What should I learn from Scheme?

Question

I was wondering what unique features I can learn from Scheme that would help me become a better programmer?

I have a lot experience in mainstream languages, and I am looking to expand my horizons and learn about functional aspects that are missing from other languages. I am familiar with closures from javascript, lambda expressions from C#, and I was wondering what I can focus on that is lacking in other languages? Aside from the Lisp syntax, I feel like what I have seen so far I've already encountered in other languages.

What is unique to Scheme/Lisp that will teach me something new?

Answer 1

Perhaps the most important defining characteristic of Lisp is "Code as Data."  You won't get that experience in quite the same way with any other language. In C#, the closest analogue is expression trees.

It is that quality that makes Lisp an excellent language for parsing. It's also the quality that motivated Paul Graham to say of Lisp: "The unusual thing about Lisp-- in fact, the defining quality of Lisp-- is that it can be written in itself." Although self-hosting compilers are nothing new, no language does it quite as elegantly as Lisp does.

Metaprogramming (something in which Lisp also excels) is also a worthwhile thing to learn.

Beating the Averages by Paul Graham
http://www.paulgraham.com/avg.html

Answer 2

Yes, it will help you think in a recursive fashion. I only studied it (scheme) for a month or so in a programming language class and it helped me evolve how I think and solve programming problems.

It is always valuable to try other programming paradigms; you then return refreshed to the OO world with new ideas.

Not the syntax, but the reasoning, it is great brain exercise. Appart from recursion and the interesting use of lists, there is not much else IMHO, but it is well worth it.

Answer 3

Continuation :

In computer science and programming, a continuation is an abstract representation of the control state of a computer program. A continuation reifies the program control state, i.e. the continuation is a data structure that represents the computational process at a given point in the process' execution; the created data structure can be accessed by the programming language, instead of being hidden in the runtime environment. It contains information such as the process' current stack (including all data whose lifetime is within the process e.g. "local variables"), as well as the process' point in the computation. An instance of continuation can be later used as a control structure; upon invocation, it will resume execution from the control point that it represents. The "current continuation" or "continuation of the computation step" is the continuation that, from the perspective of running code, would be derived from the current point in a program's execution.

and then try to implement McCarthy's Ambiguous Operator :

In 1963 John McCarthy, the inventor of Lisp, published the paper A Basis for a Mathematical Theory of Computation in which he proposed the function (in the computer program sense of the word) amb(.,.). The idea is that amb(x,y) is first equal to x. But if later in the computation it is found that this leads to some sort of contradiction the value of x is retracted and replaced with y. This is a much more complex business than it may seem to be at first. Retracting a value essentially means winding back the entire state of the computation to where it was when amb returned the value x, and then slipping in the value of y. This means somehow freezing and copying the entire state when x was first returned. When a contradiction is found the entire state of the program is discarded and replaced with the frozen version which is reactivated. These frozen states are known as continuations. In many ways it's like a GOTO statement on acid. It can cause a jump to an arbitrary spot on your code. But continuations are nicer than GOTOs because they are more amenable to logical reasoning.

Answer 4

I can think of the following:

• Real macros (using the full power of the language to generate code)
• Homoiconicity (data as code, code as data)
• Lazy evaluation
• Continuations

I also think lisp languages should be awesome to define domain specific languages (DSL). That's something you might want to read about if you don't know about it already.