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This talk was given during the Java 8 Launch Event of the Israeli Java User Group (ilJUG) It is talking about Java8 CompletableFuture

Aim of this presentation is not to make you masters in Java 8 Concurrency, but to help you guide towards that goal. Sometimes it helps just to know that there is some API that might be suitable for a particular situation. Make use of the pointers given to search more and learn more on those topics. Refer to books, Java API Documentation, Blogs etc. to learn more. Examples and demos for all cases discussed will be added to my blog www.javajee.com.

Slides from tech talk about the art of non-blocking waiting in Java with LockSupport.park/unpark and AbstractQueuedSynchronizer. Presented on JPoint 2016 Conference.

Feihong talks about PEP 3156 and basic usage of Tulip, the reference implementation. Video: http://pyvideo.org/video/2194/asynchronous-io-in-python-3 Source code: https://github.com/feihong/tulip-talk/

This session, delivered at Devoxx Poland, covers all the major changes to the Java platform between JDK 12 and JDK 17. All language features are covered, as well as many of the important API changes.

This document provides an overview of Clojure and why one may want to try it. Some key points include: - Clojure is a functional programming language that runs on the JVM and allows easy interoperability with Java. - It has a very small and elegant syntax based on Lisp with sensible macro names and prefix notation. - Clojure encourages pure functional programming and the use of immutable data structures, while providing tools like Software Transactional Memory to allow safe mutable state changes. - Its focus on functions as first-class citizens and referential transparency can provide benefits for writing parallel and concurrent code more easily compared to other languages.

Every Java developer knows that multithreading is the root of all evil and it is quite hard to write correct code for concurrent environment. But what tasks do exist in real commercial development except running code in asynchronous way? In this talk I will present several tasks from my real projects and solutions we designed for them. This talk is very application oriented and allows participants to extend their vision of concurrent programming.

Modern Java concurrency has undergone significant changes since Java 5 with the introduction of java.util.concurrent (j.u.c.). While concurrency is not a new subject, j.u.c. provides constructs like ReentrantLock, ConcurrentHashMap, and Executors that make concurrent programming easier compared to traditional approaches. However, many applications still use older concurrency approaches despite j.u.c. being faster and more refined in recent Java versions. The document advocates upgrading applications to take advantage of modern concurrency features.

This document provides an overview of functional reactive programming (FRP) and compositional event systems (CES). It discusses how FRP approaches handling time-varying values like regular values. It presents an example of modeling game movements reactively using key press events. It also demonstrates how CES can be used to handle asynchronous workflows by turning network responses into observable streams. The document compares CES to other approaches like core.async and discusses benefits of CES like supporting multiple subscribers.

This slides explains why ConfigureAwait(false) needs to be called when we use async await. This slides is based on the following blog by Microsoft. https://devblogs.microsoft.com/dotnet/configureawait-faq/

Functional Programming is preferred since it uses pure functions and values and keeps side effects at bay. However, while building real-life applications, side effects are often needed in the scenario when, say, one needs to query a database or read from or write to the stream. If you’re facing this challenge in your projects too, then IO Monads can come to your rescue. Explore how using IO Monads, Scala developers can smoothly encapsulate side effects and write graceful programs while maintaining purity in Functional programming. 1. How to deal with side-effects in Scala in a purely functional way? 2. Important features like a) Synchronous and asynchronous computations b) Error handling c) Concurrency d) Parallelism e) Cancellation

The document discusses parallel programming in .NET. It covers two main strategies for parallelism - data parallelism and task parallelism. For data parallelism, it describes using Parallel.For to partition work over collections. For task parallelism, it discusses using the Task Parallel Library to create and run independent tasks concurrently, allowing work to be distributed across multiple processors. It provides examples of creating tasks implicitly with Parallel.Invoke and explicitly by instantiating Task objects and passing delegates.