Exploration Through Example

UPDATE: Turns out that what I want to do, modeled after something used for RubyConf, can’t be done in stock Twitter. Seeing if I can persuade the Twitter people to work the same magic for me.

Item: Richard P. Gabriel has this habit of making software people write or speak within artificial constraints.

• For writers’ workshops (book-length PDF), he’s made reviewers write a summary exactly 29 words long.

• In last OOPSLA’s “50 in 50” keynote, he and Guy Steele, Jr., covered the last five decades of programming languages in 50 segments, each exactly 50 words long (in a talk lasting, I believe, about 50 minutes).

The point of constraints is that they make you work: you can’t use the words that first come to mind. You have to struggle to say what you want while playing by the rules them—and sometimes that makes you realize you ought to be wanting to say something else. Constraints are a tool to make you think new thoughts.

Item: I’ve become strangely fond of Twitter. It’s a service that lets you send short (140 character) “tweets” out into the ether. Other people can subscribe to (”follow”) your tweets. They can see the tweets of everyone they follow by visiting their own twitter web page (here’s mine), subscribing to an RSS feed, or using a twitter-specific app to fetch tweets. (I use Twitterrific.)

That’s form: what about content? As Twitter user shalunov (Stanislav Shalunov) puts it (in a tweet):

Four main ways to tweet: ideas, news, @-chat, phatic coffee. The last is the original, rest invented by users.

Ideas are the tweets I’m most interested in. Slalunov’s is an example of an idea tweet.

News is my second interest. As a geographically isolated person, it’s one way of knowing what interesting people are chattering about.

• bilkleb, for example, is fond of linking to both technical topics (“heard Paul Tuckfield talk about scaling YouTube MySQL, “mirror disk drives in hardware, stripe in software.” (http://tinyurl.com/277dvy)”, “watching Matz’s Google Talk: http://tinyurl.com/3bzbuu“) and not-technical ones (“@barbjordan http://kluster.com looks interesting.”)

• Twitter’s also a good way for me to learn about new and interesting apps for the Mac.

• …and I follow lrz because he’s Apple’s Ruby guy, so what he does will affect my next book.

• …and there’s also the quick links to the absurd and humorous that’ve been around since the beginning of the web, like this from andytinkham: “This is just wrong, wrong, wrong (on so many levels): http://tinyurl.com/2zjpz5“ or this from objo: “hilarious http://rubyurl.com/DdyJ (via @timbray)”.

“@-chat” is a sort of person-to-person instant messaging. For example, cypher23 wrote “Stalker is a weird and wonderful film.” I replied: “@cypher23 Harrison’s new _Nova Swing_ is in the sub-sub-genre with Stalker, _Rogue Moon_, and _Roadside Picnic_. Liking it so far.” Anyone following cypher23 would see both his tweet and my reply. Someone following only me would see only my reply (but could click on the hyperlinked cypher23 to see all his recent tweets). Because of the one-sidedness, and because the topics tend to be less interesting than those in the first two categories, I tend not to follow people who have a high proportion of @-chat in their tweets.

“Phatic coffee” is just tweeting what you’re doing now, like avibryant’s recent “obsessively refreshing UPS tracking page for new laptop” Although I’m somewhat of a hermit and not much for social chit-chat, I’m not immune to phaticality. (I find chadfowler’s heavily phatic tweets appealing, oddly puckish, and somehow soothing.) But I likely won’t follow someone who’s predominantly phatic.

Item: While writing a book, I often find myself disinclined to spend spare time writing blog posts. Yet I continue to have ideas. I’m sure lots of other people do too.

Synthesis: I’ve created a fake twitter user named pithysoft. It’s for anyone’s pithy tweets about software development. When I finish this post, I’ll send the first one: “d pithysoft Business-facing tests are like personal ads: No matter how exact your description, the reality always tells you something new.” People following pithysoft will see it. If the pithy claim intrigues them, they can tweet pithysoft with something like “@marick More about tests and personal ads, plz”. That would encourage me to write it up on my blog. When I did that, I could tweet “@pithysoft Expanded on XYX here: XYX”

An experiment. Let’s see how it goes.

Jason Gorman compares Scrum to a virus. He uses the example of a DNA virus that destroys the cells it infects. But it could be an endogenous retrovirus that infects the DNA of germ (reproductive) cells and thereby takes over an entire species. From an interesting New Yorker article:

It takes less than two per cent of our genome to create all the proteins necessary for us to live. Eight per cent, however, is composed of broken and disabled retroviruses, which, millions of years ago, managed to embed themselves in the DNA of our ancestors. They are called endogenous retroviruses, because once they infect the DNA of a species they become part of that species.

