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Programming Paradigms & Object-Oriented
4.3 (Programming Paradigms & Object-Oriented- Computer Science 9608 Programming) with Majid Tahir Syllabus Content: 4.3.1 Programming paradigms Show understanding of what is meant by a programming paradigm Show understanding of the characteristics of a number of programming paradigms (low- level, imperative (procedural), object-oriented, declarative) – low-level programming Demonstrate an ability to write low-level code that uses various address modes: o immediate, direct, indirect, indexed and relative (see Section 1.4.3 and Section 3.6.2) o imperative programming- see details in Section 2.3 (procedural programming) Object-oriented programming (OOP) o demonstrate an ability to solve a problem by designing appropriate classes o demonstrate an ability to write code that demonstrates the use of classes, inheritance, polymorphism and containment (aggregation) declarative programming o demonstrate an ability to solve a problem by writing appropriate facts and rules based on supplied information o demonstrate an ability to write code that can satisfy a goal using facts and rules Programming paradigms 1 4.3 (Programming Paradigms & Object-Oriented- Computer Science 9608 Programming) with Majid Tahir Programming paradigm: A programming paradigm is a set of programming concepts and is a fundamental style of programming. Each paradigm will support a different way of thinking and problem solving. Paradigms are supported by programming language features. Some programming languages support more than one paradigm. There are many different paradigms, not all mutually exclusive. Here are just a few different paradigms. Low-level programming paradigm The features of Low-level programming languages give us the ability to manipulate the contents of memory addresses and registers directly and exploit the architecture of a given processor. -
Bioconductor: Open Software Development for Computational Biology and Bioinformatics Robert C
View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by Collection Of Biostatistics Research Archive Bioconductor Project Bioconductor Project Working Papers Year 2004 Paper 1 Bioconductor: Open software development for computational biology and bioinformatics Robert C. Gentleman, Department of Biostatistical Sciences, Dana Farber Can- cer Institute Vincent J. Carey, Channing Laboratory, Brigham and Women’s Hospital Douglas J. Bates, Department of Statistics, University of Wisconsin, Madison Benjamin M. Bolstad, Division of Biostatistics, University of California, Berkeley Marcel Dettling, Seminar for Statistics, ETH, Zurich, CH Sandrine Dudoit, Division of Biostatistics, University of California, Berkeley Byron Ellis, Department of Statistics, Harvard University Laurent Gautier, Center for Biological Sequence Analysis, Technical University of Denmark, DK Yongchao Ge, Department of Biomathematical Sciences, Mount Sinai School of Medicine Jeff Gentry, Department of Biostatistical Sciences, Dana Farber Cancer Institute Kurt Hornik, Computational Statistics Group, Department of Statistics and Math- ematics, Wirtschaftsuniversitat¨ Wien, AT Torsten Hothorn, Institut fuer Medizininformatik, Biometrie und Epidemiologie, Friedrich-Alexander-Universitat Erlangen-Nurnberg, DE Wolfgang Huber, Department for Molecular Genome Analysis (B050), German Cancer Research Center, Heidelberg, DE Stefano Iacus, Department of Economics, University of Milan, IT Rafael Irizarry, Department of Biostatistics, Johns Hopkins University Friedrich Leisch, Institut fur¨ Statistik und Wahrscheinlichkeitstheorie, Technische Universitat¨ Wien, AT Cheng Li, Department of Biostatistical Sciences, Dana Farber Cancer Institute Martin Maechler, Seminar for Statistics, ETH, Zurich, CH Anthony J. Rossini, Department of Medical Education and Biomedical Informat- ics, University of Washington Guenther Sawitzki, Statistisches Labor, Institut fuer Angewandte Mathematik, DE Colin Smith, Department of Molecular Biology, The Scripps Research Institute, San Diego Gordon K. -
Paradigms of Computer Programming
