erlang 关于学习“如何进行功能性思考”的建议?

zlwx9yxi  于 2022-12-08  发布在  Erlang
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As a newbie in functional languages (I started touching Erlang a couple of weeks ago -- the first functional language I could get my hands on).
I started to writing some small algorithms (such as left_rotate_list , bubble_sort,merge_sort etc.). I found myself often getting lost in decisions such as "should I use a helper List for intermediate result storage?" and "should I create a helper function to do this?"
After a while, I found that functional programming (bear with me if what I am talking does not make sense at all) encourages a "top down" design: i.e., when I do merge_sort, you first write down all the merge sort steps, and name them as individual helper functions; and then you implement those helper functions one by one (and if you need to further dividing those helper functions, do it in the same approach).
This seems to contradict OO design a little, in which you can start from the bottom to build the basic data structure, and then assemble the data structure and algorithms into what you want.
Thanks for comments. Yes, I want to get advice about how to "think in functional language" (just like "thinking in Java", "thinking in C++").

5lwkijsr

5lwkijsr1#

An answer is that functional programming is to program using functions, as they are defined in mathematics (in short, side-effect free things that map values from the domain to the codomain). To actually translate that into "how to think" is the hand-waving part that is difficult to be exhaustive about, but I'll sample some of my thoughts:

  1. The definition is more important than the efficiency. That is, an obviously correct implementation of a function that one can understand all of the behaviour of is better than a complex optimized one that is hard to reason about. (And should be preferred as long as possible; until there is evidence one must break this nice property.)
  2. A mathematical function has no side-effects. A useful program must have side-effects. A functional programmer is aware of side effects, as a very dangerous and complicating thing, and designs the program as a bunch of functions that take output values from one side-effect and creates input values to the next side-effect.
    Number one is associated with the vague: "elegant code". List comprehensions can present very succinct and mathematical-equations like definitions of functions. Just look at the quick-sort implemented with LCs. This is how I define elegance, succinct and makes all behaviours clear. Not that perl code-golf where you are most often terse and cryptic.
    Number two is something that I use day to day in all programming. Divide code into functions (methods, routines, etc...) of current state that are side-effect free computations giving inputs to the next action to take (even which the next action to take is). When the value is returned, give it to a routine that performs the action that is described, then start over.
    In my head I diagram an Erlang process as a state machine graph, where each vertex is a side-effect and a function whose output is which edge to chose out of the vertex. The high regard of side-effects is something the functional programming paradigm taught me. Especially in Erlang, since side-effects really matter in concurrency, and Erlang makes concurrency very available.
    The same way some isolated tribes have only one word for numbers above 3, or no words for "mine"/"yours". It feels like popular languages do not have words for "this will cause a side-effect", but Functional Programming has it. It is forcing you to be aware of it all the time, and that is a good thing.
vbopmzt1

vbopmzt12#

After a while, I found that functional programming [...] encourages a "top down" design.
Well, it's not about "top down" or "bottom up" design really. It's about focusing on the "what" of the problem at hand, rather than the "how". When I started off with functional programming, I found that I kept recalling imperative constructs like the nested for loop in C. Then I quickly found out that trying to translate my imperative thinking to functional constructs was very difficult. I'll try to give you a more concrete example. I'll implement an equivalent program in C and Haskell and attempt to trace my thought process in both cases. Note that I've been explicitly verbose for the purpose of explanation.
In C:

#include <stdio.h>

int main(void)
{
  int i, inputNumber, primeFlag = 1;
  scanf("%d", &inputNumber);
  for(i = 2; i <= inputNumber / 2; i ++)
    {
      if (inputNumber % i == 0)
        {
          primeFlag = 0;
          break;
        }
    }
  if (primeFlag == 0) printf("False\n");
  else printf ("True\n");
  return 0;
}

Trace of my thought process:

  1. Think in steps. First, accept a number from the user. Let this number be called inputNumber . scanf() written.
  2. Basic algorithm: A number is prime unless otherwise proven. primeFlag declared and set equal to 1 .
  3. Check primeNumber against every number from 2 to primeNumber/2 . for loop started. Declared a loop variable i to check primeNumber against.
  4. To disprove our initial assertion that the number is prime, check primeNumber against each i . The moment we find even one i that divides primeNumber , set primeFlag to 0 and break . Loop body written.
  5. After going through our rigorous checking process in the for loop, check the value of primeFlag and report it to the user. printf() written.
    In Haskell:
assertPrime :: (Integral a) => a -> Bool
assertPrime x = null divisors
    where divisors = takeWhile (<= div x 2) [y | y <- [2..], mod x y == 0]

Trace of my thought process:

  1. A number is prime if it has no divisors but one and itself. So, null divisors .
  2. How do we build divisors ? First, let's write down a list of possible candidates. Wrote down Texas range from 2 to number/2.
  3. Now, filter the list, and pick out only items that are really divisors of the number. Wrote the filter mod x y == 0
    I want to get advice about how to "think in functional language"
    Ok, first and foremost, think "what", not "how". This can take a lot of practice to get used to. Also, if you were formerly a C/C++ programmer like me, stop worrying about memory! Modern languages have a garbage collector, and it's written for you to use- so don't even try to modify variables in place. Another thing that has personally helped me: write down English-like definitions in your program to abstract out the functions that do the heavy-lifting.
sxpgvts3

sxpgvts33#

过了一段时间,我发现函数式编程[...]鼓励“自上而下”的设计。
我不确定这是不是一个准确的说法。我最近一直在自学函数式编程,我发现一种“自底向上”的编程风格对我很有帮助。用你的合并排序的例子来说:

  • 首先看看基本情况。如何对0/1元素的数组进行排序?
  • 接下来,看看base + 1,base + 2,...案例。最终,你应该看到一个模式(拆分成子问题,求解子问题,组合子解决方案),它允许你编写一个最终到达基本案例的一般递归案例。
  • 拆分成子问题很容易,但是合并子解有点困难。你需要一种方法将两个排序数组合并成一个排序数组。
  • 现在把所有的东西放在一起。恭喜你,你已经编写了merge sort。:)

我可能误用了这个术语,但对我来说,这感觉像是自底向上的设计。函数式编程 * 不同于 * 面向对象编程,但在两者之间切换时,您不应该完全放弃现有的设计技术。

rqenqsqc

rqenqsqc4#

我发现自己经常迷失在诸如“我是否应该使用helper List来存储中间结果?”和“我是否应该创建一个helper函数来实现这一点?”之类的决策中。
对此我的建议是:读The Little Schemer。你可以用Erlang来理解它。这是一本很好的书,可以让你深入了解它。

qc6wkl3g

qc6wkl3g5#

习惯于认为数据可以用作代码,* 反之亦然 *,这是很重要的。
通常,您使用几个基本操作(折叠、嵌套、线程、分布......,以及一些广义内积、外积等)来构造程序(数据),并使用此程序(数据)来操作其他数据。
过了一段时间,我发现函数式编程[...]鼓励“自上而下”的设计。
我同意。

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