分析和性能分析是一回事。

然后我发现，虽然分析器总比没有强，但它包含错误的假设，比如:

只有总量才重要，细节无关紧要 统计精度是定位性能问题的必要条件 测量时间和定位不必要的耗时操作是一回事

这种编程是不可能的。

不是开玩笑的，我一直认为编程是一种不可能学会的东西，我总是远离它。当我接近代码的时候，我永远也无法理解它。

然后有一天，我坐下来阅读了一些基本的初学者教程，并从那里开始学习。现在我是一名程序员，我热爱工作的每一分钟。

另外，我认为编程并不容易，它是一个挑战，我更喜欢学习，没有什么比解决一些编程问题更有趣的了。

@Kyralessa: It's worth noting that on most processors, in assembly/machine language, it's possible for functions to return someplace other than their caller while leaving the stack in good condition. Indeed, there are a variety of situations where this can be useful. One variation I first saw on the 6502, though it works even better on the Z80, was a print-message routine where the text to be printed immediately followed the call instruction; execution would resume after the zero terminator (or, as a slight optimization when using the Z80, at the zero terminator, since letting the zero byte be executed as a NOP would be cheaper than trying to avoid it).

有趣的是，在许多现代语言中，函数都有一个正常的退出点(将在调用之后恢复执行)，但也可以通过抛出异常退出。即使在C语言中，也可以使用setjmp/longjmp来模拟这种行为。

作为一名老的过程式程序员，当我第一次开始为一个业余项目用Java编程时，我并不真正理解OO。编写了大量的代码，却没有真正理解接口的意义，试图通过将所有东西都强制放到继承层次结构中来最大化代码重用——当一个层次结构无法容纳清理时，希望Java具有多重继承。我的代码成功了，但我现在对早期的东西感到畏缩。

When I started reading about dynamic languages and trying to figure out a good one to learn, reading about Python's significant whitespace turned me off - I was convinced that I would hate that. But when I eventually learned Python, it became something I really like. We generally make the effort in whatever language to have consistent indent levels, but get nothing for it in return (other than the visual readability). In Python, I found that I wasn't doing any more effort than I had before with regard to indent levels, and Python handled what I'd been having to use braces or whatever for in other languages. It makes Python feel cleaner to me now.

软件的质量会带来更大的销量。有时确实如此，但并非总是如此。

在不浪费字节和CPU周期的情况下编写高效的程序是非常重要的。

但随着经验的积累，它与字节或CPU周期无关，它与你的思想流有关，连续的，不间断的，就像一首诗。

本质上，不要太努力。