Mempick: High-Level Data Structure Detection in C/C++ Binaries
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Top-K Entity Resolution with Adaptive Locality-Sensitive Hashing
Top-K Entity Resolution with Adaptive Locality-Sensitive Hashing Vasilis Verroios Hector Garcia-Molina Stanford University Stanford University [email protected] [email protected] ABSTRACT Given a set of records, entity resolution algorithms find all the records referring to each entity. In this paper, we study Entity 1 the problem of top-k entity resolution: finding all the records Entity 2 referring to the k largest (in terms of records) entities. Top-k Top-k Entity entity resolution is driven by many modern applications that Dataset Filtering Entities’ Records Resolution operate over just the few most popular entities in a dataset. We propose a novel approach, based on locality-sensitive hashing, that can very rapidly and accurately process mas- Entity k sive datasets. Our key insight is to adaptively decide how much processing each record requires to ascertain if it refers to a top-k entity or not: the less likely a record is to refer to Figure 1: Filtering stage in the overall workflow. a top-k entity, the less it is processed. The heavily reduced rest. As we will see, this fact makes it easier to find the top- amount of processing for the vast majority of records that k entities without computing all entities. We next illustrate do not refer to top-k entities, leads to significant speedups. two additional applications where one typically only needs Our experiments with images, web articles, and scientific top-k entities. Incidentally, two of the datasets we use for publications show a 2x to 25x speedup compared to the tra- our experiments are from these applications. -
C Programming: Data Structures and Algorithms
C Programming: Data Structures and Algorithms An introduction to elementary programming concepts in C Jack Straub, Instructor Version 2.07 DRAFT C Programming: Data Structures and Algorithms, Version 2.07 DRAFT C Programming: Data Structures and Algorithms Version 2.07 DRAFT Copyright © 1996 through 2006 by Jack Straub ii 08/12/08 C Programming: Data Structures and Algorithms, Version 2.07 DRAFT Table of Contents COURSE OVERVIEW ........................................................................................ IX 1. BASICS.................................................................................................... 13 1.1 Objectives ...................................................................................................................................... 13 1.2 Typedef .......................................................................................................................................... 13 1.2.1 Typedef and Portability ............................................................................................................. 13 1.2.2 Typedef and Structures .............................................................................................................. 14 1.2.3 Typedef and Functions .............................................................................................................. 14 1.3 Pointers and Arrays ..................................................................................................................... 16 1.4 Dynamic Memory Allocation ..................................................................................................... -
Solving the Funarg Problem with Static Types IFL ’21, September 01–03, 2021, Online
Solving the Funarg Problem with Static Types Caleb Helbling Fırat Aksoy [email protected] fi[email protected] Purdue University Istanbul University West Lafayette, Indiana, USA Istanbul, Turkey ABSTRACT downwards. The upwards funarg problem refers to the manage- The difficulty associated with storing closures in a stack-based en- ment of the stack when a function returns another function (that vironment is known as the funarg problem. The funarg problem may potentially have a non-empty closure), whereas the down- was first identified with the development of Lisp in the 1970s and wards funarg problem refers to the management of the stack when hasn’t received much attention since then. The modern solution a function is passed to another function (that may also have a non- taken by most languages is to allocate closures on the heap, or to empty closure). apply static analysis to determine when closures can be stack allo- Solving the upwards funarg problem is considered to be much cated. This is not a problem for most computing systems as there is more difficult than the downwards funarg problem. The downwards an abundance of memory. However, embedded systems often have funarg problem is easily solved by copying the closure’s lexical limited memory resources where heap allocation may cause mem- scope (captured variables) to the top of the program’s stack. For ory fragmentation. We present a simple extension to the prenex the upwards funarg problem, an issue arises with deallocation. A fragment of System F that allows closures to be stack-allocated. returning function may capture local variables, making the size of We demonstrate a concrete implementation of this system in the the closure dynamic. -