There is even some evidence that:

without endogenous retroviruses mammals might never have developed a placenta, which protects the fetus and gives it time to mature. That led to live birth, one of the hallmarks of our evolutionary success over birds, reptiles, and fish. Eggs cannot eliminate waste or draw the maternal nutrients required to develop the large brains that have made mammals so versatile. “These viruses made those changes possible,’’ Heidmann told me. “It is quite possible that, without them, human beings would still be laying eggs.”

So that kind of Scrum-as-a-virus could be a positive and enduring good (though there’s a lot of suffering amongst the “early adopters”).

I had a thought at the Simple Design and Test conference.

“Simple” is an adjective, but there are different kinds of adjectives. For example, one might point at a can and say that the adjective “blue” applies to it. That use of the adjective is objectively true, at least in Richard Rorty’s sense: we use the adjective “objective” to describe those statements it’s pretty easy to get people to agree about. The harder it is to get people to agree, the more subjective the statement.

However, suppose the can contains iced coffee. I claim that the adjective “tasty” does not apply, but other people would disagree. Here’s an adjective that quite clearly depends not just on the object it labels but also on the person doing the labeling.

Finally, consider a bed labeled “comfortable”. To be more specific, suppose it’s a waterbed. A waterbed might be extremely comfortable for sleeping, but someone I trust tells me it wouldn’t be comfortable when making love, and I’m quite sure that no waterbed would be a comfortable platform for doing deadlifts. Here we have a case where the suitability of the adjective is bound up with both the person applying it and the activity they’re thinking about.

I claim that “simple”, when it comes to “design and test”, is most like the third category. In a way, when we say “that’s a simple design”, what we should be saying is “that design lets me do actions X, Y, and Z without friction and with ease.”

So: when we talk about what properties make, say, a design “simple,” we’re using shorthand: “I’ve noticed that property X is usually associated with designs that make activities A, B, and C easy.” The fact that we have a hard time getting people to recognize or desire simple designs suggests that we maybe ought to focus on understanding and explaining the activities over capturing the properties.

A transcript of an OOPSLA talk: Table of contents

Update 1, update 2, update 3: Added links to some useful reviews.

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A transcript of an OOPSLA talk: Table of contents

Here is the table of contents for a set of postings that, together, are a transcript of an OOPSLA talk on Bruno Latour and Actor-Network Theory (ANT). I will add links as I post new entries.

1. Testing as an example: I use Actor-Network theory as a way to get ideas while consulting. Here’s one example.

2. ANT and the building of the social: ANT is about tracing how “actors” (people and things) in a story push on each other. Stable patterns of interaction produce social objects like neighborhoods.

3. Anthrax and standups: ANT analyses often give uncommon weight to inanimate objects. How that gave me an idea to make standups less dull.

4. An ANT reading list.

5. The divide: Early Agile, especially XP, had an ANTian delight in the interplay between the social and tools. That’s being lost. Someone should do something about it.

A transcript of an OOPSLA talk: Table of contents

Shift gears now to the daily standup. There’s a ritual: someone says what she did yesterday, what she plans to do today, and what impediments she sees in the team’s path. Good standups are crisp and motivating. A lot of standups are bad. They have the enervating effect of an hour-plus weekly status meeting, only spread out over a week.

Why is this? And what can be done about it?

To answer, I’ll start with the story of the anthrax bacillus from Latour’s The Pasteurization of France. At one point, there was a disease called “anthrax.” People understood the properties of this disease: they knew what symptoms it had, they knew that people could contract the disease from warm corpses but not from cold or rotten ones, and they knew that some “accursed” fields gave anthrax to any animal that grazed there.

Pasteur wanted to replace anthrax-the-disease with anthrax-a-bacillus. He undertook a fairly systematic programme:

• Early on, he could induce the symptoms of anthrax by extracting icky stuff from a sick animal, diluting it fantastically, and then injecting a tiny bit of the dilute solution into a new animal. However: so? No one sneaks around at night injecting cows in fields.

• So the next step is to induce anthrax by a more natural means. They tried feeding the animals hay laced with anthrax, but that didn’t give them the disease. However, a feed more representative of real life—feed containing prickly nettles—did. So there’s a realistic way animals can get the disease that’s directly traceable to the idea of injection.

