Eloquent JavaScript 第三版草稿

时间:2021-1-8 作者:admin

When action grows unprofitable, gather information; when information grows unprofitable, sleep.

A program is many things. It is a piece of text typed by a programmer, it is the directing force that makes the computer do what it does, it is data in the computer’s memory, yet it controls the actions performed on this same memory. Analogies that try to compare programs to objects we are familiar with tend to fall short. A superficially fitting one is that of a machine—lots of separate parts tend to be involved, and to make the whole thing tick, we have to consider the ways in which these parts interconnect and contribute to the operation of the whole.

A computer is a machine built to act as a host for these immaterial machines. Computers themselves can do only stupidly straightforward things. The reason they are so useful is that they do these things at an incredibly high speed. A program can ingeniously combine an enormous number of these simple actions in order to do very complicated things.

A program is a building of thought. It is costless to build, it is weightless, and it grows easily under our typing hands.

But without care, a program’s size and complexity will grow out of control, confusing even the person who created it. Keeping programs under control is the main problem of programming. When a program works, it is beautiful. The art of programming is the skill of controlling complexity. The great program is subdued—made simple in its complexity.

Some programmers believe that this complexity is best managed by using only a small set of well-understood techniques in their programs. They have composed strict rules (“best practices”) prescribing the form programs should have, and carefully stay within their safe little zone.

This is not only boring, it is also ineffective. New problems often require new solutions. The field of programming is young and still developing rapidly, and is varied enough to have space for wildly different approaches. There are many terrible mistakes to make in program design, so go ahead and make them so that you understand them better. A sense of what a good program looks like is developed in practice, not learned from a list of rules.

Why language matters

In the beginning, at the birth of computing, there were no programming languages. Programs looked something like this:

00110001 00000000 00000000
00110001 00000001 00000001
00110011 00000001 00000010
01010001 00001011 00000010
00100010 00000010 00001000
01000011 00000001 00000000
01000001 00000001 00000001
00010000 00000010 00000000
01100010 00000000 00000000

That is a program to add the numbers from 1 to 10 together and print out the result: 1 + 2 + ... + 10 = 55. It could run on a simple, hypothetical machine. To program early computers, it was necessary to set large arrays of switches in the right position or punch holes in strips of cardboard and feed them to the computer. You can probably imagine how tedious and error-prone this procedure was. Even writing simple programs required much cleverness and discipline. Complex ones were nearly inconceivable.

Of course, manually entering these arcane patterns of bits (the ones and zeros) did give the programmer a profound sense of being a mighty wizard. And that has to be worth something in terms of job satisfaction.

Each line of the previous program contains a single instruction. It could be written in English like this:

1\. Store the number 0 in memory location 0.
2\. Store the number 1 in memory location 1.
3\. Store the value of memory location 1 in memory location 2.
4\. Subtract the number 11 from the value in memory location 2.
5\. If the value in memory location 2 is the number 0,
   continue with instruction 9.
6\. Add the value of memory location 1 to memory location 0.
7\. Add the number 1 to the value of memory location 1.
8\. Continue with instruction 3.
9\. Output the value of memory location 0.

Although that is already more readable than the soup of bits, it is still rather obscure. Using names instead of numbers for the instructions and memory locations helps.

 Set “total” to 0.
 Set “count” to 1.
[loop]
 Set “compare” to “count”.
 Subtract 11 from “compare”.
 If “compare” is zero, continue at [end].
 Add “count” to “total”.
 Add 1 to “count”.
 Continue at [loop].
[end]
 Output “total”.

Can you see how the program works at this point? The first two lines give two memory locations their starting values: total will be used to build up the result of the computation, and count will keep track of the number that we are currently looking at. The lines using compare are probably the weirdest ones. The program wants to see whether count is equal to 11 in order to decide whether it can stop running. Because our hypothetical machine is rather primitive, it can only test whether a number is zero and make a decision (or jump) based on that. So it uses the memory location labeled compare to compute the value of count - 11 and makes a decision based on that value. The next two lines add the value of count to the result and increment count by 1 every time the program has decided that count is not 11 yet.

Here is the same program in JavaScript:

let total = 0, count = 1;
while (count <= 10) {
  total += count;
  count += 1;
}
console.log(total);
// → 55

This version gives us a few more improvements. Most importantly, there is no need to specify the way we want the program to jump back and forth anymore. The while language construct takes care of that. It continues executing the block (wrapped in braces) below it as long as the condition it was given holds. That condition is `count

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