“美国人没有过去，也没有未来，他们生活在一个延伸的现在。”这描述了计算的状态。我们生活在80年代一直延续到21世纪。唯一改变的是尺寸。Alan Kay

来源: Alan Kay:计算机科学是一种矛盾修饰法吗?

我认为我们需要真正的新想法 在计算机的大部分领域，我 想知道有什么重要的吗 以及已经完成的强有力的任务 最近。如果我们真的找不到 他们，那么我们应该问“为什么? “我们该怎么办?”

在我看来，我们在计算领域没有那么多新想法，因为我们在很大程度上不需要它们。我们一直在挖掘旧的想法，并从中获得了很多东西，比如cpu速度的显著增长。

当我们因为“井干了”而需要新想法时，我们就会明白需求是发明之母。

Damas-Milner type inference (often called Hindley-Milner type inference) was published in 1983 and has been the basis of every sophisticated static type system since. It was a genuinely new idea in programming languages (admitted based on ideas published in the 1970s, but not made practical until after 1980). In terms of importance I put it up with Self and the techniques used to implement Self; in terms of influence it has no peer. (The rest of the OO world is still doing variations on Smalltalk or Simula.)

类型推断的变化仍在上演;我最喜欢的变体是Wadler和Blott的解决重载的类型类机制，后来发现它为类型级别的编程提供了非常强大的机制。这个故事的结局还在书写中。

我认为自20世纪80年代以来发明的最好的想法将是我们不知道的。要么是因为它们很小，无处不在，以至于不引人注意，要么是因为它们的受欢迎程度还没有真正起飞。

前者的一个例子是单击并拖动以选择文本的一部分。我相信这是1984年首次出现在麦金塔电脑上。在此之前，您有单独的按钮用于选择选择的开始和结束。相当繁重。

后者的一个例子是(可能是)可视化编程语言。我不是说像hypercard，我是说像Max/MSP, Prograph, Quartz Composer, yahoo pipes等。目前它们确实是小众的，但我认为，除了思想分享之外，没有什么能阻止它们像标准编程语言一样具有表现力和强大的功能。

可视化编程语言有效地加强了引用透明性的函数式编程范式。这对于代码来说是一个非常有用的属性。他们执行这一点的方式也不是人为的——这只是由于他们使用的比喻。

VPL让那些本来不会编程的人也能编程，比如有语言障碍的人，比如阅读困难的人，甚至只是需要简单节省时间的门外汉。专业程序员可能会对此嗤之以鼻，但就我个人而言，我认为如果编程成为一种真正无处不在的技能，就像识字一样，那就太好了。

就目前来看，VPL只是一个小众的兴趣，还没有真正成为主流。

我们应该做些什么不同的事情

all computer science majors should be required to double major- coupling the CS major with one of the humanities. Painting, literature, design, psychology, history, english, whatever. A lot of the problem is that the industry is populated with people that have a really narrow and unimaginative understanding of the world, and therefore can't begin to imagine a computer working any significantly differently than it already does. (if it helps, you can imagine that I'm talking about someone other than you, the person reading this.) Mathematics is great, but in the end it's just a tool for achieving. we need experts who understand the nature of creativity, who also understand technology.

But even if we have them, there needs to be an environment where there's a possibility that doing something new would be worth the risk. It's 100 times more likely that anything truly new gets rejected out of hand, rather viciously. (the newton is an example of this). so we need a much higher tolerance for failure. We should not be afraid to try an idea which has failed in the past. We should not fully reject our own failures- and we should learn to recognize when we have failed. We should not see failure as a bad thing, and so we shouldn't lie to ourselves or to others about it. We should just get used to it, because it is just about the only constant in this ever changing industry. Post mortems are useful in this regard.

One of the more interesting things, about smalltalk, I think, was not the language itself, but the process that was used to arrive at the design of smalltalk. The iterative design process, going through many many revisions- But also very carefully and critically identifying the flaws of the existing system, and finding solutions in the next one. The more perspectives, and the broader the perspectives we have on the situation, the better we can judge where the mistakes and problems are. So don't just study computer science. Study as many other academic subjects as you can get yourself to be interested in.

我相信单元测试、TDD和持续集成是1980年之后的重大发明。

这是谷歌map-reduce的一个插件，不仅是为了它自己，也是谷歌在不可靠的商品机器农场上运行快速、可靠服务的成就的一个代理。这绝对是一项重要的发明，与1980年主导重量级计算的大型主机方法完全不同。