An Agent-Oriented Approach Based on the Simpal Language
Total Page:16
File Type:pdf, Size:1020Kb
Load more
Recommended publications
-
7.4, Integration with Google Apps Is Deprecated
Google Search Appliance Integrating with Google Apps Google Search Appliance software version 7.2 and later Google, Inc. 1600 Amphitheatre Parkway Mountain View, CA 94043 www.google.com GSA-APPS_200.03 March 2015 © Copyright 2015 Google, Inc. All rights reserved. Google and the Google logo are, registered trademarks or service marks of Google, Inc. All other trademarks are the property of their respective owners. Use of any Google solution is governed by the license agreement included in your original contract. Any intellectual property rights relating to the Google services are and shall remain the exclusive property of Google, Inc. and/or its subsidiaries (“Google”). You may not attempt to decipher, decompile, or develop source code for any Google product or service offering, or knowingly allow others to do so. Google documentation may not be sold, resold, licensed or sublicensed and may not be transferred without the prior written consent of Google. Your right to copy this manual is limited by copyright law. Making copies, adaptations, or compilation works, without prior written authorization of Google. is prohibited by law and constitutes a punishable violation of the law. No part of this manual may be reproduced in whole or in part without the express written consent of Google. Copyright © by Google, Inc. Google Search Appliance: Integrating with Google Apps 2 Contents Integrating with Google Apps ...................................................................................... 4 Deprecation Notice 4 Google Apps Integration 4 -
Composable Concurrency Models
Composable Concurrency Models Dan Stelljes Division of Science and Mathematics University of Minnesota, Morris Morris, Minnesota, USA 56267 [email protected] ABSTRACT Given that an application is likely to make use of more The need to manage concurrent operations in applications than one concurrency model, programmers would prefer that has led to the development of a variety of concurrency mod- different types of models could safely interact. However, dif- els. Modern programming languages generally provide sev- ferent models do not necessarily work well together, nor are eral concurrency models to serve different requirements, and they designed to. Recent work has attempted to identify programmers benefit from being able to use them in tandem. common \building blocks" that could be used to compose We discuss challenges surrounding concurrent programming a variety of models, possibly eliminating subtle problems and examine situations in which conflicts between models when different models interact and allowing models to be can occur. Additionally, we describe attempts to identify represented at lower levels without resorting to rough ap- features of common concurrency models and develop lower- proximations [9, 11, 12]. level abstractions capable of supporting a variety of models. 2. BACKGROUND 1. INTRODUCTION In a concurrent program, the history of operations may Most interactive computer programs depend on concur- not be the same for every execution. An entirely sequen- rency, the ability to perform different tasks at the same tial program could be proved to be correct by showing that time. A web browser, for instance, might at any point be its history (that is, the sequence in which its operations are rendering documents in multiple tabs, transferring files, and performed) always yields a correct result. -
Reactive Async: Expressive Deterministic Concurrency
