One of the valuable services that blogs do is to help publicize things. Well, it always takes me a while to remember/figure out where Google hides their China street maps, so I might as well help the rest of the world remember as well: it is at
Don’t ask me why you have to go there to find the maps, why you can’t get to them via http://maps.google.com. I don’t know.
(You can see street maps of Hong Kong and satellite imagry of everywhere on http://maps.google.com.)
My buddy Vince tagged me with a chain blog thing. I have an allergic reaction to chain-anything (in part because of my experience with chain email letters), but this one looks kind of fun. I’m going to compromise by posting my six weird things but not by passing it on.
Six weird things about me:
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I made a shirt for Yeshe for Christmas. He’s been working in construction for six months, so…
All the tools are actual size. The nice people at Coe Lumber (3485 W. Broadway, Vancouver – (604) 731-6178) bemusedly allowed me to trace their tools onto vellum, and then I used white transfer paper (like carbon paper, but white) to transfer them to the shirt. Then it was merely a small matter of staying inside the lines.
I had fun at Coe Lumber. I was particularly pleased at finding the humongous adjustable crescent wrench. I bumped into one of the staff as I was taking it over to where my tracing paper was. My eyes were big as I said, “Look what I found! Isn’t it beautiful?!?!” The staff member had this look of, “uh, yeeeeeeeah, sure, lady”, but he laughed, too. 🙂
I wanted to make one for Tristan as well, but I wasn’t sure quite how to show his obsession: girls. I thought of painting silhouettes of girls’ arms embrassing him, with an abundance of kissmarks all over. I wasn’t sure, though, if it would be really really cool, really really embarassing, or both.
Instead, I made a promisorry note for him, with some examples of what kinds of things I could do. He was really taken with the idea of a tshirt that had a photo of a person printed on the chest, with filmstrip tracks (the things that look like ladders, that have holes for the sprockets of the film driver) on the sides of the photo, and cartoon versions of the photo below it.
If we do it right, we should be able to line up the neck of the tshirt with the neck of the person. The top frame would have a real person;. The next frame down would have a photo of a person (maybe Tristan?), and the next frame down would have a cartoon version of a person. Then, on the back, we could have upside-down versions of the same. (Or maybe images of the back of the head?)
That tshirt will be really really cool — assuming I can pull it off — but will also take a ton of work. I’m hoping that I can have it done by next Christmas!
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This morning I had a actual, genuine, real, honest-to-goodness I-forgot-to-take-an-exam nightmare — and I’m not even taking any classes this term.
My father said that he knew he was a grownup when he had a nightmare that he forgot to give an exam; I knew that I was a grownup when I had a dream that I had forgotten an exam and, even in the dream, was completely not concerned about it. I believe that was my first exam dream; today’s was definitely the only one since.
In this morning’s dream, a whole cavalcade of things were causing anxiety: not only had I forgotten to take my Econ class (in reality, I haven’t had an Econ class in my life), I had lost my wedding ring, and I needed to pee and fell in the toilet! (I’d also forgotten to start my History of Marriage term paper, but I wasn’t very concerned about that even in the dream because I could write that paper in my sleep, so to speak.)
My husband says that he gets nightmares when he gets too warm — that it’s the brain’s way of making you take off a blanket — but I wasn’t overly warm. I needed to pee, but it wasn’t urgent. It was 9:45 AM: Jim had gotten up at 6:30 AM to go flying, which messed up my sleep cycle and he turned off the alarm clock.
I think the dream was just my brain’s way of making me get my indolent posterior out of bed.
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What factors go into programmer productivity? I’ve been thinking about that a lot lately.
My recent reflections on the Curtis results and reflections on the Ko et al results of experiments of programmer productivity have focused on one narrow slice, what I call “hands-on-keyboard”. Hands-on-keyboard productivity is measured by how fast someone who is given a small, well-defined task can do that task. As I mentioned in those two blog posts, it is hard to measure even that simple thing.
