OBJECT-ORIENTED TECHNOLOGY VERIFICATION PHASE 3 REPORT— August 2007 STRUCTURAL COVERAGE at the SOURCE-CODE and OBJECT-CODE LEVELS 6
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Executable Code Is Not the Proper Subject of Copyright Law a Retrospective Criticism of Technical and Legal Naivete in the Apple V
Executable Code is Not the Proper Subject of Copyright Law A retrospective criticism of technical and legal naivete in the Apple V. Franklin case Matthew M. Swann, Clark S. Turner, Ph.D., Department of Computer Science Cal Poly State University November 18, 2004 Abstract: Copyright was created by government for a purpose. Its purpose was to be an incentive to produce and disseminate new and useful knowledge to society. Source code is written to express its underlying ideas and is clearly included as a copyrightable artifact. However, since Apple v. Franklin, copyright has been extended to protect an opaque software executable that does not express its underlying ideas. Common commercial practice involves keeping the source code secret, hiding any innovative ideas expressed there, while copyrighting the executable, where the underlying ideas are not exposed. By examining copyright’s historical heritage we can determine whether software copyright for an opaque artifact upholds the bargain between authors and society as intended by our Founding Fathers. This paper first describes the origins of copyright, the nature of software, and the unique problems involved. It then determines whether current copyright protection for the opaque executable realizes the economic model underpinning copyright law. Having found the current legal interpretation insufficient to protect software without compromising its principles, we suggest new legislation which would respect the philosophy on which copyright in this nation was founded. Table of Contents INTRODUCTION................................................................................................. 1 THE ORIGIN OF COPYRIGHT ........................................................................... 1 The Idea is Born 1 A New Beginning 2 The Social Bargain 3 Copyright and the Constitution 4 THE BASICS OF SOFTWARE .......................................................................... -
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. -
Architectural Support for Scripting Languages
Architectural Support for Scripting Languages By Dibakar Gope A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy (Electrical and Computer Engineering) at the UNIVERSITY OF WISCONSIN–MADISON 2017 Date of final oral examination: 6/7/2017 The dissertation is approved by the following members of the Final Oral Committee: Mikko H. Lipasti, Professor, Electrical and Computer Engineering Gurindar S. Sohi, Professor, Computer Sciences Parameswaran Ramanathan, Professor, Electrical and Computer Engineering Jing Li, Assistant Professor, Electrical and Computer Engineering Aws Albarghouthi, Assistant Professor, Computer Sciences © Copyright by Dibakar Gope 2017 All Rights Reserved i This thesis is dedicated to my parents, Monoranjan Gope and Sati Gope. ii acknowledgments First and foremost, I would like to thank my parents, Sri Monoranjan Gope, and Smt. Sati Gope for their unwavering support and encouragement throughout my doctoral studies which I believe to be the single most important contribution towards achieving my goal of receiving a Ph.D. Second, I would like to express my deepest gratitude to my advisor Prof. Mikko Lipasti for his mentorship and continuous support throughout the course of my graduate studies. I am extremely grateful to him for guiding me with such dedication and consideration and never failing to pay attention to any details of my work. His insights, encouragement, and overall optimism have been instrumental in organizing my otherwise vague ideas into some meaningful contributions in this thesis. This thesis would never have been accomplished without his technical and editorial advice. I find myself fortunate to have met and had the opportunity to work with such an all-around nice person in addition to being a great professor. -
Opportunities and Open Problems for Static and Dynamic Program Analysis Mark Harman∗, Peter O’Hearn∗ ∗Facebook London and University College London, UK
1 From Start-ups to Scale-ups: Opportunities and Open Problems for Static and Dynamic Program Analysis Mark Harman∗, Peter O’Hearn∗ ∗Facebook London and University College London, UK Abstract—This paper1 describes some of the challenges and research questions that target the most productive intersection opportunities when deploying static and dynamic analysis at we have yet witnessed: that between exciting, intellectually scale, drawing on the authors’ experience with the Infer and challenging science, and real-world deployment impact. Sapienz Technologies at Facebook, each of which started life as a research-led start-up that was subsequently deployed at scale, Many industrialists have perhaps tended to regard it unlikely impacting billions of people worldwide. that much academic work will prove relevant to their most The paper