• What about the slaughterhouse workers and the safe corpses? Well, it turns out that anthrax forms spores to ride out harsh environments: like the cold, nasty environment of a dead animal. That’s a plausible explanation for what renderers know. One more bit of anthrax-the-disease can be explained in terms of anthrax-the-bacillus.

• There’s even a reason for accursed fields. Suppose someone buries an animal dead of anthrax. You’ve basically buried a whole pile of spores. In dirt. That contains earthworms. One of the things that earthworms do is turn dirt over, moving dirt from down below to the surface. As a side-effect, they steadily replenish the surface with spores. Result: an accursed field, perhaps accursed well after the last person’s forgotten anything was buried there.

• And, finally, you can do more with the bacillus than you can with the disease. In particular, you can make a vaccine.

At some point, anthrax-the-disease can be understood in terms of anthrax-the-bacillus. Roles switch: now if you want to say something about the disease, you have to be prepared to trace that statement back to the bacillus.

In the jargon, the bacillus has become an obligatory point of passage.

One of the things we’ve done in Agile is to make the frequent creation of running, tested, potentially shippable software into an obligatory point of passage. Teams that don’t produce potentially shippable software at the end of each iteration are likely in trouble. Moreover, team members ought to be able to trace what they’re doing to the goals of the release; if not, they ought to be prepared to question what they’re doing.

In order to understand and pace the work of the release, it’s convenient to break it down into smaller pieces, individual stories. The stories are also individual points of passage, just littler ones.

Dull standups often make no reference to visible stories. Either people don’t have a wall with stories on it, they don’t do the standup in front of that wall, or they don’t gesture at the wall while speaking. In ANTian terms, they’re demonstrating that the stories aren’t really obligatory points of passage. What to do about that?

Another trick of ANT’s is not to bother making a distinction between humans and other kinds of actors. So, when Kent Beck writes, in the introduction to Smalltalk Best-Practice Patterns, “If you’re programming along, and all of a sudden your program gets balky, makes things hard for you, it’s talking,” an ANT analysis wouldn’t report that with a side-comment like “Of course, programs don’t really get balky.” Lots of programmers talk as if code can push back, so why not take them at their word and see what comes of that?

A while back, I was thinking along these lines when I realized that if the stories are so important to the project, they ought to be the ones speaking in the standup. I imagined a story card saying, “Brian’s going to keep working on me today, but he’s having trouble. He could use the help of someone who knows Hibernate.”

Now, I never had the nerve to actually suggest that team members ought to hold the story cards like little mouths, open and close them, and pretend it was the stories talking, but while I was preparing for this talk, I had another thought. Yes, the stories can’t talk, but there’s no reason not to structure the standup around them. Instead of going around the people, you can step through all the stories in play. For each, someone can say what happened to that story yesterday, what’s to be done on it today, and whether there are any risks to its completion.

I plan to recommend that clients give this a try. At least, it will cut out conversational deadeners like “I paired with Dawn and Karl, so I did the same thing they did” and “I can’t remember what I did.” [I’m also pleased that two people said they’d try it on their teams when they got home.]

So, there: another example of using a weirdo theory from sociologist to give myself ideas.

Story board from arbdesign.dk, woman with fish from Willem Velthoven.

A transcript of an OOPSLA talk: Table of contents

Why does Actor-Network Theory (ANT) care so much about things? Latour explains in terms of baboons. Baboons usually have a pretty good life. They don’t have to spend a whole lot of time looking for food, but they do need protection from predators. That means they need to live in packs to survive. How do they keep the packs functioning well? In the words of the Agile Manifesto, they spend a lot of time attending to individuals and interactions. In fact, they spend all their free time attending to individuals and interactions. As a result, they have no time to write software.

We humans have a trick: we substitute things for social forces. Latour uses the example of policemen. Let’s say that society has decided that people should drive slowly down a particular stretch of road. People being what they are, sometimes some of them will want to drive fast instead. One way to prevent that is to station a policeman by the side of the road. That person exerts a social force that will cause people to slow down.

But then we’d be like the baboon: devoting a lot of time to maintaining group norms. Unlike the baboons, though, we have an alternative:

In the US, we call these “speed bumps.” In other parts of the world, they’re called “sleeping policemen.” (The model pictured is a Rediweld Sitecop sleeping policeman.)

Through a different mechanism, the sleeping policeman has the same social effect as a human policeman: slower cars and an environment matching collective preferences.

We can take this a step further. Consider neighborhoods. Many sociologists might explain the existence of neighborhoods by appealing to powerful abstract forces like power, class, or racism. An ANT explanation, by contrast, might start with speed bumps.

