Eclipse内存分析器:

使用Lengauer-Tarjan支配树算法进行内存使用分析。

当然，1980年以前是施乐PARC的辉煌时期。在图形用户界面、鼠标、激光打印机、互联网和个人电脑刚刚诞生的时候。(鉴于我太年轻了，不可能活在那个年代，而你几乎在努力发明所有这些东西，关于1980年的事情，我不能告诉你任何你不知道的事情，所以我们继续吧。)

The thing is, though, that the pre-1980 days were a lot more vibrant in terms of truly disruptive new technologies. That's the way it is with any new field -- hwo many game-changing technology advances have you seen in railroads in the past 100 years? How many have you seen in lightbulbs? In the printing press? Once something ignites a hype in the right circles, there is an explosive period of invention, followed by a long period of maturing. After that, you're not going to see the same kind of completely radical changes again UNLESS the basic circumstances change.

幸运的是，这可能会发生在一些领域，而且已经发生在其他一些领域:

Mobility - smart phones bring computing to a truly portable platform, which will soon include location-based services and proximity-based ad-hoc networks. It's a completely new paradigm that's potentially as game-changing as the GUI has been The WWW (HTTP, HTML and DNS) has already been mentioned and is an obvious addition to the list, since it is enabling global, inexpensive, mainstream rich communication across the globe - all thanks to a computing platform On the interface side, both touch, multitouch (Jeff Han comes to mind) and the Wiimote need mentioning. Currently, they are basically curiosities, but so were the early GUIs. OOP design patterns -- higher level solutions as best practices to hard problems. Depending on your definition of 'computing', it may or may not belong on the list, but if you count OOP as a significant advance pre-1980 (I certainly do), I think design patterns and the GoF deserve a mention too Google's PageRank and MapReduce algorithms - I am pleased to notice I wasn't the first to mention them, and seriously --- where would the world be without the principles of both of them? I vividly remember what the world looked like before them, and suffice it to say Google really IS my friend. Non-volatile memory -- it's on the hardware side, but it is going to play a significant role in the future of computing - making bootup times a thing of the past, for example, and enabling us to use computers in entirely new ways Semantic (natural language) search / analysis / classification / translation... We're not quite there yet, but companies like Powerset give the impression that we're on the brink. On that note, intelligent HTMs should be on this list as well. I am yet another believer in Jeff Hawkins' model and approach, and if it works, it will mean a complete redefinition of what computers can do, what it means to be human, and where the world can go from here. Creating a real intelligence in that way (synthetically) would be bigger than anything the human race has accomplished before. GNU + Linux 3D printing / rapid prototyping (and, in time, manufacturing) P2P (which also lead to VoIP etc.) E-ink, once the technologies mature a bit more RFID might belong on the list, but the verdict is still out on that one Quantum Computing is the most obvious element on the list, except we still haven't been able to get enough qubits to play along. However, my friends in the field tell me there's incredible progress going on even as we speak, so I'm holding my breath for that one. And finally, I want to mention a personal favourite: distributed intelligence, or its other name: artificial artificial intelligence. The idea of connecting a huge number of people in a network and allowing them access to the combined minds of everyone else through some form of question answering interface. It's been done a number of times recently, with Yahoo Answers, Askville, Amazon Mechanical Turk, and so on, but in my mind, those are all missing the mark by a LOT... much like the many implementations of distributed hypertext that came before Tim Berners-Lee's HTML, or the many web crawlers before Google. Seriously -- someone needs to build an search interface into 'the hive mind' to blow everyone else out of the water. IMHO - it is only a matter of time.

多代理系统。

你可以回到分布式人工智能的根源，我认为仍然可以安全地呆在80年代。

多智能体系统有很多组成部分，有很多研究涉及语言行为或合作，所以很难指出并说“看，这里，这是不同的，创新的和重要的!”但我还是会试试的。: -)

我认为信念-欲望-意图模型尤其值得注意。智能体在内部构建了世界的模型。他们有特定的愿望或目标，并制定计划，如何与他们所知道的世界互动，以实现这些目标，从而形成意图。

或者打个比方，电影《创》(Tron)中的角色对他们周围的世界是如何运作的有一定的了解。他们不了解整个世界，他们可能会对世界的某些部分产生误解。但他们有愿望和目标，他们提出了进一步实现目标的计划。如果你看过《创》，我相信你会有类似的感觉。

它还没有对计算机产生太大的影响。但是，你看，那些对计算机产生影响的东西似乎需要几十年的时间。参见:OOP, GC，字节码编译。

自1980年以来，关于社会计算的想法已经取得了进展。油井工程始于1985年。虽然我确信以前有在线社区，但我相信该领域的一些真正的见解发生在1980年之后。社会社区的不利动态方面及其在软件系统上的交互很像塔科马海峡大桥的灾难。

我认为Clay Shirky在该领域的工作阐明了这些影响以及如何减轻它们。我想说，社交软件洞察力的有趣的现实世界的例子包括reCAPTCHA和维基百科，其中重要的有价值的工作是由软件调解的参与者完成的。

飞行汽车和悬浮滑板。哦，等等，那些还没有被发明出来。但到2015年，我们必须拥有它们。否则《回到未来2》就是个弥天大谎!

即时消息已经出现很长时间了(60年中后期)，但是IRC在1988年之前还没有出现。

除此之外，视频通讯(比如，Windows Live Messenger，或Skype，或……)确实改变了我们的沟通方式;)而且是最近才出现的。

<修改> (见VideoConferencing: 1968, alt text http://wpcontent.answers.com/wikipedia/en/thumb/6/64/On_Line_System_Videoconferencing_FJCC_1968.jpg/180px-On_Line_System_Videoconferencing_FJCC_1968.jpg，正如Alan Kay自己在评论中指出的那样:

请再次查看恩格尔巴特在1968年演示的内容(包括实时视频聊天和屏幕共享)。低，猜测真的没有查东西管用。这就是为什么大多数人对事物的发明时间做不充分的假设。)

把它放在我的脸上;)，这是理所当然的。

注意:那个时代的“网络摄像头”(视频设置)并不是为普通的客厅设计的;)

> < /修正

[…继续回答:]

网络摄像头替代文本http://wpcontent.answers.com/wikipedia/commons/thumb/c/c5/Logitech_Quickcam_Pro_4000.jpg/180px-Logitech_Quickcam_Pro_4000.jpg的推广也有帮助(始于1991年，第一个这样的摄像头，称为CoffeeCam，是针对剑桥大学计算机科学系的特洛伊房间咖啡壶)。

所以:80后:2 / 3:IRC和网络摄像头。