identifies open problems that have yet to receive pressing industrial concerns. On the other hand, it is not significant attention from the scientific community, yet which uncommon for academic and scientific researchers to believe have potential for profound real world impact, formulating these that most of the problems faced by industrialists are either as research questions that, we believe, are ripe for exploration and that would make excellent topics for research projects. boring, tedious or scientifically uninteresting. This sociological phenomenon has led to a great deal of miscommunication between the academic and industrial sectors. I. INTRODUCTION We hope that we can make a small contribution by focusing on the intersection of challenging and interesting scientific How do we transition research on static and dynamic problems with pressing industrial deployment needs. Our aim analysis techniques from the testing and verification research is to move the debate beyond relatively unhelpful observations communities to industrial practice? Many have asked this we have typically encountered in, for example, conference question, and others related to it. -
Addresssanitizer + Code Coverage Kostya Serebryany, Google Eurollvm 2014 New and Shiny -Fprofile-Instr-Generate
AddressSanitizer + Code Coverage Kostya Serebryany, Google EuroLLVM 2014 New and shiny -fprofile-instr-generate ● Coming this year ● Fast BB-level code coverage ● Increment a counter per every (*) BB ○ Possible contention on counters ● Creates special non-code sections ○ Counters ○ Function names, line numbers Meanwhile: ASanCoverage ● Tiny prototype-ish thing: ○ Part of AddressSanitizer ○ 30 lines in LLVM, 100 in run-time ● Function- or BB- level coverage ○ Booleans only, not counters ○ No contention ○ No extra sections in the binary At compile time: if (!*BB_Guard) { __sanitizer_cov(); *BB_Guard = 1; } At run time void __sanitizer_cov() { Record(GET_CALLER_PC()); } At exit time ● For every binary/DSO in the process: ○ Dump observed PCs in a separate file as 4-byte offsets At analysis time ● Compare/Merge using 20 lines of python ● Symbolize using regular DWARF % cat cov.c int main() { } % clang -g -fsanitize=address -mllvm -asan-coverage=1 cov. c % ASAN_OPTIONS=coverage=1 ./a.out % wc -c *sancov 4 a.out.15751.sancov % sancov.py print a.out.15751.sancov sancov.py: read 1 PCs from a.out.15751.sancov sancov.py: 1 files merged; 1 PCs total 0x4850b7 % sancov.py print *.sancov | llvm-symbolizer --obj=a.out main /tmp/cov.c:1:0 Fuzzing with coverage feedback ● Test corpus: N random tests ● Randomly mutate random test ○ If new BB is covered -- add this test to the corpus ● Many new bugs in well fuzzed projects! Feedback from our customers ● Speed is paramount ● Binary size is important ○ Permanent & temporary storage, tmps, I/O ○ Stripping non-code -
CDC Build System Guide
CDC Build System Guide Java™ Platform, Micro Edition Connected Device Configuration, Version 1.1.2 Foundation Profile, Version 1.1.2 Optimized Implementation Sun Microsystems, Inc. www.sun.com December 2008 Copyright © 2008 Sun Microsystems, Inc., 4150 Network Circle, Santa Clara, California 95054, U.S.A. All rights reserved. Sun Microsystems, Inc. has intellectual property rights relating to technology embodied in the product that is described in this document. In particular, and without limitation, these intellectual property rights may include one or more of the U.S. patents listed at http://www.sun.com/patents and one or more additional patents or pending patent applications in the U.S. and in other countries. U.S. Government Rights - Commercial software. Government users are subject to the Sun Microsystems, Inc. standard license agreement and applicable provisions of the FAR and its supplements. This distribution may include materials developed by third parties. Parts of the product may be derived from Berkeley BSD systems, licensed from the University of California. UNIX is a registered trademark in the U.S. and in other countries, exclusively licensed through X/Open Company, Ltd. Sun, Sun Microsystems, the Sun logo, Java, Solaris and HotSpot are trademarks or registered trademarks of Sun Microsystems, Inc. or its subsidiaries in the United States and other countries. The Adobe logo is a registered trademark of Adobe Systems, Incorporated. Products covered by and information contained in this service manual are controlled by U.S. Export Control laws and may be subject to the export or import laws in other countries. Nuclear, missile, chemical biological weapons or nuclear maritime end uses or end users, whether direct or indirect, are strictly prohibited. -
Using Ld the GNU Linker