Reactive Async: Expressive Deterministic Concurrency Philipp Haller Simon Geries Michael Eichberg Guido Salvaneschi KTH Royal Institute of Technology, Sweden TU Darmstadt, Germany [email protected] feichberg, [email protected] Abstract tion can generate non-deterministic results because of their Concurrent programming is infamous for its difficulty. An unpredictable scheduling. Traditionally, developers address important source of difficulty is non-determinism, stemming these problems by protecting state from concurrent access from unpredictable interleavings of concurrent activities. via synchronisation. Yet, concurrent programming remains Futures and promises are widely-used abstractions that help an art: insufficient synchronisation leads to unsound pro- designing deterministic concurrent programs, although this grams but synchronising too much does not exploit hardware property cannot be guaranteed statically in mainstream pro- capabilities effectively for parallel execution. gramming languages. Deterministic-by-construction con- Over the years researchers have proposed concurrency current programming models avoid this issue, but they typi- models that attempt to overcome these issues. For exam- cally restrict expressiveness in important ways. ple the actor model [13] encapsulates state into actors This paper introduces a concurrent programming model, which communicate via asynchronous messages–a solution Reactive Async, which decouples concurrent computations that avoids shared state and hence (low-level) race condi- using -
A Reduction Semantics for Direct-Style Asynchronous Observables
Journal of Logical and Algebraic Methods in Programming 105 (2019) 75–111 Contents lists available at ScienceDirect Journal of Logical and Algebraic Methods in Programming www.elsevier.com/locate/jlamp A reduction semantics for direct-style asynchronous observables ∗ Philipp Haller a, , Heather Miller b a KTH Royal Institute of Technology, Sweden b Carnegie Mellon University, USA a r t i c l e i n f o a b s t r a c t Article history: Asynchronous programming has gained in importance, not only due to hardware develop- Received 31 January 2016 ments like multi-core processors, but also due to pervasive asynchronicity in client-side Received in revised form 6 March 2019 Web programming and large-scale Web applications. However, asynchronous program- Accepted 6 March 2019 ming is challenging. For example, control-flow management and error handling are much Available online 18 March 2019 more complex in an asynchronous than a synchronous context. Programming with asyn- chronous event streams is especially difficult: expressing asynchronous stream producers and consumers requires explicit state machines in continuation-passing style when using widely-used languages like Java. In order to address this challenge, recent language designs like Google’s Dart introduce asynchronous generators which allow expressing complex asynchronous programs in a familiar blocking style while using efficient non-blocking concurrency control under the hood. However, several issues remain unresolved, including the integration of analogous constructs into statically-typed languages, and the formalization and proof of important correctness properties. This paper presents a design for asynchronous stream generators for Scala, thereby ex- tending previous facilities for asynchronous programming in Scala from tasks/futures to asynchronous streams. -
Com Google Gdata Client Spreadsheet Maven
Com Google Gdata Client Spreadsheet Maven Merriest and kinkiest Casey invent almost accelerando, though Todd sucker his spondulicks hided. Stupefied and microbiological Ethan readies while insecticidal Stephen shanghais her lichee horribly and airts cherubically. Quietist and frostbitten Waiter never nest antichristianly when Stinky shook his seizin. 09-Jun-2020 116 24400 google-http-java-client-findbugs-1220-lp1521. It just gives me like a permutation code coverage information plotted together to complete output panel making mrn is com google gdata client spreadsheet maven? Chrony System EnvironmentDaemons 211-1el7centos An NTP client. Richard Huang contact-listgdata. Gdata-mavenmaven-metadataxmlmd5 at master eburtsev. SpreadsheetServiceVersionsclass comgooglegdataclientspreadsheet. Index of sitesdownloadeclipseorgeclipseMirroroomph. Acid transactions with maven coordinates genomic sequences are required js code coverage sequencing kits and client library for com google gdata client spreadsheet maven project setup and table of users as. Issues filed for googlegdata-java-client Record data Found. Uncategorized Majecek's Weblog. API using Spring any Spring Data JPA Maven and embedded H2 database. GData Spreadsheet1 usages comgooglegdataclientspreadsheet gdata-spreadsheet