code, as code that targets the runtime is known as the Managed Code and code doesn’t target to runtime is known as Unmanaged code. -
Dmon: Efficient Detection and Correction of Data Locality
DMon: Efficient Detection and Correction of Data Locality Problems Using Selective Profiling Tanvir Ahmed Khan and Ian Neal, University of Michigan; Gilles Pokam, Intel Corporation; Barzan Mozafari and Baris Kasikci, University of Michigan https://www.usenix.org/conference/osdi21/presentation/khan This paper is included in the Proceedings of the 15th USENIX Symposium on Operating Systems Design and Implementation. July 14–16, 2021 978-1-939133-22-9 Open access to the Proceedings of the 15th USENIX Symposium on Operating Systems Design and Implementation is sponsored by USENIX. DMon: Efficient Detection and Correction of Data Locality Problems Using Selective Profiling Tanvir Ahmed Khan Ian Neal Gilles Pokam Barzan Mozafari University of Michigan University of Michigan Intel Corporation University of Michigan Baris Kasikci University of Michigan Abstract cally at run time. In fact, as we (§6.2) and others [2,15,20,27] Poor data locality hurts an application’s performance. While demonstrate, compiler-based techniques can sometimes even compiler-based techniques have been proposed to improve hurt performance when the assumptions made by those heuris- data locality, they depend on heuristics, which can sometimes tics do not hold in practice. hurt performance. Therefore, developers typically find data To overcome the limitations of static optimizations, the locality issues via dynamic profiling and repair them manually. systems community has invested substantial effort in devel- Alas, existing profiling techniques incur high overhead when oping dynamic profiling tools [28,38, 57,97, 102]. Dynamic used to identify data locality problems and cannot be deployed profilers are capable of gathering detailed and more accurate in production, where programs may exhibit previously-unseen execution information, which a developer can use to identify performance problems. -
Evaluation of Clojure, Java, and Scala
Evaluation of Clojure, Java, and Scala Analysis of Programming Languages TTÜ Toke Abildgaard von Ryberg 10.12.2015 Evaluation of Clojure, Java, and Scala 10.12.2015 Analysis of Programming Languages Toke Abildgaard von Ryberg Introduction Java Virtual Machine Java Scala Clojure Programming languages evaluation Essential characteristics Well defined syntactic and semantic definition of language Reliability Fast translation Machine independence Desirable characteristics Generality Consistency with commonly used notations Uniformity Extensibility (ease to add features) Summary References 2 Evaluation of Clojure, Java, and Scala 10.12.2015 Analysis of Programming Languages Toke Abildgaard von Ryberg Introduction In this paper I will evaluate three languages that all uses Java Virtual Machine (JVM). The three languages are Clojure, Java, and Scala. First, I will briefly describe JVM and the three languages. Then I will evaluate the languages based on essential characteristics and desirable characteristics. The essential characteristics I use for evaluating programming languages are: ● Well defined syntactic and semantic definition of language ● Reliability ● Fast translation ● Machine independence The desirable characteristics are: ● Generality ● Consistency with commonly used notations ● Uniformity ● Extensibility (ease to add features) Java Virtual Machine1 The Java Virtual Machine(JVM) is a virtual machine used for executing Java bytecode. JVM is part of Java Runtime Environment(JRE) along with Java Class library. JRE is available on multiple platforms including Windows, Mac OS X, and Linux. The features of JVM include garbage collection and a JIT compiler. A programming language with functionality expressed in valid class files and able to be hosted by JVM is called a JVM language. When choosing to create a new programming language one might choose to create a JVM language to take advantage of the features of JVM. -
Java and C I CSE 351 Autumn 2016
L26: JVM CSE351, Spring 2018 Java Virtual Machine CSE 351 Spring 2018 Model of a Computer “Showing the Weather” Pencil and Crayon on Paper Matai Feldacker-Grossman, Age 4 May 22, 2018 L26: JVM CSE351, Spring 2018 Roadmap C: Java: Memory & data Integers & floats car *c = malloc(sizeof(car)); Car c = new Car(); x86 assembly c->miles = 100; c.setMiles(100); c->gals = 17; c.setGals(17); Procedures & stacks float mpg = get_mpg(c); float mpg = Executables free(c); c.getMPG(); Arrays & structs Memory & caches Assembly get_mpg: Processes language: pushq %rbp Virtual memory movq %rsp, %rbp ... Memory allocation popq %rbp Java vs. C ret OS: Machine 0111010000011000 code: 100011010000010000000010 1000100111000010 110000011111101000011111 Computer system: 2 L26: JVM CSE351, Spring 2018 Implementing Programming Languages Many choices in how to implement programming models We’ve talked about compilation, can also interpret Interpreting languages has a long history . Lisp, an early programming language, was interpreted Interpreters are still in common use: . Python, Javascript, Ruby, Matlab, PHP, Perl, … Interpreter Your source code implementation Your source code Binary executable Interpreter binary Hardware Hardware 3 L26: JVM CSE351, Spring 2018 An Interpreter is a Program Execute (something close to) the source code directly Simpler/no compiler – less translation More transparent to debug – less translation Easier to run on different architectures – runs in a simulated environment that exists only inside the interpreter process . Just port the interpreter (program), not the program-intepreted Slower and harder to optimize 4 L26: JVM CSE351, Spring 2018 Interpreter vs. Compiler An aspect of a language implementation . A language can have multiple implementations . Some might be compilers and other interpreters “Compiled languages” vs. -
Compile Time and Runtime
COMPILE TIME AND RUNTIME Compile time and runtime are two distinctly different times during the active life of a computer program. Compile time is when the program is compiled; runtime is when it executes (on either a physical or virtual computer). Programmers use the term static to refer to anything that is created during compile time and stays fixed during the program run. They use the term dynamic to refer to things that are created and can change during execution. Example In application MyApp shown below, the data type of variable tax is statically set to double for the entire program run. Its value is dynamically set when the assignment statement (marked **) executes. public class MyApp { public static void main( String [] args ) { double tax; . ** tax = price * TAX_RATE; . } } Compiler Tasks The main tasks of the compiler are to: Check program statements for errors and report them. Generate the machine instructions that carry out the operations specified by the program. To do this, the compiler must gather as much information as possible about the items (e.g. variables, classes, objects, etc.) used in the program. Compile Time and Runtime Page 1 Example Consider this Java assignment statement: x = y2 + z; To determine if it is correct, the compiler needs to know if y2 is a declared variable (perhaps the programmer meant to type y*2). To generate correct bytecode, the compiler needs to know the data types of the variables (integer addition is a different machine instruction than floating-point addition). Declarations Program text that is primarily meant to provide information to the compiler is called a declaration, which the compiler processes by collecting the information given.