Consider a car as an “actor” that can affect—push on, act as a force upon—other actors, specifically children. Speeding cars are a danger to children, and they affect their behavior. Children aren’t allowed to play near streets where cars travel fast.

Now suppose speed bumps are put up across those streets. The speed bumps mediate or “translate” the effect of cars on children. The cars become less dangerous. Parents (another set of actors) are more likely to allow children to play outside. As many parents know, children who are playing together outside soon invade houses in packs. Parents come to know the nearby children. And, inevitably, they come to know those childrens’ parents. They begin trading favors like driving children around. They become neighborly.

Now, speed bumps by themselves don’t create a neighborhood, but there are lots of other physical objects that have similar effects, and they keep having these effects, day in and day out. The continual recurrence (”circulation”) of all these forces, all these actors affecting other actors, is (according to ANT) a sufficient explanation for the “assembly” of a neighborhood. We don’t need to bring abstractions like power into the equation.

Does that make neighborhoods somehow less real than cars? (Is ANT purely materialist?) To Latour, neighborhoods are as real as cars if the people in the story talk about them that way. For example, the city council in my town would, if you asked them, say my neighborhood is real. Some time ago, the city wanted to replace our antique street lamps with ugly modern street lamps. The neighborhood pushed back and got more expensive street lamps that fit better with our lovely old brick streets and old trees. To the city council and the people reading about the brouhaha in the newspaper, the neighborhood was an actor that changed things. To Latour, it would be arrogant for an analyst on the outside to tell us that our neighborhood isn’t really real. ANT comes with a respect for the ontology of the people doing the work; that is, it assumes they’re pretty savvy about what things exist in their world.

Complete table of contents

At OOPSLA in Montreal, I gave an invited talk on Actor-Network Theory (ANT), a style of observation and description that’s most associated with the French philosopher/sociologist Bruno Latour. I told some stories about how I use ANT in my work. I also said some hotheaded things about its relevance for some problems I see with Agile. Because blog posts should be short, I’m going to blog this talk in pieces. Here’s the first.

(This first bit is something of a retread for those who’ve been reading my blog since 2003.)

I’m a consultant. I drop into projects for about a week. I work with the people on the project—pairing, testing, whatever. Along the way, I’m supposed to notice things they don’t see and make suggestions they haven’t already tried, all with the aim of helping them get better at building software.

A tough job: projects are complicated, with lots of moving parts. It’s terribly easy as a consultant to see only the things you’re used to seeing. Worse: it’s easy to see things that aren’t there, just because they’re the things you’re best at seeing.

So a consultant needs mental tricks to kick himself out of ruts and habits. I use ANT as such a trick.

An example: the role of testing in Agile projects

One thing ANT people do is pay attention to things and how they move around.

In the mid-to-late 70’s, Bruno Latour—a philosopher who knew little English and less biochemistry—arrived at the Salk Institute in San Diego, California. Not only did he know little about the content of the work they did there, he deliberately tried to forget what he did know. He wanted to be like an anthropologist visiting some completely foreign tribe with a completely different culture.

As you might expect, some of his observations were odd. For example, he saw that there was one place in the laboratory where, at periodic intervals, bound sheaves of paper called “journals” were delivered.

At other places, people called “technicians” tended expensive and balky machines whose purpose seemed to be to make marks on paper (line drawings, blotchy pictures, lists of numbers, and the like). These two sets of paper were delivered to a third place, the “offices” of the “scientists”. The scientists put the two types of paper—journals and “experimental results”—next to each other and compared them. As (and after) doing so, they would write things on new pieces of paper, which they would deliver to a place inhabited by “typists”, who would “type them up” (put them in a tidier form), then send them out the door to “publishers” who would, in due course, bind them up together with other “papers” and deliver the resulting journals to… still more laboratories.

To Latour, it seemed the laboratory was a factory for turning paper into more paper.

Now, Karl Popper, likely the most influential philosopher of science, would describe all of what Latour saw as an epiphenomenon, not what science is really about. What science is really about is this:

1. A theoretician comes up with a theory. Oddly, the examples always seem to use really great theoreticians, the ones you’ve all heard of.

2. Someone—maybe the great theoretician, maybe someone else—makes predictions from that theory: in situation X, the world should do thing Y.

3. An experimenter—who you quite often won’t have heard of—will create situation X and observe whether the world does thing Y.