GData Spreadsheet Last feather on Feb 19 2010. Maven dependency for Google Spreadsheet Stack Overflow. Httpmavenotavanopistofi7070nexuscontentrepositoriessnapshots false. Gdata-spreadsheet-30jar Fri Feb 19 105942 GMT 2010 51623. I'm intern to use db2triples for the first time fan is a java maven project. It tries to approve your hours of columns throughout the free software testing late to work. Maven Com Google Gdata Client Spreadsheet Google Sites. Airhacksfm podcast with adam bien Apple. Unable to build ODK Aggregate locally Development ODK. Bmkdep bmon bnd-maven-plugin BNFC bodr bogofilter boinc-client bomber bomns bonnie boo books bookworm boomaga boost1710-gnu-mpich-hpc. -
Download the Index
Dewsbury.book Page 555 Wednesday, October 31, 2007 11:03 AM Index Symbols addHistoryListener method, Hyperlink wid- get, 46 $wnd object, JSNI, 216 addItem method, MenuBar widget, 68–69 & (ampersand), in GET and POST parameters, addLoadListener method, Image widget, 44 112–113 addMessage method, ChatWindowView class, { } (curly braces), JSON, 123 444–445 ? (question mark), GET requests, 112 addSearchResult method JUnit test case, 175 SearchResultsView class, 329 A addSearchView method, MultiSearchView class, 327 Abstract Factory pattern, 258–259 addStyleName method, connecting GWT widgets Abstract methods, 332 to CSS, 201 Abstract Window Toolkit (AWT), Java, 31 addToken method, handling back button, 199 AbstractImagePrototype object, 245 addTreeListener method, Tree widget, 67 Abstraction, DAOs and, 486 Adobe Flash and Flex, 6–7 AbstractMessengerService Aggregator pattern Comet, 474 defined, 34 Jetty Continuations, 477 Multi-Search application and, 319–321 action attribute, HTML form tag, 507 sample application, 35 Action-based web applications Aggregators, 320 overview of, 116 Ajax (Asynchronous JavaScript and XML) PHP scripts for building, 523 alternatives to, 6–8 ActionObjectDAO class, 527–530 application development and, 14–16 Actions, server integration with, 507–508 building web applications and, 479 ActionScript, 6 emergence of, 3–5 ActiveX, 7 Google Gears for storage, 306–309 Add Import command Same Origin policy and, 335 creating classes in Eclipse, 152 success and limitations of, 5–6 writing Java code using Eclipse Java editor, -
Ray Cromwell
Building Applications with Google APIs Ray Cromwell Monday, June 1, 2009 “There’s an API for that” • code.google.com shows 60+ APIs • full spectrum (client, server, mobile, cloud) • application oriented (android, opensocial) • Does Google have a Platform? Monday, June 1, 2009 Application Ecosystem Client REST/JSON, GWT, Server ProtocolBuffers Earth PHP Java O3D App Services Media Docs Python Ruby Utility Blogger Spreadsheets Maps/Geo JPA/JDO/Other Translate Base Datastore GViz Social MySQL Search OpenSocial Auth FriendConnect $$$ ... GData Contacts AdSense Checkout Monday, June 1, 2009 Timefire • Store and Index large # of time series data • Scalable Charting Engine • Social Collaboration • Story Telling + Video/Audio sync • Like “Google Maps” but for “Time” Monday, June 1, 2009 Android Version 98% Shared Code with Web version Monday, June 1, 2009 Android • Full API stack • Tight integration with WebKit browser • Local database, 2D and 3D APIs • External XML UI/Layout system • Makes separating presentation from logic easier, benefits code sharing Monday, June 1, 2009 How was this done? • Google Web Toolkit is the Foundation • Target GWT JRE as LCD • Use Guice Dependency Injection for platform-specific APIs • Leverage GWT 1.6 event system Monday, June 1, 2009 Example App Code Device/Service JRE interfaces Guice Android Browser Impl Impl Android GWT Specific Specific Monday, June 1, 2009 Shared Widget Events interface HasClickHandler interface HasClickHandler addClickHandler(injectedHandler) addClickHandler(injectedHandler) Gin binds GwtHandlerImpl -
Abstract Interface Behavior of an Object-Oriented Language with Futures and Promises
