---
created_at: '2014-12-14T22:22:38.000Z'
title: Advanced programming languages (2009)
url: http://matt.might.net/articles/best-programming-languages/
author: swah
points: 91
story_text: ''
comment_text: 
num_comments: 42
story_id: 
story_title: 
story_url: 
parent_id: 
created_at_i: 1418595758
_tags:
- story
- author_swah
- story_8749782
objectID: '8749782'
year: 2009

---
## Some advanced languages

## Haskell

[Haskell](http://www.haskell.org/) excels as a language for writing a
compiler, an interpreter or a static analyzer. I don't do a lot of
artificial intelligence, natural-language processing or machine-learning
research, but if I did, Haskell would be my first pick there too.
([Scheme](#scheme) would be a strong second.) Haskell is the only widely
used pure, lazy functional programming language.

Like Standard ML and OCaml, Haskell uses an extension of
[Hindley-Milner-style](http://en.wikipedia.org/wiki/Type_inference) type
inference, which means that the programmer doesn't have to write down
(most) types, because the compiler can infer them. It has been my
experience that it is difficult to get a bug through the Hindley-Milner
type system. In fact, experienced programmers become adept at encoding
correctness constraints directly into the Haskell type system. A common
remark after programming in Haskell (or ML) for the first time is that
once the program compiles, it's almost certainly correct.

As a pure language, side effects (mutations of variables or data
structures and I/O) are prohibited in the language proper. This has
forced the language's designers to think seriously about how to provide
such functionality. Their answer,
[monads](http://en.wikipedia.org/wiki/Monads_in_functional_programming),
enables one to perform side effects and I/O inside a safely constrained
framework. Naturally, Haskell lets users define their own monads, and
now the programmer has access to monads for continuations, transducers,
exceptions, logic programming and more.

Aside from being pure, Haskell is also lazy. That is, an expression in
Haskell is not evaluated until (and unless) its result is required to
make forward computational progress. Some have argued that the promised
efficiency gains from laziness haven't materialized, but that's not of
concern for me. I appreciate laziness for the increase in
expressiveness. In Haskell, it is trivial to describe data structures of
infinite extent. Where other languages permit mutually recursive
functions, Haskell permits mutually recursive values.

More pragmatically, I have found laziness useful in encoding option
types, where utilizing the empty case should always nuke the program. In
Haskell, you can avoid creating an option type and instead use `error`
to produce the empty value. Because of laziness, every type in Haskell
automatically has two additional values: non-termination and error. Used
well, this eliminates much tedious pattern matching.

My favorite feature of Haskell is type classes. Haskell's type system
allows the compiler to infer the correct code to run based on its type
context, even when that type context is also inferred. The example of
type classes that got me excited was bounded lattices. A [bounded
lattice](http://en.wikipedia.org/wiki/Lattice_\(order\)) is a
mathematical structure that has a least element (`bot`), a greatest
element (`top`), a partially ordered less than relation (`<:`), a join
operation (`join`) and a meet operation (`meet`).

In Haskell, one can define a bounded lattice as a type class:

``` 
  class Lattice a where
   top  :: a
   bot  :: a
   (<:) :: a -> a -> Bool
   join :: a -> a -> a
   meet :: a -> a -> a
  
```

This says that if type `a` is a `Lattice`, then `a` supports the
expected operations.

This says that if typeis a, thensupports the expected operations.

What I really love about Haskell is that it lets the programmer define
conditional instances of a class; for example:

``` 
  instance (Ord k, Lattice a) => Lattice (Map k a) where
   bot = Map.empty
   top = error $ "Cannot be represented."
   f <: g = Map.isSubmapOfBy (<:) f g
   f `join` g = Map.unionWith join f g
   f `meet` g = Map.intersectionWith meet f g
  
```

This rule says that if the type `k` is an instance of an order (class
`Ord`) and the type `a` is an instance of a lattice, then a map from `k`
to `a` is also an instance of a lattice.

This rule says that if the typeis an instance of an order (class) and
the typeis an instance of a lattice, then a map fromtois also an
instance of a lattice.

As another example, you can easily turn the Cartesian product of two
lattices into a lattice:

``` 
  instance (Lattice a, Lattice b) => Lattice (a,b) where
   bot = (bot,bot)
   top = (top,top)
   (a1,b1) <: (a2,b2) = (a1 <: a2) ||
                      (a1 == a2 && b1 <: b2) 
   (a1,b1) `join` (a2,b2) = (a1 `join` a2, b1 `join` b2)
   (a1,b1) `meet` (a2,b2) = (a1 `meet` a2, b1 `meet` b2) 
  
```

It's easy to make the "natural" lifting of the lattice operations,
relations and elements to almost any data structure. The end result is
that if you use the expression `bot` or the relation `<:` anywhere in
your code, Haskell can infer, at compile-time, their "appropriate"
meaning based on the type of the expression (which it can also infer).

