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Peter Norvig Seibel: And do you think that changes the kind of people who can be successful at programming now Norvig: I think the people that are really successful are the same at least that s what I see around here. But, yeah, it is a little bit more of, Can I quickly get an understanding of what I need, and less of, I need complete understanding. I think some of it is bravado, this willingness to say, I m just going to go ahead and do it, the fearlessness of saying, I don t understand everything that s going on, but I went into the documentation and I learned these three things. I tried it and it worked, so I m just going to go ahead. That gets you to a certain point, but I think to really be a good programmer, you can t just do that. You have to understand a little bit more, and say, Is it safe, what I m doing here Or what are the failure cases Sure, I tried it once and it worked, but is it always going to work How do I write test cases to show that and to understand it a little better, and then once I ve done that, can I extract what I ve done and publish a new tool that other people can use because I ve put these pieces together in a certain way. Seibel: How did you like to work on a team when you were a programmer Is it better to take the problem and split it up so everybody gets their piece Or do you like the XP model of pair-program everything and everybody owns all the code collectively Norvig: I guess it s more break it up. Steve Yegge s got this Good Agile, Bad Agile piece. I think he s about right. Ten percent of the time it is a really good idea to sit down together because you want that shared understanding. I think most of the time you re not going to be as effective. If you have two good programmers, it s better for them to work independently and then debug each other s work afterwards rather than to say, We ll take a 50 percent hit just for that added set of eyes. I think it is important to get together when you re figuring out what it is you want to do both in terms of brainstorming what is the problem we re trying to solve and what is the functionality going to be here You don t even know what the product is before you start. That you really want to do together. Then you get to the point of saying, OK, now we know what we want to do. How are we going to divide it up That you want to do together. Once you have a pretty good idea, I think you re better off
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Peter Norvig spending most of the time on your own. You want feedback, so I think you should require every piece of code to be reviewed by another set of eyes, but it doesn t have to be real-time, when you re writing it. I remember the IBM master-programmer idea, and that just seemed like the dumbest thing I have ever heard of. Why would anybody want to subject themselves to being a gopher for the one real programmer Seibel: I m surprised you think the master-programmer model is such a dumb idea. In your Teach Yourself Programming in Ten Years essay you make the point that programming is a skill that, like many skills, probably takes about a decade to really master. And lots of crafts had master/journeymen/apprentice kind of hierarchies. So maybe nobody wants to be the apprentice, but maybe it isn t crazy to say that somebody who s been through that decade-long learning experience should be doing different work than someone who s fresh out of school. Norvig: I think the best part of the apprentice approach is that you get to watch the master, and I would like to see more of that. So I guess that s another use of pair programming. I can see that it d be really good, if you were inexperienced, to watch somebody who s much more experienced. Particularly for the types of things that aren t taught as much, like debugging skills. Anybody can learn algorithms and so on, but they don t really teach debugging and watching someone, and saying, Wow, I never thought of doing that, that s really useful. But I think part of the reasons why you had master and apprentice is because the materials were rarer. When you were doing goldsmithing, there s only so much gold. Or when the surgeon s operating, there s only one heart, and so you want the best person on that and you want the other guys just helping. With coding, it s not like that. You ve got plenty of terminals. You ve got plenty of keyboards. You don t have to ration it. Seibel: Speaking of things that aren t taught as much, you ve been both an academic and in industry; do you feel like academic computer science and industrial programming meet in the right place Norvig: It s a big question. I don t think there s a lot of waste in computerscience curriculum. I think that it s mostly very good stuff to know. I think
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