In the wild, there are a huge number of factors that don’t bear on the types of experiments that Curtis and Ko et al did:
All of these things are very important — perhaps more important than the hands-on-keyboard productivity. I am starting to lose faith that differences in programmer productivity can be measured in a meaningful way. 🙁
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My experiences with Canadian bureaucracy have been surprisingly pleasant. For example:
In addition to being very pleasant to deal with, the Canadian bureaucracies seem much more flexible than U.S. ones. It seems that in the U.S., There Are Rules, and the individual agents have no discretion. In Canada, it seems like the agents have much more discretion to be reasonable.
This is probably due in part to a much smaller population, meaning fewer levels of bureaucracy. I suspect that it’s also due to smaller socioeconomic stratification. As Larissa Tieden’s research explains, humans think that low-status people do bad things. This means that if there are fewer low-status people dealing with the bureaucracy, then there will be less suspicion about them trying to “take advantage of the system”.
I’ve often thought about how income discrepancies hurt even the wealthy: they have to worry more about crime, for example. I hadn’t ever thought about how status discrepancies might make bureaucracy more annoying.
(Note that I have the impression that people think that European bureaucracies are worse than U.S. bureaucracies; perhaps this is due to greater emphasis on social class?)
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I found another paper that has some data on variability of programmers’ productivity, and again it shows that the differences between programmers isn’t as big as the “common wisdom” made me think.
In An Exploratory Study of How Developers Seek, Relate, and Collect Relevant Information during Software Maintenance Tasks, Andrew Ko et al report on the times that ten experienced programmers spent on five (relatively simple tasks). They give the average time spent as well as the standard deviation, and — like the Curtis results I mentioned before. (Note, however, that I believe Ko et al include programmers who didn’t finish in the allotted time. This will make the average lower than it would be if they waited for people to finish, and make the standard deviation appear smaller than it really is.)
| Task name | Average time | Standard deviation | std dev / avg |
|---|---|---|---|
| Thickness | 17 | 8 | 47% |
| Yellow | 10 | 8 | 80% |
| Undo | 6 | 5 | 83% |
| Line | 22 | 12 | 55% |
| Scroll | 64 | 55 | 76% |
These numbers are the same order of magnitude as the Curtis numbers (which were 53% and 87% for the two tasks).
Ko et al don’t break out the time spent per-person, but they do break out actions per person. (They counted actions by going through screen-video-captures, ugh, tedious!) While this won’t be an exact reflection of time, it presumably is related: I would be really surprised if 12 actions took longer than 208 actions.
I’ve plotted the number of actions per task in a bar graph, with each color representing a different coder. The y-axis shows the time spent on each task, with negative numbers if they didn’t successfully complete the task. (Click on the image to see a wider version.)
Looking at the action results closely, I was struck by the impossibility of ranking the programmers.
One thing that is very clear is that there is regression to the mean, i.e. the variability on all the tasks collectively is smaller than the variability on just one task. People seem to get stuck on some things and do well on others, and it’s kind of random which ones they do well/poorly on. If you look the coders who all finished THICKNESS, YELLOW, UNDO, and SCROLL, the spread is higher on the individual tests than the aggregate:
It also seemed like there was more of a difference between the median coder and the bottom than between the median and the top. This isn’t surprising: there are limits to how quickly you can solve a problem, but no limits to how slowly you can do something.
What I take from this is that when making hiring decisions, it is not as important to get the top 1% of programmers as it is to avoid getting the bottom 50%. When managing people, it is really important to create a culture where people will give to and get help from each other to minimize the time that people are stuck.
Google Maps now has multipoint routing! For example, see this map from LA to Chicago to Minneapolis to Miami to Houston.
I didn’t work on multipoint routing, but my cubemate did. 🙂
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I’ve heard a few people say that the most productive programmers are about 100x more productive than the least, but that didn’t seem to ring true to me. The only times that I’ve seen someone taking five months to produce as much as someone else could do in one day, it was a management problem. The low-productivity person was either goofing off or (more commonly) they were working on the wrong thing.