The ML languages have functors to play the role of type classes, but
they lack the ad hoc polymorphism support of Haskell's type classes.
Having spent a considerable amount of time programming in the MLs and in
Haskell, the practical ramifications of inference on expressiveness
cannot be overstated.

### Favorite features

### Resources

  - [haskell.org](http://www.haskell.org/). Downloads, documentation,
    tutorials and more.
  - [The Glasgow Haskell Compiler (GHC)](http://www.haskell.org/ghc/).
    GHC provides robust support for Haskell on multiple platforms.
  - [Kathleen Fisher's
    slides](http://www.cs.tufts.edu/~kfisher/teaching.html) for her
    class at Stanford are a good introduction to Haskell.
  - [Real World Haskell](http://book.realworldhaskell.org/read/). As the
    title implies, this book pays attention to using Haskell for real
    applications (e.g., web programming), instead of just for compilers,
    interpreters and program analyzers.
    [![](images/51xQwhNrj6L._SL160_.jpg)](http://www.amazon.com/gp/product/0596514980?ie=UTF8&tag=ucmbread-20&linkCode=as2&camp=1789&creative=390957&creativeASIN=0596514980)![](http://www.assoc-amazon.com/e/ir?t=aboutmatthewm-20&l=as2&o=1&a=0596514980)

## Scala

[Scala](http://www.scala-lang.com/) is a rugged, expressive, strictly
superior replacement for Java. Scala is the programming language I use
for tasks like writing web servers or IRC clients. In contrast to
[OCaml](#ml), which was a functional language with an object-oriented
system grafted to it, Scala feels more like a true hybrid. That is,
object-oriented programmers should be able to start using Scala
immediately, picking up the functional parts only as they choose to.

I learned of Scala from [Martin
Odersky](http://icwww.epfl.ch/~odersky/)'s invited talk at POPL 2006. At
the time, I saw functional programming as strictly superior to
object-oriented programming, so I didn't see a need for a language that
fused functional and object-oriented programming. (That was probably
because all I wrote back then were compilers, interpreters and static
analyzers.)

The need for Scala didn't become apparent to me until I wrote a
concurrent HTTPD from scratch to support long-polled AJAX for
[yaplet](http://www.yaplet.com/). In order to get multicore support, I
wrote the first version in Java. I don't think Java is all that bad, and
I can enjoy well-done object-oriented programming. As a functional
programmer, however, the lack of terse support for functional
programming features (like higher-order functions) grates on me. So, I
gave Scala a chance.

Scala runs on the JVM, so I could gradually port my existing project
into Scala. It also means that Scala, in addition to its own rather
[large library](http://www.scala-lang.org/node/216), has access to the
entire Java library as well. This means you can get real work done in
Scala.

As I started using Scala, I became impressed by how tightly the
functional and object-oriented worlds had been blended. In particular,
Scala has a powerful case class/pattern-matching system that addressed
annoyances lingering from my experiences with Standard ML, OCaml and
Haskell: the programmer can decide which fields of an object should be
matchable (as opposed to being forced to match on all of them), and
variable-arity arguments are permitted. In fact, Scala even allows
programmer-defined patterns.

I write a lot of functions that operate on abstract syntax nodes, so
it's nice to match on only the syntactic children, while ignoring fields
for annotations or source location.

The case class system lets one split the definition of an algebraic data
type across multiple files or across multiple parts of the same file.
Scala also supports well-defined multiple inheritance through class-like
constructs called traits. And, Scala allows operator overloading; even
function application and collection update can be overloaded. Used well,
this tends to make my Scala programs more intuitive and concise.

One feature that turns out to save a lot of code, in the same way that
type classes save code in Haskell, is implicits. You can imagine
implicits as an API for the error-recovery phase of the type-checker. In
short, when the type checker needs an X but got a Y, it will check to
see if there's a function marked implicit in scope that converts Y into
X; if it finds one, it automatically applies the implicit function to
repair the type error.

Implicits make it possible to look like you're extending the
functionality of a type for a limited scope. For example, suppose you
want to "add" an `escapeHTML()` method to type `String`. You can't
modify the definition of `String`, but with implicits, you can make it
so that when type-checking fails on `myString.escapeHTML()`, it will
look for an implicit function in scope that can convert a `String`
object into a type that supports the `escapeHTML()` method.