Using ld The GNU linker ld version 2 January 1994 Steve Chamberlain Cygnus Support Cygnus Support [email protected], [email protected] Using LD, the GNU linker Edited by Jeffrey Osier (jeff[email protected]) Copyright c 1991, 92, 93, 94, 95, 96, 97, 1998 Free Software Foundation, Inc. Permission is granted to make and distribute verbatim copies of this manual provided the copyright notice and this permission notice are preserved on all copies. Permission is granted to copy and distribute modified versions of this manual under the conditions for verbatim copying, provided also that the entire resulting derived work is distributed under the terms of a permission notice identical to this one. Permission is granted to copy and distribute translations of this manual into another lan- guage, under the above conditions for modified versions. Chapter 1: Overview 1 1 Overview ld combines a number of object and archive files, relocates their data and ties up symbol references. Usually the last step in compiling a program is to run ld. ld accepts Linker Command Language files written in a superset of AT&T’s Link Editor Command Language syntax, to provide explicit and total control over the linking process. This version of ld uses the general purpose BFD libraries to operate on object files. This allows ld to read, combine, and write object files in many different formats—for example, COFF or a.out. Different formats may be linked together to produce any available kind of object file. See Chapter 5 [BFD], page 47, for more information. Aside from its flexibility, the gnu linker is more helpful than other linkers in providing diagnostic information. -
A Zero Kernel Operating System: Rethinking Microkernel Design by Leveraging Tagged Architectures and Memory-Safe Languages
A Zero Kernel Operating System: Rethinking Microkernel Design by Leveraging Tagged Architectures and Memory-Safe Languages by Justin Restivo B.S., Massachusetts Institute of Technology (2019) Submitted to the Department of Electrical Engineering and Computer Science in partial fulfillment of the requirements for the degree of Masters of Engineering in Computer Science and Engineering at the MASSACHUSETTS INSTITUTE OF TECHNOLOGY February 2020 © Massachusetts Institute of Technology 2020. All rights reserved. Author............................................................................ Department of Electrical Engineering and Computer Science January 29, 2020 Certified by....................................................................... Dr. Howard Shrobe Principal Research Scientist, MIT CSAIL Thesis Supervisor Certified by....................................................................... Dr. Hamed Okhravi Senior Staff Member, MIT Lincoln Laboratory Thesis Supervisor Certified by....................................................................... Dr. Samuel Jero Technical Staff, MIT Lincoln Laboratory Thesis Supervisor Accepted by...................................................................... Katrina LaCurts Chair, Master of Engineering Thesis Committee DISTRIBUTION STATEMENT A. Approved for public release. Distribution is unlimited. This material is based upon work supported by the Assistant Secretary of Defense for Research and Engineering under Air Force Contract No. FA8702-15-D-0001. Any opinions, findings, conclusions -
Guidelines on Minimum Standards for Developer Verification of Software
Guidelines on Minimum Standards for Developer Verification of Software Paul E. Black Barbara Guttman Vadim Okun Software and Systems Division Information Technology Laboratory July 2021 Abstract Executive Order (EO) 14028, Improving the Nation’s Cybersecurity, 12 May 2021, di- rects the National Institute of Standards and Technology (NIST) to recommend minimum standards for software testing within 60 days. This document describes eleven recommen- dations for software verification techniques as well as providing supplemental information about the techniques and references for further information. It recommends the following techniques: • Threat modeling to look for design-level security issues • Automated testing for consistency and to minimize human effort • Static code scanning to look for top bugs • Heuristic tools to look for possible hardcoded secrets • Use of built-in checks and protections • “Black box” test cases • Code-based structural test cases • Historical test cases • Fuzzing • Web app scanners, if applicable • Address included code (libraries, packages, services) The document does not address the totality of software verification, but instead recom- mends techniques that are broadly applicable and form the minimum standards. The document was developed by NIST in consultation with the National Security Agency. Additionally, we received input from numerous outside organizations through papers sub- mitted to a NIST workshop on the Executive Order held in early June, 2021 and discussion at the workshop as well as follow up with several of the submitters. Keywords software assurance; verification; testing; static analysis; fuzzing; code review; software security. Disclaimer Any mention of commercial products or reference to commercial organizations is for infor- mation only; it does not imply recommendation or endorsement by NIST, nor is it intended to imply that the products mentioned are necessarily the best available for the purpose. -
Optimizing Function Placement for Large-Scale Data-Center Applications
