Instrew: Leveraging LLVM for High Performance Dynamic Binary Instrumentation
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The Sad State of Web Development Random Thoughts on Web Development
The Sad State of Web Development Random thoughts on web development Going to shit 2015 is when web development went to shit. Web development used to be nice. You could fire up a text editor and start creating JS and CSS files. You can absolutely still do this. That has not changed. So yes, everything I’m about to say can be invalidated by saying that. The web (specifically the Javascript/Node community) has created some of the most complicated, convoluted, over engineered tools ever conceived. Node.js/NPM At times, I think where web development is at this point is some cruel joke played on us by Ryan Dahl. You see, to get into why web development is so terrible, you have to start at Node. By definition I was a magpie developer, so undoubtedly I used Node, just as everyone should. At universities they should make every developer write an app with Node.js, deploy it to production, then try to update the dependencies 3 months later. The only downside is we would have zero new developers coming out of computer science programs. You see the Node.js philosophy is to take the worst fucking language ever designed and put it on the server. Combine that with all the magpies that were using Ruby at the time, and you have the perfect fucking storm. Lets take everything that was great in Ruby and re write it in Javascript, I think was the official motto. Most of the smart magpies have moved on to Go at this point, but the people who have stayed in the Node community have undoubtedly created the most over engineered eco system that has ever appeared. -
16 Inspiring Women Engineers to Watch
Hackbright Academy Hackbright Academy is the leading software engineering school for women founded in San Francisco in 2012. The academy graduates more female engineers than UC Berkeley and Stanford each year. https://hackbrightacademy.com 16 Inspiring Women Engineers To Watch Women's engineering school Hackbright Academy is excited to share some updates from graduates of the software engineering fellowship. Check out what these 16 women are doing now at their companies - and what languages, frameworks, databases and other technologies these engineers use on the job! Software Engineer, Aclima Tiffany Williams is a software engineer at Aclima, where she builds software tools to ingest, process and manage city-scale environmental data sets enabled by Aclima’s sensor networks. Follow her on Twitter at @twilliamsphd. Technologies: Python, SQL, Cassandra, MariaDB, Docker, Kubernetes, Google Cloud Software Engineer, Eventbrite 1 / 16 Hackbright Academy Hackbright Academy is the leading software engineering school for women founded in San Francisco in 2012. The academy graduates more female engineers than UC Berkeley and Stanford each year. https://hackbrightacademy.com Maggie Shine works on backend and frontend application development to make buying a ticket on Eventbrite a great experience. In 2014, she helped build a WiFi-enabled basal body temperature fertility tracking device at a hardware hackathon. Follow her on Twitter at @magksh. Technologies: Python, Django, Celery, MySQL, Redis, Backbone, Marionette, React, Sass User Experience Engineer, GoDaddy 2 / 16 Hackbright Academy Hackbright Academy is the leading software engineering school for women founded in San Francisco in 2012. The academy graduates more female engineers than UC Berkeley and Stanford each year. -
Resourceable, Retargetable, Modular Instruction Selection Using a Machine-Independent, Type-Based Tiling of Low-Level Intermediate Code
Reprinted from Proceedings of the 2011 ACM Symposium on Principles of Programming Languages (POPL’11) Resourceable, Retargetable, Modular Instruction Selection Using a Machine-Independent, Type-Based Tiling of Low-Level Intermediate Code Norman Ramsey Joao˜ Dias Department of Computer Science, Tufts University Department of Computer Science, Tufts University [email protected] [email protected] Abstract Our compiler infrastructure is built on C--, an abstraction that encapsulates an optimizing code generator so it can be reused We present a novel variation on the standard technique of selecting with multiple source languages and multiple target machines (Pey- instructions by tiling an intermediate-code tree. Typical compilers ton Jones, Ramsey, and Reig 1999; Ramsey and Peyton Jones use a different set of tiles for every target machine. By analyzing a 2000). C-- accommodates multiple source languages by providing formal model of machine-level computation, we have developed a two main interfaces: the C-- language is a machine-independent, single set of tiles that is machine-independent while retaining the language-independent target language for front ends; the C-- run- expressive power of machine code. Using this tileset, we reduce the time interface is an API which gives the run-time system access to number of tilers required from one per machine to one per archi- the states of suspended computations. tectural family (e.g., register architecture or stack architecture). Be- cause the tiler is the part of the instruction selector that is most dif- C-- is not a universal intermediate language (Conway 1958) or ficult to reason about, our technique makes it possible to retarget an a “write-once, run-anywhere” intermediate language encapsulating instruction selector with significantly less effort than standard tech- a rigidly defined compiler and run-time system (Lindholm and niques. -