Paradigms of computer programming l This course aims to teach programming as a unified discipline that covers all programming languages l We cover the essential concepts and techniques in a uniform framework l Second-year university level: requires some programming experience and mathematics (sets, lists, functions) l The course covers four important themes: l Programming paradigms l Mathematical semantics of programming l Data abstraction l Concurrency l Let’s see how this works in practice Hundreds of programming languages are in use... So many, how can we understand them all? l Key insight: languages are based on paradigms, and there are many fewer paradigms than languages l We can understand many languages by learning few paradigms! What is a paradigm? l A programming paradigm is an approach to programming a computer based on a coherent set of principles or a mathematical theory l A program is written to solve problems l Any realistic program needs to solve different kinds of problems l Each kind of problem needs its own paradigm l So we need multiple paradigms and we need to combine them in the same program How can we study multiple paradigms? l How can we study multiple paradigms without studying multiple languages (since most languages only support one, or sometimes two paradigms)? l Each language has its own syntax, its own semantics, its own system, and its own quirks l We could pick three languages, like Java, Erlang, and Haskell, and structure our course around them l This would make the course complicated for no good reason -
The Machine That Builds Itself: How the Strengths of Lisp Family
Khomtchouk et al. OPINION NOTE The Machine that Builds Itself: How the Strengths of Lisp Family Languages Facilitate Building Complex and Flexible Bioinformatic Models Bohdan B. Khomtchouk1*, Edmund Weitz2 and Claes Wahlestedt1 *Correspondence: [email protected] Abstract 1Center for Therapeutic Innovation and Department of We address the need for expanding the presence of the Lisp family of Psychiatry and Behavioral programming languages in bioinformatics and computational biology research. Sciences, University of Miami Languages of this family, like Common Lisp, Scheme, or Clojure, facilitate the Miller School of Medicine, 1120 NW 14th ST, Miami, FL, USA creation of powerful and flexible software models that are required for complex 33136 and rapidly evolving domains like biology. We will point out several important key Full list of author information is features that distinguish languages of the Lisp family from other programming available at the end of the article languages and we will explain how these features can aid researchers in becoming more productive and creating better code. We will also show how these features make these languages ideal tools for artificial intelligence and machine learning applications. We will specifically stress the advantages of domain-specific languages (DSL): languages which are specialized to a particular area and thus not only facilitate easier research problem formulation, but also aid in the establishment of standards and best programming practices as applied to the specific research field at hand. DSLs are particularly easy to build in Common Lisp, the most comprehensive Lisp dialect, which is commonly referred to as the “programmable programming language.” We are convinced that Lisp grants programmers unprecedented power to build increasingly sophisticated artificial intelligence systems that may ultimately transform machine learning and AI research in bioinformatics and computational biology. -
Scripting: Higher- Level Programming for the 21St Century
. John K. Ousterhout Sun Microsystems Laboratories Scripting: Higher- Cybersquare Level Programming for the 21st Century Increases in computer speed and changes in the application mix are making scripting languages more and more important for the applications of the future. Scripting languages differ from system programming languages in that they are designed for “gluing” applications together. They use typeless approaches to achieve a higher level of programming and more rapid application development than system programming languages. or the past 15 years, a fundamental change has been ated with system programming languages and glued Foccurring in the way people write computer programs. together with scripting languages. However, several The change is a transition from system programming recent trends, such as faster machines, better script- languages such as C or C++ to scripting languages such ing languages, the increasing importance of graphical as Perl or Tcl. Although many people are participat- user interfaces (GUIs) and component architectures, ing in the change, few realize that the change is occur- and the growth of the Internet, have greatly expanded ring and even fewer know why it is happening. This the applicability of scripting languages. These trends article explains why scripting languages will handle will continue over the next decade, with more and many of the programming tasks in the next century more new applications written entirely in scripting better than system programming languages. languages and system programming -