Abstract interface behavior of an object-oriented language with futures and promises 3. September 2007 Erika Abrah´ am´ 1, and Immo Grabe2, and Andreas Gruner¨ 2, and Martin Steffen3 1 Albert-Ludwigs-University Freiburg, Germany 2 Christian-Albrechts-University Kiel, Germany 3 University of Oslo, Norway 1 Motivation How to marry concurrency and object-orientation has been a long-standing issue; see e.g., [2] for an early discussion of different design choices. Recently, the thread-based model of concurrency, prominently represented by languages like Java and C# has been criticized, especially in the context of component-based software development. As the word indicates, components are (software) artifacts intended for composition, i.e., open systems, interacting with a surrounding environment. To compare different concurrency models on a solid mathematical basis, a semantical description of the interface behavior is needed, and this is what we do in this work. We present an open semantics for a core of the Creol language [4,7], an object-oriented, concurrent language, featuring in particular asynchronous method calls and (since recently [5]) future-based concurrency. Futures and promises A future, very generally, represents a result yet to be computed. It acts as a proxy for, or reference to, the delayed result from a given sequential piece of code (e.g., a method or a function body in an object-oriented, resp. a functional setting). As the client of the delayed result can proceed its own execution until it actually needs the result, futures provide a natural, lightweight, and (in a functional setting) transparent mechanism to introduce parallelism into a language. -
N4244: Resumable Lambdas
Document Number: N4244 Date: 2014-10-13 Reply To Christopher Kohlhoff <[email protected]> Resumable Lambdas: A language extension for generators and coroutines 1 Introduction N3977 Resumable Functions and successor describe a language extension for resumable functions, or “stackless” coroutines. The earlier revision, N3858, states that the motivation is: [...] the increasing importance of efficiently handling I/O in its various forms and the complexities programmers are faced with using existing language features and existing libraries. In contrast to “stackful” coroutines, a prime use case for stackless coroutines is in server applications that handle many thousands or millions of clients. This is due to stackless coroutines having lower memory requirements than stackful coroutines, as the latter, like true threads, must have a reserved stack space. Memory cost per byte is dropping over time, but with server applications at this scale, per-machine costs, such as hardware, rack space, network connectivity and administration, are significant. For a given request volume, it is always cheaper if the application can be run on fewer machines. Existing best practice for stackless coroutines in C and C++ uses macros and a switch-based technique similar to Duff’s Device. Examples include the coroutine class included in Boost.Asio1, and Protothreads2. Simon Tatham’s web page3, Coroutines in C, inspired both of these implementations. A typical coroutine using this model looks like this: void operator()(error_code ec, size_t n) { if (!ec) reenter (this) { for (;;) { yield socket_->async_read_some(buffer(*data_), *this); yield async_write(*socket_, buffer(*data_, n), *this); } } } The memory overhead of a stackless coroutine can be as low as a single int. -
Concepts and Paradigms of Object-Oriented Programming Expansion of Oct 400PSLA-89 Keynote Talk Peter Wegner, Brown University
Concepts and Paradigms of Object-Oriented Programming Expansion of Oct 400PSLA-89 Keynote Talk Peter Wegner, Brown University 1. What Is It? 8 1.1. Objects 8 1.2. Classes 10 1.3. Inheritance 11 1.4. Object-Oriented Systems 12 2. What Are Its Goals? 13 2.1. Software Components 13 2.2. Object-Oriented Libraries 14 2.3. Reusability and Capital-intensive Software Technology 16 2.4. Object-Oriented Programming in the Very Large 18 3. What Are Its Origins? 19 3.1. Programming Language Evolution 19 3.2. Programming Language Paradigms 21 4. What Are Its Paradigms? 22 4.1. The State Partitioning Paradigm 23 4.2. State Transition, Communication, and Classification Paradigms 24 4.3. Subparadigms of Object-Based Programming 26 5. What Are Its Design Alternatives? 28 5.1. Objects 28 5.2. Types 33 5.3. Inheritance 36 5.4. Strongly Typed Object-Oriented Languages 43 5.5. Interesting Language Classes 45 5.6. Object-Oriented Concept Hierarchies 46 6. what Are Its Models of Concurrency? 49 6.1. Process Structure 50 6.2. Internal Process Concurrency 55 6.3. Design Alternatives for Synchronization 56 6.4. Asynchronous Messages, Futures, and Promises 57 6.5. Inter-Process Communication 58 6.6. Abstraction, Distribution, and Synchronization Boundaries 59 6.7. Persistence and Transactions 60 7. What Are Its Formal Computational Models? 62 7.1. Automata as Models of Object Behavior 62 7.2. Mathematical Models of Types and Classes 65 7.3. The Essence of Inheritance 74 7.4. Reflection in Object-Oriented Systems 78 8. -