4. If the world does not, the great theoretician has to discard the theory and try again.

5. If the world does do Y, that does not confirm the theory. No number of confirmed predictions logically proves that a theory is true. If, however, the theory passes a sufficient number of challenging tests, scientists are justified in accepting it and using it in their own work.

Popper’s opinion matters to me because some software testers make explicit analogies between Popper’s view of science and testing:

1. The programmer is like a theoretician, proposing a theory like “for any input X typed into this text box, the program will calculate f(X).”

2. The tester turns that into a prediction. “So the program should calculate f(X) if the input is one of those things we call a SQL injection attack.”

3. The tester sets up the experiment, tries a SQL injection attack.

4. If the program doesn’t work as predicted, the programmer has to go back and try again. The tester gets a little thrill, because it really is fun to break programs.

5. If the program passes the test, it may still not be correct—no number of passed tests suffices to prove the program is bug-free. But if it passes a sufficient number of challenging tests, managers are justified in releasing it into the world.

The problem is the effect on an Agile team. At the time I was thinking about this (around 2002), there was lots of tension between testers and Agile proponents. Unwise things were said on both sides. Against that backdrop, the testers’ normal drive-by defacements of the programmers’ programs—and the programmers’ egos—wasn’t contributing to the unity of effort I believe is so important on Agile teams. One could say the programmers should be more egoless, but I’m more inclined to work with the grain of human nature than against it.

Popperian science seemed to be the wrong metaphor. (Besides, having read people like Feyerabend and Lakatos, I was pretty skeptical that Popperian science had anything much to do with how real scientists came to accept theories.)

At some point, a detail of Latour’s book describing his Salk experience (Laboratory Life, with Steven Woolgar) came to me. During the process of turning paper into more paper, scientists would hand out “drafts” to other scientists. They’d then get together to discuss the drafts. The conversation would have this tone:

There’s a good chance that Morin is going to be one of the reviewers of this, and you know how she is about antibiotic treatment. If you want this to get past her, you’ll need to strengthen this justification here.

or

I can help you with SAS, make the statistical analysis more solid.

or

If you included the results of assay X, more people would be interested. I can lend you my technician.

The effect is one of people anticipating what dangers the paper will face when it ventures into the world, and making suggestions about how it might be muscled up to survive them. Although I don’t think I realized it at the time, this is the style of paper reviewing that Richard P. Gabriel had imported from the creative writing community into the design patterns community. (See his Writers’ Workshops and the Work of Making Things.)

This, I realized, was a way of having testers’ skills contribute both to the product and also to the team’s feeling of unity of effort. So I began using this new metaphor in my consulting. The particular suggestions I make depend on the team. I might nudge the testers into the role of supporting the (typically overworked) product owner. They could help her talk more more precisely and comprehensively about what she wants. They could then turn that clearer description into tests that programmers could use in the familiar test-first way. Or I might nudge them into the role of teaching the programmers about the domain, one test at a time. (This affects the kinds of tests you write and the order in which you use them.) And so on.

I think this style of thinking about testing is now pretty common in the Agile world. It probably would have happened without me—I’m by no means the only person to think along those lines. That’s not the point: the point is that I probably would not have thought of it had I not absorbed a bit of Latour’s way of looking at things.

I staunchly refused Robert Biddle when he invited me to give a talk at OOPSLA. More than once.

I’m not sure when it’s scheduled, but my OOPSLA talk is titled “Actor-Network Theory: Nothing to Do with TCP/IP or Distributed Objects”

Today we agree that DNA is the template for inherited characteristics. But that agreement didn’t just happen the instant Watson and Crick published. Work still had to be done—lots of work. Actor-Network Theory (ANT) is a social science theory about the work done to reach and maintain agreement, particularly in science and technology. It’s my hope that understanding the techniques of ANT will help OOPSLA attendees understand why those Programs, Languages, and Systems we work on are simultaneously so change-resistant and so fragile.

I spent some spare time hanging out with sociologists a few years back. One result was a paper on Agile in a sociology book (The Mangle in Practice: look for it from your nearest Duke University Press outlet sometime “soon”.) The co-editor is going to do research in data mining and counterterrorism. He writes:

The dream of course would be to locate people who have actually written data mining programs related to counterterrorism. […] If that proves impossible, I would just be interested in interviewing people who have experience designing data mining programs for other applications.

If you are such a person, mail me, and I’ll put you two in touch. He’s a good guy. He spent time riding in police cars to domestic violence calls, sitting in court, talking to perpetrators, etc. Interesting stories.