Kickstart Your Gatling Performance Testing
Kickstart Your Gatling Performance Testing Siegfried Goeschl Version 1.0.0, 2018-11-04 Introduction 1 Siegfried Goeschl • Senior Software Engineer • Writing server-side code • Java Meetup Vienna co-organizer • Apache Software Foundation member • Currently working at Erste Bank Austria 2 Introducing Gatling • Performance testing framework • Tests are written in in Scala • Developer-centric test tool • Development started in 2010 • Gatling 3.0.1 released now • Since V3 there are two license models - free & commercial. • As you know some guys have a strong opinion about OSS 3 What Linus Says 4 5 • Having said that a commercial license could generate more revenue keeping the Open Source version alive. 6 Money Makes The World Go Round 7 Gatling vs. FrontLine • Gatling Open Source is under ASL 2.0 • Gatling FrontLine is the enterprise edition ◦ Annual license or "pay as you go" ◦ Web-based, ◦ More bells & whistle ◦ Real-time reporting 8 Under The Hood • Supports HTTP 1.1/2.0 & JMS protocol • Response validation ◦ Regular expressions ◦ XPath & JSONPath ◦ CSS selectors 9 Under The Hood • Provides Domain Specific Language (DSL) • Uses asynchronous non-blocking HTTP client • Integrates with Maven, SBT & Gradle • Test data feeders CSV, JSON, JDBC, Redis • Management-friendly HTML reports • No more 1:1 mapping between virtual users and worker threads. 10 When To Use Gatling? • Want to write test code in your IDE? • Need some integration & performance tests? • Want to run those test on your CI server? • Do you care about reviews and version control? 11 Getting Started 12 Getting Started • JDK 1.8 • Apache Maven 3.5.x • IntelliJ Community Edition • IntelliJ Scala Plugin 13 Getting Started • https://github.com/gatling/gatling-maven-plugin-demo • Import the Maven project into your IDE • Write and debug Scala code there • Execute Gatling tests on the command line • Simple CI integration using Maven • The official Gatling distributable is not suited for development. -
Tero Suominen PERFORMANCE TESTING REST APIS Information
Tero Suominen PERFORMANCE TESTING REST APIS Information Technology 2017 PERFORMANCE TESTING REST APIS Suominen, Tero Satakunta University of Applied Sciences Degree Programme in Computer Science December 2017 Number of pages: 39 Appendices: 0 Keywords: REST, performance testing, automation ____________________________________________________________________ The subject for this thesis was performance testing REST APIs that had been imple- mented into a Java application. The purpose of this research was to come up with a method on how the performance and functionality of the REST APIs could be meas- ured and tested within Profit Software. The research consisted of two parts. First, I searched to find an existing software ca- pable of being used for testing REST APIs. After selecting the tool that would be used to create the performance tests, a local test environment was set up that allowed us to estimate the capability of the software and the method of testing itself. The local envi- ronment consisted of the same components and software that could be used also in the already existing test environments within the company. This way moving the tests from the local environment into the actual test environment went smoothly. With the help of this research we were able to detect issues with the functionality of some APIs, when they were under load. We were able to fix these issues in the imple- mentation during the development phase and after changing the implementation we could verify that the APIs functioned correctly by using these same tests. REST RAJAPINTOJEN SUORITUSKYKYTESTAUS Suominen, Tero Satakunnan ammattikorkeakoulu Tietotekniikan koulutusohjelma Joulukuu 2017 Sivumäärä: 39 Liitteitä: 0 Asiasanat: REST, suorituskykytestaus, automaatio ____________________________________________________________________ Opinnäytetyön aiheena oli Java-sovellukseen toteutettujen REST rajapintojen performanssitestaus. -
