What is Xtend and what are its top alternatives?
Xtend is a statically-typed programming language that compiles to readable Java source code. It aims to improve upon Java by adding advanced features like lambda expressions, type inference, and extension methods. Xtend simplifies coding through concise syntax and powerful tools for code generation. However, one limitation of Xtend is its dependency on Java, which can hinder compatibility with other programming languages and environments.
- Kotlin: Kotlin is a statically-typed language that is fully interoperable with Java. Key features include concise syntax, null safety, extension functions, and coroutine support. Pros: Easy integration with existing Java code, reduced verbosity, and strong tooling support. Cons: Learning curve for Java developers and potential performance overhead.
- Scala: Scala is a powerful language that combines object-oriented and functional programming paradigms. It offers advanced features like pattern matching, higher-order functions, and type inference. Pros: Expressive language features, extensive standard library, and strong community support. Cons: Steeper learning curve, complex syntax, and potential performance overhead.
- Groovy: Groovy is a dynamic language that seamlessly integrates with Java. It features concise syntax, dynamic typing, and metaprogramming capabilities. Pros: Easy learning curve for Java developers, enhanced developer productivity, and support for DSLs. Cons: Performance issues compared to statically-typed languages, limited tooling support, and potential maintenance challenges.
- Ceylon: Ceylon is a modular language with a strong focus on readability and developer productivity. It boasts features like type inference, union types, and powerful type system constraints. Pros: Concise syntax, strong interoperability with Java, and emphasis on modularity and abstraction. Cons: Limited adoption and community support, potential learning curve for new developers, and slower compilation times.
- Elixir: Elixir is a functional language built on the Erlang VM known for its fault-tolerance and scalability. It offers features like immutable data structures, pattern matching, and lightweight concurrency. Pros: Robust ecosystem, easy parallelism, and fault-tolerant design. Cons: Limited adoption outside of certain domains, potential performance trade-offs, and smaller developer community.
- Closure: Clojure is a functional Lisp dialect that emphasizes simplicity, immutability, and functional programming principles. It provides features like persistent data structures, software transactional memory, and expressive syntax. Pros: Rich ecosystem of libraries, support for concurrent programming, and versatile language features. Cons: Steep learning curve due to Lisp syntax, potential performance overhead, and limited tooling compared to mainstream languages.
- Rust: Rust is a systems programming language known for its focus on safety, speed, and concurrency. It offers features like memory safety, zero-cost abstractions, and fearless concurrency. Pros: High performance, memory safety guarantees, and strong tooling support. Cons: Steeper learning curve, strict compiler rules, and potential challenges with complex data structures and algorithms.
- Swift: Swift is a modern, open-source language developed by Apple for iOS, macOS, watchOS, and tvOS development. It features safety, performance, and expressiveness through features like optional types, generics, and first-class functions. Pros: Easy-to-learn syntax, strong type system, and interoperability with Objective-C. Cons: Limited support for platforms outside of Apple ecosystem, potential tooling issues on platforms other than macOS, and evolving language features.
- Haskell: Haskell is a purely functional language known for its strong type system, laziness, and advanced language features like type classes, monads, and immutability. Pros: Expressive language features, mathematical purity, and strong emphasis on correctness. Cons: Steeper learning curve, potential performance overhead, and limited adoption in mainstream development.
- TypeScript: TypeScript is a superset of JavaScript that adds static typing, classes, interfaces, and other features to the language. It aims to improve developer productivity and code quality in large-scale JavaScript applications. Pros: Type safety, tooling support, and gradual adoption for existing JavaScript projects. Cons: Learning curve for JavaScript developers, potential overhead of type annotations, and build step required for compilation.
Top Alternatives to Xtend
- Kotlin
Kotlin is a statically typed programming language for the JVM, Android and the browser, 100% interoperable with Java ...
- Java
Java is a programming language and computing platform first released by Sun Microsystems in 1995. There are lots of applications and websites that will not work unless you have Java installed, and more are created every day. Java is fast, secure, and reliable. From laptops to datacenters, game consoles to scientific supercomputers, cell phones to the Internet, Java is everywhere! ...
- OpenCL
It is the open, royalty-free standard for cross-platform, parallel programming of diverse processors found in personal computers, servers, mobile devices and embedded platforms. It greatly improves the speed and responsiveness of a wide spectrum of applications in numerous market categories including gaming and entertainment titles, scientific and medical software, professional creative tools, vision processing, and neural network training and inferencing. ...
- Helix
Helix allows you to write Ruby classes in Rust without having to write the glue code yourself. ...
- PostSharp
It adds design patterns and thread safety to C# and VB so you can avoid boilerplate and focus on business value. ...
- Cursive
It is the Clojure(Script) IDE that understands your code. Advanced structural editing, refactorings, VCS integration and much more, all out of the box. ...