Open Data Structures (In Java)
Open Data Structures (in Java) Edition 0.1G Pat Morin Contents Acknowledgments ix Why This Book? xi 1 Introduction 1 1.1 The Need for Efficiency ..................... 2 1.2 Interfaces ............................. 4 1.2.1 The Queue, Stack, and Deque Interfaces . 5 1.2.2 The List Interface: Linear Sequences . 6 1.2.3 The USet Interface: Unordered Sets .......... 8 1.2.4 The SSet Interface: Sorted Sets ............ 9 1.3 Mathematical Background ................... 9 1.3.1 Exponentials and Logarithms . 10 1.3.2 Factorials ......................... 11 1.3.3 Asymptotic Notation . 12 1.3.4 Randomization and Probability . 15 1.4 The Model of Computation ................... 18 1.5 Correctness, Time Complexity, and Space Complexity . 19 1.6 Code Samples .......................... 22 1.7 List of Data Structures ..................... 22 1.8 Discussion and Exercises .................... 26 2 Array-Based Lists 29 2.1 ArrayStack: Fast Stack Operations Using an Array . 30 2.1.1 The Basics ........................ 30 2.1.2 Growing and Shrinking . 33 2.1.3 Summary ......................... 35 Contents 2.2 FastArrayStack: An Optimized ArrayStack . 35 2.3 ArrayQueue: An Array-Based Queue . 36 2.3.1 Summary ......................... 40 2.4 ArrayDeque: Fast Deque Operations Using an Array . 40 2.4.1 Summary ......................... 43 2.5 DualArrayDeque: Building a Deque from Two Stacks . 43 2.5.1 Balancing ......................... 47 2.5.2 Summary ......................... 49 2.6 RootishArrayStack: A Space-Efficient Array Stack . 49 2.6.1 Analysis of Growing and Shrinking . 54 2.6.2 Space Usage ....................... 54 2.6.3 Summary ......................... 55 2.6.4 Computing Square Roots . 56 2.7 Discussion and Exercises ................... -
Kernel Extensions and Device Support Programming Concepts
Bull Kernel Extensions and Device Support Programming Concepts AIX ORDER REFERENCE 86 A2 36JX 02 Bull Kernel Extensions and Device Support Programming Concepts AIX Software November 1999 BULL ELECTRONICS ANGERS CEDOC 34 Rue du Nid de Pie – BP 428 49004 ANGERS CEDEX 01 FRANCE ORDER REFERENCE 86 A2 36JX 02 The following copyright notice protects this book under the Copyright laws of the United States of America and other countries which prohibit such actions as, but not limited to, copying, distributing, modifying, and making derivative works. Copyright Bull S.A. 1992, 1999 Printed in France Suggestions and criticisms concerning the form, content, and presentation of this book are invited. A form is provided at the end of this book for this purpose. To order additional copies of this book or other Bull Technical Publications, you are invited to use the Ordering Form also provided at the end of this book. Trademarks and Acknowledgements We acknowledge the right of proprietors of trademarks mentioned in this book. AIXR is a registered trademark of International Business Machines Corporation, and is being used under licence. UNIX is a registered trademark in the United States of America and other countries licensed exclusively through the Open Group. Year 2000 The product documented in this manual is Year 2000 Ready. The information in this document is subject to change without notice. Groupe Bull will not be liable for errors contained herein, or for incidental or consequential damages in connection with the use of this material. Contents Trademarks and Acknowledgements . iii 64-bit Kernel Extension Development. 23 About This Book . -
Java: Exercises in Style
Java: Exercises in Style Marco Faella June 1, 2018 i ii This work is licensed under the Creative Commons Attribution- NonCommercial 4.0 International License. To view a copy of this li- cense, visit http://creativecommons.org/licenses/by-nc/4.0/ or send a letter to Creative Commons, PO Box 1866, Mountain View, CA 94042, USA. Author: Marco Faella, [email protected] Preface to the Online Draft This draft is a partial preview of what may eventually become a book. The idea is to share it with the public and obtain feedback to improve its quality. So, if you read the whole draft, or maybe just a chapter, or you just glance over it long enough to spot a typo, let me know! I’m interested in all comments and suggestions for improvement, including (natural) language issues, programming, book structure, etc. I would like to thank all the students who have attended my Programming Languages class, during the past 11 years. They taught me that there is no limit to the number of ways you may think to have solved a Java assignment. Naples, Italy Marco Faella January 2018 iii Contents Contents iv I Preliminaries 1 1 Introduction 3 1.1 Software Qualities . 5 2 Problem Statement 9 2.1 Data Model and Representations . 10 3 Hello World! 13 4 Reference Implementation 17 4.1 Space Complexity . 21 4.2 Time Complexity . 23 II Software Qualities 29 5 Need for Speed 31 5.1 Optimizing “getAmount” and “addWater” . 32 5.2 Optimizing “connectTo” and “addWater” . 34 5.3 The Best Balance: Union-Find Algorithms . -
Graph Reduction Without Pointers