Six Canonical Projects by Rem Koolhaas
5 Six Canonical Projects by Rem Koolhaas has been part of the international avant-garde since the nineteen-seventies and has been named the Pritzker Rem Koolhaas Architecture Prize for the year 2000. This book, which builds on six canonical projects, traces the discursive practice analyse behind the design methods used by Koolhaas and his office + OMA. It uncovers recurring key themes—such as wall, void, tur montage, trajectory, infrastructure, and shape—that have tek structured this design discourse over the span of Koolhaas’s Essays on the History of Ideas oeuvre. The book moves beyond the six core pieces, as well: It explores how these identified thematic design principles archi manifest in other works by Koolhaas as both practical re- Ingrid Böck applications and further elaborations. In addition to Koolhaas’s individual genius, these textual and material layers are accounted for shaping the very context of his work’s relevance. By comparing the design principles with relevant concepts from the architectural Zeitgeist in which OMA has operated, the study moves beyond its specific subject—Rem Koolhaas—and provides novel insight into the broader history of architectural ideas. Ingrid Böck is a researcher at the Institute of Architectural Theory, Art History and Cultural Studies at the Graz Ingrid Böck University of Technology, Austria. “Despite the prominence and notoriety of Rem Koolhaas … there is not a single piece of scholarly writing coming close to the … length, to the intensity, or to the methodological rigor found in the manuscript -
Loadrunner Professional and Loadrunner Enterprise 2021
Product Flyer Application Delivery Management LoadRunner Professional and LoadRunner Enterprise 2021 License Bundles Community bundles and license bundles available for LoadRunner Professional and LoadRunner Enterprise 2021. Learn more at Community Bundles (Free of Charge) https://software.microfocus.com/ Bundle Name Description products Community 50 Vusers for all protocols, except for Templates and GUI Mobile UI Unlimited Vusers for the TruClient—Native Mobile protocol. Note: This bundle requires an Micro Focus Mobile Center license. For more details, see: https://software.microfocus.com/software/customer-technical-support-services License Bundles Bundle Name Protocols .NET Record/Replay Microsoft .NET Database ODBC Oracle—2 Tier Development SDK Unit Test—NUnit, Junit Selenium, LeanFT* GUI Unified Functional Testing (UFT) Java Java Record Replay Java over HTTP Mobile and IoT DevWeb JMeter Gatling Web—HTTP/HTML TruClient—Mobile Web SMP (SAP Mobile Platform) MQTT (Internet of Things) CoAP (Internet of Things) Network DNS (Domain Name Resolution) FTP (File Transfer Protocol) IMAP (Internet Message Access Protocol) LDAP (Listing Directory Service) MAPI (Microsoft Exchange) POP3 (Post Office Protocol) SMTP (Simple Mail Transfer Protocol) Tuxedo Windows Sockets (Winsock) Oracle E-Business DevWeb JMeter Gatling Oracle NCA Oracle—Web Siebel—Web Web—HTTP/HTML * Continued on next page LeanFT support is for LoadRunner Enterprise only. Contact us at: www.microfocus.com Like what you read? Share it. Bundle Name Protocols Remote Access Citrix ICA -
Continuous Quality and Testing to Accelerate Application Development
Continuous Quality and Testing to Accelerate Application Development How to assess your current testing maturity level and practice continuous testing for DevOps Continuous Quality and Testing to Accelerate Application Development // 1 Table of Contents 03 Introduction 04 Why Is Continuous Quality and Testing Maturity Important to DevOps? 05 Continuous Testing Engineers Quality into DevOps 07 Best Practices for Well- Engineered Continuous Testing 08 Continuous Testing Maturity Levels Level 1: Chaos Level 2: Continuous Integration Level 3: Continuous Flow Level 4: Continuous Feedback Level 5: Continuous Improvement 12 Continuous Testing Maturity Assessment 13 How to Get Started with DevOps Testing? 