Optimizing Function Placement for Large-Scale Data-Center Applications Guilherme Ottoni Bertrand Maher Facebook, Inc., USA ottoni,bertrand @fb.com { } Abstract While the large size and performance criticality of such Modern data-center applications often comprise a large applications make them good candidates for profile-guided amount of code, with substantial working sets, making them code-layout optimizations, these characteristics also im- good candidates for code-layout optimizations. Although pose scalability challenges to optimize these applications. recent work has evaluated the impact of profile-guided intra- Instrumentation-based profilers significantly slow down the module optimizations and some cross-module optimiza- applications, often making it impractical to gather accurate tions, no recent study has evaluated the benefit of function profiles from a production system. To simplify deployment, placement for such large-scale applications. In this paper, it is beneficial to have a system that can profile unmodi- we study the impact of function placement in the context fied binaries, running in production, and use these data for of a simple tool we created that uses sample-based profiling feedback-directed optimization. This is possible through the data. By using sample-based profiling, this methodology fol- use of sample-based profiling, which enables high-quality lows the same principle behind AutoFDO, i.e. using profil- profiles to be gathered with minimal operational complexity. ing data collected from unmodified binaries running in pro- This is the approach taken by tools such as AutoFDO [1], duction, which makes it applicable to large-scale binaries. and which we also follow in this work. Using this tool, we first evaluate the impact of the traditional The benefit of feedback-directed optimizations for some Pettis-Hansen (PH) function-placement algorithm on a set of data-center applications has been evaluated in some pre- widely deployed data-center applications. -
LLVM, Clang and Embedded Linux Systems
LLVM, Clang and Embedded Linux Systems Bruno Cardoso Lopes University of Campinas What’s LLVM? What’s LLVM • Compiler infrastructure To o l s Frontend Optimizer IR Assembler Backends (clang) Disassembler JIT What’s LLVM • Virtual Instruction set (IR) • SSA • Bitcode C source code IR Frontend int add(int x, int y) { define i32 @add(i32 %x, i32 %y) { return x+y; Clang %1 = add i32 %y, %x } ret i32 %1 } What’s LLVM • Optimization oriented compiler: compile time, link-time and run-time • More than 30 analysis passes and 60 transformation passes. Why LLVM? Why LLVM? • Open Source • Active community • Easy integration and quick patch review Why LLVM? • Code easy to read and understand • Transformations and optimizations are applied in several parts during compilation Design Design • Written in C++ • Modular and composed of several libraries • Pass mechanism with pluggable interface for transformations and analysis • Several tools for each part of compilation To o l s To o l s Front-end • Dragonegg • Gcc 4.5 plugin • llvm-gcc • GIMPLE to LLVM IR To o l s Front-end • Clang • Library approach • No cross-compiler generation needed • Good diagnostics • Static Analyzer To o l s Optimizer • Optimization are applied to the IR • opt tool $ opt -O3 add.bc -o add2.bc optimizations Aggressive Dead Code Elmination Tail Call Elimination Combine Redudant Instructions add.bc add2.bc Dead Argument Elimination Type-Based Alias Analysis ... To o l s Low Level Compiler • llc tool: invoke the static backends • Generates assembly or object code $ llc -march=arm add.bc -
Compiling.Pdf
CS50 Compiling Overview Key Terms Compiling is the process of translating source code, which is the code that you write in • compiling a programming language like C, and translating it into machine code: the sequence of • machine code 0s and 1s that a computer's central processing unit (CPU) can understand as instruc- • preprocessing tions for how to execute the program. Although the command make is used to compile • assembly code, make itself is not a compiler. Instead, make calls upon the underlying compiler • object code in order to compile C source code into object code. clang • linking Preprocessing The entire compilation process can be broken down into four steps. The first Source Code step is preprocessing, performed by a program called the preprocessor. Any source code in C that begins with a # is a signal to the preprocessor to perform some action. Preprocessing For example, #include tells the preprocessor to literally include the contents of a different file in the preprocessed file. When a program includes a line like #include <stdio.h> in the source code, the preprocessor generates a new file (still in C, and still considered source code), but with the #include line Preprocessed replaced by the entire contents of stdio.h. Source Code Compiling After the preprocessor produces preprocessed source code, the next step Compiling is to compile (using a program called a compiler) C code into a lower-level programming language known as assembly. Assembly has far fewer different types of operations than C does, but by Assembly using them in conjunction, can still perform the same tasks that C can.