'Original program' presentation slideshows

Compilation 0368-3133 (Semester A, 2013/14)

Compilation 0368-3133 (Semester A, 2013/14). Lecture 12: Abstract Interpretation Noam Rinetzky. Slides credit: Roman Manevich , Mooly Sagiv and Eran Yahav. What is a compiler?.

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Mutation Testing Dagstuhl 08/08

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Hank Childs, University of Oregon

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QED: A Simplifier for Concurrent Programs

QED: A Simplifier for Concurrent Programs. Shaz Qadeer Microsoft Research. Joint work with Tayfun Elmas Ali Sezgin Serdar Tasiran. Reliable concurrent software?. Concurrency results in Heisenbugs non-deterministic, timing dependent data corruption, crashes

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Malicious Code

Malicious Code. Program Flaws. Taxonomy of flaws: how (genesis) when (time) where (location) the flaw was introduced into the system. Security Flaws by Genesis. Genesis Intentional Inadvertent. Intentional Genesis. Malicious: Trojan Horse, Trapdoor, Logic Bomb, covert channels

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Synthesis, Analysis, and Verification Lecture 05a

Synthesis, Analysis, and Verification Lecture 05a. Programs with Data Structures: Assertions for Accesses. Dynamic Allocation. Lectures: Viktor Kuncak. VCG for Real Languages. Programs that Manipulate Integers, Maps, Arrays, and Linked D ata Structures. Compute Formulas from Programs

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COUNTERMEASURE #3

COUNTERMEASURE #3. Ibnu Mubarok. Introduction. Exploit memory corruption change in control flow execution of the shellcode. 1. Buffer Restrictions Polymorphic Printable ASCII Shellcode 2. Non-executable stack ret2libs return into system() 3. Randomized Stack Space

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Lecture 14 Overview

Lecture 14 Overview. Program Flaws. Taxonomy of flaws: how (genesis) when (time) where (location) the flaw was introduced into the system. Security Flaws by Genesis. Genesis Intentional Malicious: Trojan Horse, Trapdoor, Logic Bomb, Worms, Virus Non-malicious Inadvertent

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CS 378 Programming for Performance Single-Thread Performance: Pipelining

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Program Slicing Mark Weiser and Precise Dynamic Slicing Algorithms Xiangyu Zhang, Rajiv Gupta & Youtao Zhang

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Remote Procedure Call (RPC)

Remote Procedure Call (RPC). Complexity of the distributed applications. The programming of distributed applications is difficult. In addition to the usual tasks, programmers who build clients and servers must deal with the complex issues of communication .

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Dynamic Floating-Point Cancellation Detection

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Para ? A Partial and Higher-Order Mutation Tool with Concurrency Operators

Para ? A Partial and Higher-Order Mutation Tool with Concurrency Operators . The 6 th International Workshop on Mutation Analysis (Mutation 2011) Berlin, Germany, March 2011. Outline. Motivation Contributions Related work P artial mutation Higher-order mutation

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Karina Hickey National Cannabis Prevention and Information Centre (NCPIC)

Karina Hickey National Cannabis Prevention and Information Centre (NCPIC). What is MakingtheLink?. A program for young people to promote help-seeking for cannabis use and mental health problems, which: teaches young people to help each other and to seek professional help

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Automating Auto Tuning

Automating Auto Tuning. Jeffrey K. Hollingsworth University of Maryland hollings@cs.umd.edu. Auto-tuning Motivation . Example, a dense matrix multiple kernel Various Options: Original program: 30.1 sec Hand Tuned (by developer): 11.4 sec Auto-tuned of hand-tuned: 15.9 sec

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Brian R. Flay, D.Phil. Public Health, Oregon State University

Implementing and Sustaining Evidence-Based Programs with Integrity: Goal Alignment between Programs and Settings. Brian R. Flay, D.Phil. Public Health, Oregon State University. Presented at Forum on Emphasizing Evidence-Based Programs for Children and Youth

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Just Basic Lessons 7&8

Just Basic Lessons 7&8. Mr. Kalmes. Lesson 7 Objectives. Compare and contrast two different programs Analyze different arithmetic operators. Previous Program. Original Program. Compare the two programs. Journal Part 1. Please click on your journal and complete sections 1 & 2.

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Platform

LPD-17. LPD-17. Amphibious Transport Dock LPD-17 San Antonio Class. Platform. Description. Speed 24.5 kts Draft 23.0 ft (Full Load) Crew 364 (29 Officers; 33 >E7; 302 <E6) Embarked Landing Force 697 (66 Officers; 42 >E7; 589 <E6); 101 Surge

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Scalable RADAR for Co-evolutionary Adaptive Environments

Scalable RADAR for Co-evolutionary Adaptive Environments. Approach: Extend our existing platforms by further examining biological factors. Future: Simulate spread of both attacks and repairs simultaneously.

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