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. -
CROP: Linking Code Reviews to Source Code Changes
CROP: Linking Code Reviews to Source Code Changes Matheus Paixao Jens Krinke University College London University College London London, United Kingdom London, United Kingdom [email protected] [email protected] Donggyun Han Mark Harman University College London Facebook and University College London London, United Kingdom London, United Kingdom [email protected] [email protected] ABSTRACT both industrial and open source software development communities. Code review has been widely adopted by both industrial and open For example, large organisations such as Google and Facebook use source software development communities. Research in code re- code review systems on a daily basis [5, 9]. view is highly dependant on real-world data, and although existing In addition to its increasing popularity among practitioners, researchers have attempted to provide code review datasets, there code review has also drawn the attention of software engineering is still no dataset that links code reviews with complete versions of researchers. There have been empirical studies on the effect of code the system’s code base mainly because reviewed versions are not review on many aspects of software engineering, including software kept in the system’s version control repository. Thus, we present quality [11, 12], review automation [2], and automated reviewer CROP, the Code Review Open Platform, the first curated code recommendation [20]. Recently, other research areas in software review repository that links review data with isolated complete engineering have leveraged the data generated during code review versions (snapshots) of the source code at the time of review. CROP to expand previously limited datasets and to perform empirical currently provides data for 8 software systems, 48,975 reviews and studies. -
Magento on HHVM Speeding up Your Webshop with a Drop-In PHP Replacement
Magento on HHVM Speeding up your webshop with a drop-in PHP replacement. Daniel Sloof [email protected] What is HHVM? ● HipHop Virtual Machine ● Created by engineers at Facebook ● Essentially a reimplementation of PHP ● Originally translated PHP to C++, now translates PHP to bytecode ● Just-in-time compiler, turning generated bytecode into machine code ● In some cases 5 to 10 times faster than regular PHP So what’s the problem? ● HHVM not entirely compatible with PHP ● Magento’s PHP triggering many of these incompatibilities ● Choosing between ○ Forking Magento to work around HHVM ○ Fixing issues within the extensive HHVM C++ codebase Resulted in... fixing HHVM ● Already over 100 commits fixing Magento related HHVM bugs; ○ SimpleXML (majority of bugfixes) ○ sessions ○ number_format ○ __get and __set ○ many more... ● Most of these fixes already merged back into the official (github) repository ● Community Edition running (relatively) stable! Benchmarks Before we go to the results... ● Magento 1.8 with sample data ● Standard Apache2 / php-fpm / MySQL stack (with APC opcode cache). ● Standard HHVM configuration (repo-authoritative mode disabled, JIT enabled) ● Repo-authoritative mode has potential to increase performance by a large margin ● Tool of choice: siege Benchmarks: Response time Average across 50 requests Benchmarks: Transaction rate While increasing siege concurrency until avg. response time ~2 seconds What about <insert caching mechanism here>? ● HHVM does not get in the way ● Dynamic content still needs to be generated ● Replaces PHP - not Varnish, Redis, FPC, Block Cache, etc. ● As long as you are burning CPU cycles (always), you will benefit from HHVM ● Think about speeding up indexing, order placement, routing, etc. -
Automated Program Transformation for Improving Software Quality
Automated Program Transformation for Improving Software Quality Rijnard van Tonder CMU-ISR-19-101 October 2019 Institute for Software Research School of Computer Science Carnegie Mellon University Pittsburgh, PA 15213 Thesis Committee: Claire Le Goues, Chair Christian Kästner Jan Hoffmann Manuel Fähndrich, Facebook, Inc. Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Software Engineering. Copyright 2019 Rijnard van Tonder This work is partially supported under National Science Foundation grant numbers CCF-1750116 and CCF-1563797, and a Facebook Testing and Verification research award. The views and conclusions contained in this document are those of the author and should not be interpreted as representing the official policies, either expressed or implied, of any sponsoring corporation, institution, the U.S. government, or any other entity. Keywords: syntax, transformation, parsers, rewriting, crash bucketing, fuzzing, bug triage, program transformation, automated bug fixing, automated program repair, separation logic, static analysis, program analysis Abstract Software bugs are not going away. Millions of dollars and thousands of developer-hours are spent finding bugs, debugging the root cause, writing a patch, and reviewing fixes. Automated techniques like static analysis and dynamic fuzz testing have a proven track record for cutting costs and improving software quality. More recently, advances in automated program repair have matured and see nascent adoption in industry. Despite the value of these approaches, automated techniques do not come for free: they must approximate, both theoretically and in the interest of practicality. For example, static analyzers suffer false positives, and automatically produced patches may be insufficiently precise to fix a bug. -
Crawling Code Review Data from Phabricator
Friedrich-Alexander-Universit¨atErlangen-N¨urnberg Technische Fakult¨at,Department Informatik DUMITRU COTET MASTER THESIS CRAWLING CODE REVIEW DATA FROM PHABRICATOR Submitted on 4 June 2019 Supervisors: Michael Dorner, M. Sc. Prof. Dr. Dirk Riehle, M.B.A. Professur f¨urOpen-Source-Software Department Informatik, Technische Fakult¨at Friedrich-Alexander-Universit¨atErlangen-N¨urnberg Versicherung Ich versichere, dass ich die Arbeit ohne fremde Hilfe und ohne Benutzung anderer als der angegebenen Quellen angefertigt habe und dass die Arbeit in gleicher oder ¨ahnlicherForm noch keiner anderen Pr¨ufungsbeh¨ordevorgelegen hat und von dieser als Teil einer Pr¨ufungsleistung angenommen wurde. Alle Ausf¨uhrungen,die w¨ortlich oder sinngem¨aߨubernommenwurden, sind als solche gekennzeichnet. Nuremberg, 4 June 2019 License This work is licensed under the Creative Commons Attribution 4.0 International license (CC BY 4.0), see https://creativecommons.org/licenses/by/4.0/ Nuremberg, 4 June 2019 i Abstract Modern code review is typically supported by software tools. Researchers use data tracked by these tools to study code review practices. A popular tool in open-source and closed-source projects is Phabricator. However, there is no tool to crawl all the available code review data from Phabricator hosts. In this thesis, we develop a Python crawler named Phabry, for crawling code review data from Phabricator instances using its REST API. The tool produces minimal server and client load, reproducible crawling runs, and stores complete and genuine review data. The new tool is used to crawl the Phabricator instances of the open source projects FreeBSD, KDE and LLVM. The resulting data sets can be used by researchers. -
Nástroje Pro Sjednocení Datových Zdrojů Projektu Gloffer Tools for Unification of Data Sources Project Gloffer
VŠB – Technická univerzita Ostrava Fakulta elektrotechniky a informatiky Katedra informatiky Nástroje pro sjednocení datových zdrojů projektu Gloffer Tools for unification of data sources project Gloffer 2018 Bc. Jakub Malchárek Rád bych poděkoval panu Ing. Radoslavu Fasugovi, Ph.D. za odbornou pomoc a konzultaci při zpracování této diplomové práce a cenné rady v průběhu implementace. Abstrakt V této diplomové práci se zabývám analýzou dostupných technologií pro implementaci webo- vého portálu Gloffer. Jsou zde popsány databáze (MySQL, Redis, MongoDB, Aerospike, Apache HBase, Apache Cassandra, Google Bigtable, Memcached), vyhledávače (Solr, Lucene, Elastic Search), webové servery (Apache HTTP server, Apache Tomcat), zprostředkovatelé zpráv (Rab- bit MQ), distribuované výpočetní technologie (Apache Hadoop) a vývojové technologie (PHP 7, Nette Framework, Java, Spring Framework). Cílem je nejen popis těchto technologií, ale také ná- vrh a implementace rozhraní pro sjednocení datových zdrojů projektu Gloffer v programovacím jazyce Java s využitím Spring Frameworku. Výstupem práce je inteligentní nástroj zpřístupňující data z více datových zdrojů. Závěr práce obsahuje výkonové testování vyvinutého nástroje. Klíčová slova: Aerospike, Apache Cassandra, Apache Hadoop, Apache HBase, Apache HTTP server, Apache Tomcat, aplikační rozhraní, datové zdroje, Elastic Search, fulltext, Google Bi- gtable, index, Java, Lucene, Memcached, MongoDB, MySQL, Nette Framework, PHP, Rabbit MQ, Redis, REST, Solr, Spring Framework Abstract In this diploma thesis I deal with analysis of the available technologies for implementation of the Gloffer web portal. There are described databases (MySQL, Redis, MongoDB, Aerospike, Apache HBase, Apache Cassandra, Google Bigtable, Memcached), search engines (Solr, Lucene, Elastic Search), web servers (Apache HTTP server, Apache Tomcat), message brokers (Rabbit MQ), distributed computing technologies (Apache Hadoop) and develop technologies (PHP 7, Nette Framework, Java, Spring Framework). -
Automatic Isolation of Compiler Errors