14 Continuous Testing in the Cloud Choosing the right tools for Continuous Testing On-demand Development and Testing Environments with Infrastructure as Code The Right Tests at the Right Time 20 Get Started 20 Conclusion 21 About AWS Marketplace and DevOps Institute 21 Contributors Introduction A successful DevOps implementation reduces the bottlenecks related to testing. These bottlenecks include finding and setting up test environments, test configurations, and test results implementation. These issues are not industry specific. They can be experienced in manufacturing, service businesses, and governments alike. They can be reduced by having a thorough understanding and a disciplined, mature implementation of Continuous Testing and related recommended engineering practices. The best place to start addressing these challenges is having a good understanding of what Continuous Testing is. Marc Hornbeek, the author of Engineering DevOps, describes it as: “A quality assessment strategy in which most tests are automated and integrated as a core and essential part of DevOps. Continuous Testing is much more than simply ‘automating tests.’” In this whitepaper, we’ll address the best practices you can adopt for implementing Continuous Quality and Testing on the AWS Cloud environment in the context of the DevOps model. -
Roman Udka Software Test Automation Engineer
Roman Udka Software Test Automation Engineer Location: Ukraine, Kharkiv Telegram/Cell phone: +380994365885 E-Mail: [email protected] Summary: ● Experience 7 years. ● Performing execution and analysis test results. ● Implementation of qa education processes. ● Developing from scratch an automation framework based on the java stack. ● Organizing automation qa processes. ● Setuping CI/CD processes. ● Preparation approach for performance testing. ● Team leading / management at least 5 people; Skills: ● Test automation: Selenium (Selenide), TestNG, Selenium Grid (Selenoid). ● Performance tools: Locust, Gatling. ● Build automation/Continuous integration: Docker, Gradle, GitLabCi, Jenkins. ● Cloud: Azure, Linode. ● Bug Tracking/Test Management: Atlassian JIRA. ● Web debugging tools: Chrome dev tools. ● Programming: Java, Python; ● Version control system: Git; ● Agile: Scrum, Kanban. Work Experience: January, 2019 - till now Senior Software Test Engineer, GlobalLogic Project Role: Lead Automation Tester Tasks and Accomplishments: ● Automation tests creation and execution on 5 sub-projects. ● Performance testing. ● Creation of test automation framework from scratch and maintenance. ● Creation a test plan and strategy. ● Leading and supporting work of qa team; Environment: ● Selenide, TestNG, Git, Gradle, GitLabCI, IntelliJ IDEA, Azure, Report Portal. ● Java, Python, Selenium Grid, Docker, JIRA, DataDog, SendGrid, Locust, Gatling; January, 2015 - January, 2019 Software Test Engineer, EPAM Systems Project Role: Automation Tester Tasks and Accomplishments: -
Loadrunner Cloud an Essential Component of the Devops Pipeline
Product Flyer Application Delivery Management LoadRunner Cloud an Essential Component of the DevOps Pipeline Enable faster release and deployment cycles by taking advantage of agile development methodologies to achieve automated con- tinuous delivery. Micro Focus® LoadRunner Cloud makes it simple to integrate testing into the Development Process and test early and often. LoadRunner Cloud at a Glance: Applying an effective testing process within a Scalability in a Continuous high-speed delivery cycle can be a major chal- ■ Scalability: Testing Environment lenge, and traditional non-automated testing Managing hardware for performance testing A cloud-based solution that eliminates the methods may become a bottleneck. Con tin- tools is always a challenge. It becomes an even dependency on hardware as infrastructure is uous testing helps overcome this problem by bigger challenge in advanced DevOps environ- provisioned in the cloud fully automating testing throughout the delivery ments that have multiple teams and multiple ■ cycle. Micro Focus LoadRunner Cloud is the Automation: pipelines executing performance tests—with ideal solution to help overcome the potential Built in integration with Git, so scripts are managed challenges of applying continuous load testing. the need to manage a larger pool of load gener- in the repository for automatic updates prior to runs ators and controllers. LoadRunner Cloud, elim- ■ inates the dependency on hardware, allowing Collaboration: LoadRunner Cloud is the market-leading, multiple users and teams to connect to a single Project Management support, allowing users to share cloud-based performance testing solution, assets such as scripts, licenses, and load generators designed to support agile teams and DevOps cloud solution.