Graph Reduction Without Pointers TR89-045 December, 1989 William Daniel Partain The University of North Carolina at Chapel Hill Department of Computer Science ! I CB#3175, Sitterson Hall Chapel Hill, NC 27599-3175 UNC is an Equal Opportunity/Aflirmative Action Institution. Graph Reduction Without Pointers by William Daniel Partain A dissertation submitted to the faculty of the University of North Carolina at Chapel Hill in partial fulfillment of the requirements for the degree of Doctor of Philosophy in the Department of Computer Science. Chapel Hill, 1989 Approved by: Jfn F. Prins, reader ~ ~<---( CJ)~ ~ ;=tfJ\ Donald F. Stanat, reader @1989 William D. Partain ALL RIGHTS RESERVED II WILLIAM DANIEL PARTAIN. Graph Reduction Without Pointers (Under the direction of Gyula A. Mag6.) Abstract Graph reduction is one way to overcome the exponential space blow-ups that simple normal-order evaluation of the lambda-calculus is likely to suf fer. The lambda-calculus underlies lazy functional programming languages, which offer hope for improved programmer productivity based on stronger mathematical underpinnings. Because functional languages seem well-suited to highly-parallel machine implementations, graph reduction is often chosen as the basis for these machines' designs. Inherent to graph reduction is a commonly-accessible store holding nodes referenced through "pointers," unique global identifiers; graph operations cannot guarantee that nodes directly connected in the graph will be in nearby store locations. This absence of locality is inimical to parallel computers, which prefer isolated pieces of hardware working on self-contained parts of a program. In this dissertation, I develop an alternate reduction system using "sus pensions" (delayed substitutions), with terms represented as trees and vari ables by their binding indices (de Bruijn numbers). -
Fundamental Data Structures Contents
Fundamental Data Structures Contents 1 Introduction 1 1.1 Abstract data type ........................................... 1 1.1.1 Examples ........................................... 1 1.1.2 Introduction .......................................... 2 1.1.3 Defining an abstract data type ................................. 2 1.1.4 Advantages of abstract data typing .............................. 4 1.1.5 Typical operations ...................................... 4 1.1.6 Examples ........................................... 5 1.1.7 Implementation ........................................ 5 1.1.8 See also ............................................ 6 1.1.9 Notes ............................................. 6 1.1.10 References .......................................... 6 1.1.11 Further ............................................ 7 1.1.12 External links ......................................... 7 1.2 Data structure ............................................. 7 1.2.1 Overview ........................................... 7 1.2.2 Examples ........................................... 7 1.2.3 Language support ....................................... 8 1.2.4 See also ............................................ 8 1.2.5 References .......................................... 8 1.2.6 Further reading ........................................ 8 1.2.7 External links ......................................... 9 1.3 Analysis of algorithms ......................................... 9 1.3.1 Cost models ......................................... 9 1.3.2 Run-time analysis -
Open Data Structures (In Pseudocode)
Open Data Structures (in pseudocode) Edition 0.1Gβ Pat Morin Contents Acknowledgments ix Why This Book? xi 1 Introduction 1 1.1 The Need for Efficiency ..................... 2 1.2 Interfaces ............................. 4 1.2.1 The Queue, Stack, and Deque Interfaces . 5 1.2.2 The List Interface: Linear Sequences . 6 1.2.3 The USet Interface: Unordered Sets .......... 8 1.2.4 The SSet Interface: Sorted Sets ............. 8 1.3 Mathematical Background ................... 9 1.3.1 Exponentials and Logarithms . 10 1.3.2 Factorials ......................... 11 1.3.3 Asymptotic Notation . 12 1.3.4 Randomization and Probability . 15 1.4 The Model of Computation ................... 18 1.5 Correctness, Time Complexity, and Space Complexity . 19 1.6 Code Samples .......................... 21 1.7 List of Data Structures ..................... 23 1.8 Discussion and Exercises .................... 23 2 Array-Based Lists 31 2.1 ArrayStack: Fast Stack Operations Using an Array . 32 2.1.1 The Basics ........................ 32 2.1.2 Growing and Shrinking . 35 2.1.3 Summary ......................... 37 Contents 2.2 FastArrayStack: An Optimized ArrayStack . 37 2.3 ArrayQueue: An Array-Based Queue . 38 2.3.1 Summary ......................... 41 2.4 ArrayDeque: Fast Deque Operations Using an Array . 42 2.4.1 Summary ......................... 44 2.5 DualArrayDeque: Building a Deque from Two Stacks . 44 2.5.1 Balancing ......................... 48 2.5.2 Summary ......................... 50 2.6 RootishArrayStack: A Space-Efficient Array Stack . 50 2.6.1 Analysis of Growing and Shrinking . 55 2.6.2 Space Usage ....................... 55 2.6.3 Summary ......................... 56 2.7 Discussion and Exercises .................... 57 3 Linked Lists 61 3.1 SLList: A Singly-Linked List . -