Xtend alternatives & related posts
Kotlin
- Interoperable with Java73
- Functional Programming support55
- Null Safety50
- Official Android support46
- Backed by JetBrains44
- Concise37
- Modern Multiplatform Applications36
- Expressive Syntax28
- Target to JVM27
- Coroutines26
- Open Source24
- Practical elegance19
- Statically Typed19
- Type Inference17
- Android support17
- Readable code14
- Powerful as Scala, simple as Python, plus coroutines <313
- Better Java12
- Pragmatic10
- Lambda9
- Target to JavaScript8
- Better language for android8
- Expressive DSLs8
- Used for Android6
- Less boilerplate code6
- Fast Programming language5
- Less code5
- Less boiler plate code4
- Functional Programming Language4
- Native4
- Friendly community4
- Spring3
- Official Google Support3
- Latest version of Java2
- Well-compromised featured Java alternative1
- Java interop makes users write Java in Kotlin7
- Frequent use of {} keys4
- Hard to make teams adopt the Kotlin style2
- Nonullpointer Exception2
- Friendly community1
- Slow compiler1
- No boiler plate code1
related Kotlin posts
Hi Community! Trust everyone is keeping safe. I am exploring the idea of building a #Neobank (App) with end-to-end banking capabilities. In the process of exploring this space, I have come across multiple Apps (N26, Revolut, Monese, etc) and explored their stacks in detail. The confusion remains to be the Backend Tech to be used?
What would you go with considering all of the languages such as Node.js Java Rails Python are suggested by some person or the other. As a general trend, I have noticed the usage of Node with React on the front or Node with a combination of Kotlin and Swift. Please suggest what would be the right approach!
In our company we have think a lot about languages that we're willing to use, there we have considering Java, Python and C++ . All of there languages are old and well developed at fact but that's not ideology of araclx. We've choose a edge technologies such as Node.js , Rust , Kotlin and Go as our programming languages which is some kind of fun. Node.js is one of biggest trends of 2019, same for Go. We want to grow in our company with growth of languages we have choose, and probably when we would choose Java that would be almost impossible because larger languages move on today's market slower, and cannot have big changes.
Java
- Great libraries599
- Widely used445
- Excellent tooling400
- Huge amount of documentation available395
- Large pool of developers available334
- Open source208
- Excellent performance202
- Great development157
- Used for android150
- Vast array of 3rd party libraries148
- Compiled Language60
- Used for Web52
- High Performance46
- Managed memory46
- Native threads44
- Statically typed43
- Easy to read35
- Great Community33
- Reliable platform29
- Sturdy garbage collection24
- JVM compatibility24
- Cross Platform Enterprise Integration22
- Universal platform20
- Good amount of APIs20
- Great Support18
- Great ecosystem14
- Backward compatible11
- Lots of boilerplate11
- Everywhere10
- Excellent SDK - JDK9
- It's Java7
- Cross-platform7
- Static typing7
- Mature language thus stable systems6
- Better than Ruby6
- Long term language6
- Portability6
- Clojure5
- Vast Collections Library5
- Used for Android development5
- Most developers favorite4
- Old tech4
- History3
- Great Structure3
- Stable platform, which many new languages depend on3
- Javadoc3
- Testable3
- Best martial for design3
- Type Safe2
- Faster than python2
- Job0
- Verbosity33
- NullpointerException27
- Nightmare to Write17
- Overcomplexity is praised in community culture16
- Boiler plate code12
- Classpath hell prior to Java 98
- No REPL6
- No property4
- Code are too long3
- Non-intuitive generic implementation2
- There is not optional parameter2
- Floating-point errors2
- Java's too statically, stronglly, and strictly typed1
- Returning Wildcard Types1
- Terrbible compared to Python/Batch Perormence1
related Java posts
How Uber developed the open source, end-to-end distributed tracing Jaeger , now a CNCF project:
Distributed tracing is quickly becoming a must-have component in the tools that organizations use to monitor their complex, microservice-based architectures. At Uber, our open source distributed tracing system Jaeger saw large-scale internal adoption throughout 2016, integrated into hundreds of microservices and now recording thousands of traces every second.
Here is the story of how we got here, from investigating off-the-shelf solutions like Zipkin, to why we switched from pull to push architecture, and how distributed tracing will continue to evolve:
https://eng.uber.com/distributed-tracing/
(GitHub Pages : https://www.jaegertracing.io/, GitHub: https://github.com/jaegertracing/jaeger)
Bindings/Operator: Python Java Node.js Go C++ Kubernetes JavaScript OpenShift C# Apache Spark
When you think about test automation, it’s crucial to make it everyone’s responsibility (not just QA Engineers'). We started with Selenium and Java, but with our platform revolving around Ruby, Elixir and JavaScript, QA Engineers were left alone to automate tests. Cypress was the answer, as we could switch to JS and simply involve more people from day one. There's a downside too, as it meant testing on Chrome only, but that was "good enough" for us + if really needed we can always cover some specific cases in a different way.