Implicits also allow cleaner domain-specific embedded languages (DSELs)
in Scala, since they allow you to transparently map Scala literals (like
`3` or `"while"`) into literals in the DSEL.

### Favorite features

  - [JVM](http://java.sun.com/docs/books/jvms/) support.
  - Intelligent [operator
    overloading](http://en.wikipedia.org/wiki/Operator_overloading).
  - Extensive library.
  - Case classes/pattern matching.
  - Extensible pattern matching.
  - Multiple inheritance via traits.
  - Rich, flexible object constructors.
  - Implicit type conversions.
  - [Lazy fields and
    arguments](http://en.wikipedia.org/wiki/Lazy_evaluation).

### Related blog articles

### Resources

  - [scala-lang.org](http://www.scala-lang.org/). Downloads,
    documentation, tutorials and more.
  - [Programming in
    Scala](http://www.amazon.com/gp/product/0981531601?ie=UTF8&tag=ucmbread-20&linkCode=as2&camp=1789&creative=390957&creativeASIN=0981531601)![](http://www.assoc-amazon.com/e/ir?t=ucmbread-20&l=as2&o=1&a=0981531601)
    by Martin Odersky (creator of Scala), Lex Spoon, and Bill Venners is
    great as both an introduction and a reference.

## Standard ML and OCaml

The ML family is a sweet spot in the language-design space: strict,
side-effectable and Hindley-Milner type-inferred. This makes these
languages practical for real-world projects that need high performance
and stronger guarantees of correctness. The ML family has gained
traction with aerospace engineers (for its support of bug-free code) and
with programmers in the financial industry (for the same reason).
Standard ML was the first functional language I learned well, so I still
remember being shocked by its expressiveness.

Today, OCaml seems to be the popular ML to learn, but there is at least
one convincing argument in SML's favor: [MLton](http://www.mlton.org/).
MLton really delivers on the thesis that functional languages offer the
best opportunities at optimization. As a whole-program optimizing
compiler, I've yet to see another compiler match its performance. I once
created OpenGL bindings for MLton to toy around with 3D graphics, and
the resulting program ran faster than the C++-based model I had used as
a reference, with just 10% of the code.

The functor system in SML, while more verbose than Haskell's type class
system, is more flexible. Once you instantiate a type class `T` for a
kind/type `k` in Haskell, you can't instantiate that type class again
for that kind/type. With functors, each instance gets its own name, so
you can have multiple instances of a given functor for the same type.
It's rarely been the case that I needed such expressiveness, but it has
been nice in those cases where I have.

The other modern branch on the ML family tree, OCaml, is good to know
because there is a large community invested in it, which means that
there are a lot of libraries available. The OCaml tool-chain is also
rich, with interpreters, optimizing compilers and byte-code compilers
available to the developer.

Because the ML languages are more expressive than all the mainstream
languages, but they still permit side effects, they make a nice stop on
the way to learning Haskell. In Haskell, programmers not yet well versed
in functional program design may find they repeatedly code themselves
into a corner, where they don't have access to the monad that they need.
The MLs keep the side effects "escape hatch" open to patch over
incomplete design, which prevents projects from coming to a sudden,
unexpected "refactor-or-abort" decision point. One useful measure of a
language is how well it tolerates a bad or incomplete design for the
software system, since design is something that inevitably changes as a
program evolves. In this regard, the MLs still have the upper hand over
Haskell.

### Favorite features

  - Flex records. (SML only)
  - Pattern matching.
  - [Structures and
    functors](http://en.wikipedia.org/wiki/Standard_ML#Module_System).

### Resources

## Scheme

Scheme is a language with a pure core (λ-calculus and the theory of
lists) and a design mandate to maximize freedom of expression. It's
untyped, which makes it ideal for web-based programming and rapid
prototyping. Given its Lisp heritage, Scheme is a natural fit for
artificial intelligence.

With its support for arbitrary-precision numerics, Scheme is also my
first choice for implementing cryptographic algorithms. \[For examples,
see my short implementations of
[RSA](../implementation-of-rsa-public-key-cryptography-algorithm-in-scheme-dialect-of-lisp/)
and the [Fermat and Solovay-Strassen primality
tests](../implementation-of-fermat-and-solovay-strassen-primality-tests-for-rsa-key-generation-in-scheme-dialect-of-lisp/)
in Scheme.\]

By far, the most compelling reason to use Scheme is its macro system.
All of the macro systems available for Scheme, including the standard
`syntax-rules` and `syntax-case` systems, are Turing-equivalent.