Tamperproofing a Software Watermark by Encoding Constants
Tamperproofing a Software Watermark by Encoding Constants by Yong He A Thesis Submitted in Partial Fulfilment of the Requirement for the Degree of MASTER OF SCIENCE in Computer Science University of Auckland Copyright © 2002 by Yong He i Abstract Software Watermarking is widely used for software ownership authentication, but it is susceptible to various de-watermarking attacks such as obfuscation. Dynamic Graph Watermarking is a relatively new technology for software watermarking, and is believed the most likely to withstand attacks, which are trying to distort watermark structure. In this thesis, we present a new technology for protecting Dynamic Graph Watermarks. This technology encodes some of the constants, which are found in a software program, into a tree structure that is similar to the watermark, and generates decoding functions to retrieve the value of the constants at program execution time. If the constant tree is modified, the value of some constants will be affected, destroying program correctness. An attacker cannot reliably distinguish the watermark tree from the constant tree, so they must preserve the watermark tree or risk introducing bugs into the program. Constant Encoding technology can be included in Dynamic Graph Watermarking systems as a plug-in module to improve the Dynamic Graph Watermark protection. In this thesis, we present a prototyping program for Constant Encoding technology, which we call the JSafeMark encoder. Besides addressing the issues about Constant Encoding technology, we also discuss the design and implementation of our JSafeMark encoder, and give a practical example to show how this technology can protect Dynamic Graph Watermarking. iii Acknowledgement I would like to thank Professor Clark Thomborson, my supervisor, for his guidance and enthusiasm. -
Handout 09: Suggested Project Topics
CS166 Handout 09 Spring 2021 April 13, 2021 Suggested Project Topics Here is a list of data structures and families of data structures we think you might find interesting topics for your research project. You're by no means limited to what's contained here; if you have another data structure you'd like to explore, feel free to do so! My Wish List Below is a list of topics where, each quarter, I secretly think “I hope someone wants to pick this topic this quarter!” These are data structures I’ve always wanted to learn a bit more about or that I think would be particularly fun to do a deep dive into. You are not in any way, shape, or form required to pick something from this list, and we aren’t offer- ing extra credit or anything like that if you do choose to select one of these topics. However, if any of them seem interesting to you, we’d be excited to see what you come up with over the quarter. • Bentley-Saxe dynamization (turning static data structures into dynamic data structures) • Bε-trees (a B-tree variant designed to minimize writes) • Chazelle and Guibas’s O(log n + k) 3D range search (fast range searches in 3D) • Crazy good chocolate pop tarts (deamortizing binary search trees) • Durocher’s RMQ structure (fast RMQ without the Method of Four Russians) • Dynamic prefix sum lower bounds (proving lower bounds on dynamic prefix parity) • Farach’s suffix tree algorithm (a brilliant, beautiful divide-and-conquer algorithm) • Geometric greedy trees (lower bounds on BSTs giving rise to a specific BST) • Ham sandwich trees (fast searches -
N4397: a Low-Level API for Stackful Coroutines
Document number: N4397 Date: 2015-04-09 Project: WG21, SG1 Author: Oliver Kowalke ([email protected]) A low-level API for stackful coroutines Abstract........................................................1 Background.....................................................2 Definitions......................................................2 Execution context.............................................2 Activation record.............................................2 Stack frame.................................................2 Heap-allocated activation record....................................2 Processor stack..............................................2 Application stack.............................................3 Thread stack................................................3 Side stack..................................................3 Linear stack................................................3 Linked stack................................................3 Non-contiguous stack..........................................3 Parent pointer tree............................................3 Coroutine.................................................3 Toplevel context function.........................................4 Asymmetric coroutine..........................................4 Symmetric coroutine...........................................4 Fiber/user-mode thread.........................................4 Resumable function............................................4 Suspend by return.............................................4 Suspend