In Joelonsoftware, Joel reports (using data from Professor Stanley Eisenstat at Yale) that he sees about a 3x or 4x difference in the time students put into an assignment (with no effect of grades). However — and this is a big “however” — Prof. Eisenstat depends upon self-reporting from the students. Self-reporting is notoriously inacurate.
I have found it surprisingly hard to find good academic literature that measures productivity. I finally found a 1966 study by Sackman that showed a 28x difference. That number apparently got widely circulated, despite some sloppiness in its methods (as refuted by Dickey in 1981). A response to the concern by Curtis (1981) gave data that showed of about 8x and 13x min:max for two problems if and only if you tossed out one outlier who got stuck and didn’t finish that problem, timing out instead. Keeping the outlier, the 13x changed to 22x.
The outlier made me realize that the difference between the “best” programmer and the “worst” programmer is the wrong measure. You can make that number arbitrarily large by finding the right person to compare against. For example, I will be infinitely more productive than an infant. I will be infinitely more productive than someone who sleeps at his/her desk for their entire workday every day.
I would be far more interested in the standard deviation, or perhaps the productivity difference between the median and the top performer. What is the performance hit if I hire people within two standard deviations of the mean instead of trying for the ones who are better than two sigma above the mean? (This should looked at in conjunction with the cost hit of hiring the absolute best.)
This graph shows the time that it took to complete some tasks, and the number of people who took that long. (One person took between 65 and 70 minutes to complete Task 2, for example.)
Using Curtis’ data, I get that the median coder takes 2x or 3x the time that the top coder does for each of Curtis’ two tasks. (It’s not exact because the data was bucketed into five-minute intervals.) Interestingly, this is the same order of magnitude that Prof. Eisenstat found.
Note, however, that Curtis gives measures for one task. Because of regression to the mean, the variation is likely to decrease if you look at a lot of tasks. (Curtis even mentions that the outlier on Task #2 did fine on other tasks.)
The shapes of the curves are interesting: they are skewed to the left, which makes sense: there are limits to how much faster you can get, but not to how much slower you can get. They are also bimodal. This is more intriguing and mysterious, especially since Saeed and Bornat found that grades in intro CS classes are bimodal.
While this data comes from 1981, it’s the best I could find so far. (Please tell me if you have better data!) It’s distressing that we don’t have lots of good data on this — it seems like such fundamental data! However, it is really hard to do good studies like this. Ideally, you’d want a large number of programmers to all work on the same large number of complex problems. Unfortunately, it’s very difficult to get a large number of programmers to spend a large number of hours on non-useful problems.
The big message that I take from this data for my personal use is don’t get stuck. That’s easier said than done, I know. But look at it this way: if I learn new tricks for squeezing out incremental gains — like memorizing all the keyboard shortcuts — that isn’t going to help me nearly as much as not getting stuck. Keyboard shortcuts might give take me from 10 minutes to 9 minutes, but getting stuck can easily take me from 10 minutes to 100 minutes.
Now all I have to do is figure out how to not get stuck.
When we came to Vancouver, we were very puzzled by flashing green traffic lights. When we asked Canadians, they said that they were intersections where a pedestrian might push the button to turn the light red. The government-owned Insurance Corporation of British Columbia also describes the flashing green in that way.
This was not a terribly satisfactory answer to us, as most of the streetlights that we’ve seen had a button for pedestrians to cause the traffic light to change (although it sometimes would take a while).
The important thing to know about flashing green traffic lights in British Columbia is that the cross traffic has a stop sign, not a a stop light. This means
One problem with the flashing green traffic lights is that in (at least parts of) Nova Scotia, Ontario, Manitoba, New Brunswick, and Quebec, there are flashing green lights that mean the same as a green left arrow in most places: “oncoming traffic is stopped”. (There are some reports that this happens even in Vancouver suburbs.) It doesn’t work well when e.g. Ontario drivers come to Vancouver or vice versa!
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Considering retirement.