Consequently, the programmer can reconfigure Scheme to reduce the
impedance mismatch between the language and the task at hand. Combined
with support for first-class continuations, it is even possible to embed
alternate programming paradigms (like logic programming).

For example, in the code:

``` 
  (let ((x (amb 3 4 5))
        (y (amb 6 7 8 )))
    (assert (= (+ x y) 12))
    (display x)
    (display y))  
```

it is possible to write an `amb` macro that "chooses" the right argument
to make a subsequent `assert` statement be true. (This program prints 4
and then 8.)

it is possible to write anmacro that "chooses" the right argument to
make a subsequentstatement be true. (This program prints 4 and then 8.)

In Scheme, during any point in the computation, the program can capture
the current continuation as a procedure: invoking this procedure returns
the program to the evaluation context that existed when the continuation
was captured. Programming with continuations feels like traveling back
and forth in time and shifting between parallel universes.

Ultimately, Scheme is so minimal and extensible that there's not a whole
lot to say about it, except that Scheme allows the programmer to extract
from the language whatever the programmer is willing to put into it.

### Favorite features

### Related blog articles

### Resources

  - [Racket](http://www.racket-lang.org/) (formerly PLT Scheme) is a
    "batteries included" Scheme system, including a battle-tested IDE, a
    compiler and an interpreter. More importantly, the Racket library is
    immense: it has a module that adds a type system to the language; it
    has a module that adds pattern-matching; it has a module for OpenGL
    programming; and it has a module for continuation-based web servers.
    In Racket, there's already a module for just about everything.
  - The best book I've seen on Racket -- [Realm of
    Racket](http://www.amazon.com/gp/product/1593274912/ref=as_li_ss_tl?ie=UTF8&camp=1789&creative=390957&creativeASIN=1593274912&linkCode=as2&tag=aboutmatthewm-20)![](http://ir-na.amazon-adsystem.com/e/ir?t=aboutmatthewm-20&l=as2&o=1&a=1593274912)
    -- introduces the features of the language through game programming:
    [![](http://ws-na.amazon-adsystem.com/widgets/q?_encoding=UTF8&ASIN=1593274912&Format=_SL160_&ID=AsinImage&MarketPlace=US&ServiceVersion=20070822&WS=1&tag=ucmbread-20)](http://www.amazon.com/gp/product/1593274912/ref=as_li_ss_il?ie=UTF8&camp=1789&creative=390957&creativeASIN=1593274912&linkCode=as2&tag=ucmbread-20)![](http://ir-na.amazon-adsystem.com/e/ir?t=ucmbread-20&l=as2&o=1&a=1593274912)
  - [Chicken scheme](http://www.call-with-current-continuation.org/) is
    a hacker-friendly implementation of Scheme.
  - [Gambit
    Scheme](http://dynamo.iro.umontreal.ca/~gambit/wiki/index.php/Main_Page)
    is popular for lower-level programming in Scheme, including iPhone
    and iPad programming.
  - [R6RS](http://www.r6rs.org/). The current Scheme standard.
  - I recommend all Scheme programmers keep a copy of [Guy
    Steele](http://research.sun.com/people/mybio.php?uid=25706)'s
    [Common LISP: The
    Language](http://www.amazon.com/gp/product/1555580416?ie=UTF8&tag=ucmbread-20&linkCode=as2&camp=1789&creative=390957&creativeASIN=1555580416)![](http://www.assoc-amazon.com/e/ir?t=ucmbread-20&l=as2&o=1&a=1555580416)
    around. After Guy Steele developed Scheme, which is a minimalist
    expression of the λ-calculus as a programming language, he designed
    Common Lisp, which is a maximalist expression of the λ-calculus as a
    programming language.
    [![](images/41VJS8YPYML._SL160_.jpg)](http://www.amazon.com/gp/product/1555580416?ie=UTF8&tag=ucmbread-20&linkCode=as2&camp=1789&creative=390957&creativeASIN=1555580416)![](http://www.assoc-amazon.com/e/ir?t=aboutmatthewm-20&l=as2&o=1&a=1555580416)
  - [Structure and Interpretation of Computer
    Programs](http://www.amazon.com/gp/product/0070004846?ie=UTF8&tag=ucmbread-20&linkCode=as2&camp=1789&creative=390957&creativeASIN=0070004846)![](http://www.assoc-amazon.com/e/ir?t=ucmbread-20&l=as2&o=1&a=0070004846)
    is a classic. Until recently, this was the textbook for freshman
    computer science at MIT. It teaches computer science by teaching
    students how to implement interpreters.
