Dart vs Haskell

Dart is a single threaded programming language. So if any piece of code blocks the execution of the program, the program practically freezes. To avoid this Dart makes use of asynchronous operations which let your program run without getting blocked. This is done through Future objects.

A Future is an object which represent a means for getting a value at a certain point in the future. A function may invoke a Future and when that happens, two outcomes can be achieved:

1. The function is unable to return a value, so it queues up work to be done and returns an uncompleted Future object.
2. Or later when a value is available to be returned, the Future object completes with that value.

Dart includes a truly comprehensive core library, making it unnecessary to include disparate, external resources for basic functionalities Other than reducing the need to pull in various 3rd-party utilities this also ensures that all Dart code looks and feels the same.

Out of the box, the developer gets core libraries to help with: async, collections, strings, regexps, conversions, formats, file I/O, math, typed data, and more.

Dartium (Chromium derivative) is a browser with integrated Dart VM, which allows you to run and debug native Dart code during development for short edit-reload cycles. Only for testing on other browsers and deployment is transpiling to JS necessary.

Dart has a lot of tools available which help with developing Dart applications. Some examples of those tools include:

• pub - package and dependency management and build tool
• analyzer - static syntax analysis with linter, quick fixes, autocompletion support for easy IDE integration
• test - powerful and flexible testing framework and test runner
• dev_compiler - generate reusable JS instead of tree-shaken minified JS output (work in progress)
• dartfmt_ - source code formatter
• server-side VM
• observatory - a powerful tool for profiling and debugging running Dart code (for Dartium and Dart server code)

In Dart many browser differences (subtle differences and also missing features) are abstracted away or polyfilled. When Dart is transpiled to JS the output works on all supported browsers. There is usually no need to load polyfills or to consider browser differences during development. No need for libraries like jQuery to make the same code work the same on all browsers.

The language will look familiar to Java developers, easing the learning curve.

And yet, while it's similar, it has some nice syntax facilities to avoid common boilerplate code found in Java. Code is terser, yet readable.

Dart has an optional type system which makes Dart a great language for prototyping. It encourages developers to gradually evolve their programs without worrying about types first.

Dart was designed to be as expressive as possible. Ahead-of-time compilers can compile Dart code to efficient machine code. This is especially important when deploying to mobile where you don't want (or can't) use a JIT.

Strong mode applies a more restrictive type system to Dart to address its unsound, surprising behavior in certain cases.

Generators, also known as semicoroutines, are also a generalization of subroutines.
Generators are primarily used to simplify the control of iteration behavior of a loop, the yield statement in a generator passes a value back to a parent routine.

A generator is very similar to a function that returns an array, in that a generator has a certain number of values. But instead of building and returning an array that contains all the wanted values, a generator returns them one at a time, this saves memory and allows the caller function to start processing the first few values immediately.

Dart to Javascript compiler (dart2js) generates very high quality source code with very high optimization. The output code is also very readable and easy to understand.

Dart does not just compile to JavaScript, it also compiles to native code on mobile platforms like iOS and Android as demonstrated by flutter.io

Haskell's referential transparency, consistency, mathematics-oriented culture, and heavy amount of abstraction encourage problem solving at a very high level. The fact that this is all built upon little other than function application means that not only is the thought process, but even concrete solutions are very transferable to any other language. In fact, in Haskell, it's quite common for a solution to simply be written as an interpreter that can then generate code in some other language. Many other languages employ language-specific features, or work around a lack of features with heavy-handed design patterns that discourage abstraction, meaning that a lot of what is learned, and a lot of code that is needed to solve a particular problem just isn't very applicable to any other language's ecosystem.

It is pure and does not mix other programming paradigms into the language. This forces you to learn functional programming in its most pure form. You avoid falling back on old habits and learn an entirely new way to program.

All Haskell implementations are completely free and open source.

As Haskell lends itself exceedingly well to abstraction, and borrows heavily from the culture of pure mathematics, it means that a lot more code conforms to very high-level abstractions. You can expect code from vastly different libraries to follow the same rules, and to be incredibly self-consistent. It's not uncommon to find that a parser library works the same way as a string library, which works the same way as a window manager library. This often means that getting familiar and productive with new libraries is often much easier than in other languages.

Haskell's Purely Functional approach means that code is referentially transparent. This means that to read a function, one only needs to know its arguments. Code works the same way that expressions work in Algebra class. There's no need to read the whole source code to determine if there's some subtle reference to some mutable state, and no worries about someone writing a "getter" that also mutates the object it's called on. Functions are all directly testable in the REPL, and there's no need to remember to call methods in a certain order to properly initialize an object. No breakage of encapsulation, and no leaky abstractions.

Conciseness of Haskell lets us to write the expression on the whiteboard or paper and discuss with others easily. This is a strong benefit to learn FP over other languages.

The base language relies primarily on function application, with a very small amount of special-case syntax. Once you know the rules for function application, you know most of the language.

It's often said that, in Haskell, if it compiles, it works. This short feedback loop can speed up learning process, by making it clear exactly when and where mistakes are made.

Every function that expects more than one arguments is basically a function that returns a partially applied function. This is well-suited to function composition, elegance, and concision.

Haskell is a very terse language, particularly due to its type inference. This means there's nothing to distract from the intent of the code, making it very readable. This is in sharp contrast to languages like Java, where skimming code requires learning which details can be ignored. Haskell's terseness also lends itself to very clear inline examples in textbooks, and makes it a pleasure to read through code even on a cellphone screen.

Haskell is really popular in universities and academia as a tool to teach programming. A lot of books for people who don't know programming are written around Haskell. This means that there are a lot of resources for beginners in programming with which to learn Haskell and functional programming concepts.

Since the basic syntax is very similar to mathematics, Haskell syntax should be easy for people who have taken higher math courses since they would be used to the symbols used in maths.

Makes categorical higher order abstractions easy to use and natural to the language.