Building the Polargrid Portal Using Web 2.0 and Opensocial
Building the PolarGrid Portal Using Web 2.0 and OpenSocial Zhenhua Guo, Raminderjeet Singh, Marlon Pierce Community Grids Laboratory, Pervasive Technology Institute Indiana University, Bloomington 2719 East 10th Street, Bloomington, Indiana 47408 {zhguo, ramifnu, marpierc}@indiana.edu ABSTRACT service gateway are still useful, it is time to revisit some of the Science requires collaboration. In this paper, we investigate the software and standards used to actually build gateways. Two feasibility of coupling current social networking techniques to important candidates are the Google Gadget component model science gateways to provide a scientific collaboration model. We and the REST service development style for building gateways. are particularly interested in the integration of local and third Gadgets are attractive for three reasons. First, they are much party services, since we believe the latter provide more long-term easier to write than portlets and are to some degree framework- sustainability than gateway-provided service instances alone. Our agnostic. Second, they can be integrated into both iGoogle prototype use case for this study is the PolarGrid portal, in which (Google’s Start Page portal) and user-developed containers. we combine typical science portal functionality with widely used Finally, gadgets are actually a subset of the OpenSocial collaboration tools. Our goal is to determine the feasibility of specification [5], which enables developers to provide social rapidly developing a collaborative science gateway that networking capabilities. Standardization is useful but more incorporates third-party collaborative services with more typical importantly one can plug directly into pre-existing social networks science gateway capabilities. We specifically investigate Google with millions of users without trying to establish a new network Gadget, OpenSocial, and related standards. -
IST687 - Viz Map HW: Median Income John Fields 5/14/2019
IST687 - Viz Map HW: Median Income John Fields 5/14/2019 Download the dataset from the LMS that has median income by zip code (an excel file). Step 1: Load the Data 1) Read the data – using the gdata package we have previously used. 2) Clean up the dataframe a. Remove any info at the front of the file that’s not needed b. Update the column names (zip, median, mean, population) library(gdata) ## gdata: read.xls support for 'XLS' (Excel 97-2004) files ENABLED. ## ## gdata: read.xls support for 'XLSX' (Excel 2007+) files ENABLED. ## ## Attaching package: 'gdata' ## The following object is masked from 'package:stats': ## ## nobs ## The following object is masked from 'package:utils': ## ## object.size ## The following object is masked from 'package:base': ## ## startsWith rawdata <- read.xls("/Users/johnfields/Library/Mobile Documents/com~apple~CloudDocs/Syracuse/IST687/Homework + Live Video Code/Week 7/MedianZIP_2_2.xls",skip=1) #Rename the columns namesOfColumns<-c("zip","median","mean","population") cleandata<-function(rawdata,namesOfColumns) {colnames(rawdata)<-namesOfColumns return(rawdata) } results<-cleandata(rawdata,namesOfColumns) head(results) ## zip median mean population ## 1 1001 56,663 66,688 16,445 ## 2 1002 49,853 75,063 28,069 ## 3 1003 28,462 35,121 8,491 ## 4 1005 75,423 82,442 4,798 ## 5 1007 79,076 85,802 12,962 ## 6 1008 63,980 78,391 1,244 3) Load the ‘zipcode’ package 1 4) Merge the zip code information from the two data frames (merge into one dataframe) 5) Remove Hawaii and Alaska (just focus on the ‘lower 48’ states)