Automatic Isolation of Compiler Errors DAVID B.WHALLEY Flor ida State University This paper describes a tool called vpoiso that was developed to automatically isolate errors in the vpo com- piler system. The twogeneral types of compiler errors isolated by this tool are optimization and nonopti- mization errors. When isolating optimization errors, vpoiso relies on the vpo optimizer to identify sequences of changes, referred to as transformations, that result in semantically equivalent code and to pro- vide the ability to stop performing improving (or unnecessary) transformations after a specified number have been performed. Acompilation of a typical program by vpo often results in thousands of improving transformations being performed. The vpoiso tool can automatically isolate the first improving transforma- tion that causes incorrect output of the execution of the compiled program by using a binary search that varies the number of improving transformations performed. Not only is the illegaltransformation automati- cally isolated, but vpoiso also identifies the location and instant the transformation is performed in vpo. Nonoptimization errors occur from problems in the front end, code generator,and necessary transforma- tions in the optimizer.Ifanother compiler is available that can produce correct (but perhaps more ineffi- cient) code, then vpoiso can isolate nonoptimization errors to a single function. Automatic isolation of compiler errors facilitates retargeting a compiler to a newmachine, maintenance of the compiler,and sup- porting experimentation with newoptimizations. General Terms: Compilers, Testing Additional Key Words and Phrases: Diagnosis procedures, nonoptimization errors, optimization errors 1. INTRODUCTION To increase portability compilers are often split into twoparts, a front end and a back end. -
Letter, If Not the Spirit, of One Or the Other Definition
Producing Open Source Software How to Run a Successful Free Software Project Karl Fogel Producing Open Source Software: How to Run a Successful Free Software Project by Karl Fogel Copyright © 2005-2021 Karl Fogel, under the CreativeCommons Attribution-ShareAlike (4.0) license. Version: 2.3214 Home site: https://producingoss.com/ Dedication This book is dedicated to two dear friends without whom it would not have been possible: Karen Under- hill and Jim Blandy. i Table of Contents Preface ............................................................................................................................. vi Why Write This Book? ............................................................................................... vi Who Should Read This Book? ..................................................................................... vi Sources ................................................................................................................... vii Acknowledgements ................................................................................................... viii For the first edition (2005) ................................................................................ viii For the second edition (2021) .............................................................................. ix Disclaimer .............................................................................................................. xiii 1. Introduction ................................................................................................................... -
Artificial Intelligence for Understanding Large and Complex
Artificial Intelligence for Understanding Large and Complex Datacenters by Pengfei Zheng Department of Computer Science Duke University Date: Approved: Benjamin C. Lee, Advisor Bruce M. Maggs Jeffrey S. Chase Jun Yang Dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in the Department of Computer Science in the Graduate School of Duke University 2020 Abstract Artificial Intelligence for Understanding Large and Complex Datacenters by Pengfei Zheng Department of Computer Science Duke University Date: Approved: Benjamin C. Lee, Advisor Bruce M. Maggs Jeffrey S. Chase Jun Yang An abstract of a dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in the Department of Computer Science in the Graduate School of Duke University 2020 Copyright © 2020 by Pengfei Zheng All rights reserved except the rights granted by the Creative Commons Attribution-Noncommercial Licence Abstract As the democratization of global-scale web applications and cloud computing, under- standing the performance of a live production datacenter becomes a prerequisite for making strategic decisions related to datacenter design and optimization. Advances in monitoring, tracing, and profiling large, complex systems provide rich datasets and establish a rigorous foundation for performance understanding and reasoning. But the sheer volume and complexity of collected data challenges existing techniques, which rely heavily on human intervention, expert knowledge, and simple statistics. In this dissertation, we address this challenge using artificial intelligence and make the case for two important problems, datacenter performance diagnosis and datacenter workload characterization. The first thrust of this dissertation is the use of statistical causal inference and Bayesian probabilistic model for datacenter straggler diagnosis.