The difference between a laborer and a professional is that a laborer takes orders from his boss, and a professional provides input to his superiors. Laborers are hired to take direction. Professionals are hired to ensure that the direction chosen makes sense.

Imagine this conversation between a patient and a doctor:

Patient: “My arm hurts.” Doctor: “What would you like me to do about it?” Patient: “Make my arm stop hurting.” Doctor: “Do you want me to cut it off?, I can do that.” Patient: “No, I just want it to stop hurting.” Doctor: “I could cut all the nerves to your arm. That’ll stop it.” Patient: “Isn’t there something less drastic you could do?” Doctor: “Ooops, sorry, time for my break.”

Clearly we don’t expect doctors to behave this way. Even though the patient is the boss, the patient expects the doctor to have the answers and help set the direction.

Here’s another version of the conversation:

Patient: “I want you to cut my arm off.” Doctor: “What’s wrong with your arm?” Patient: “It hurts. I’m tired of it. Just cut it off.” Doctor: “Let me see your arm. Hmmm. Looks like you’ve got a sprain or perhaps a hairline fracture. We should take some X-Rays.” Patient: “No, just cut it off.” Doctor: “Sir, I do not cut off healthy arms.” Patient: “But I’m paying you. You have to do what I say!” Doctor: “No, sir, I don’t. Cutting off your arm would violate my oath.”

Which of these two doctors would you rather be? Now project these two doctors into your own profession, and which would you rather be?

Programmers are professionals. They know more about designing and implementing software systems than their bosses do. Indeed, they are hired for this knowledge and expertise. And they have a solemn duty to prevent their managers from doing things that would be harmful.

All this boils down to one simple thing. Professionals are willing to say “No”. When their managers come to them with direction that makes no sense, a professional programmer will refuse the direction.

Is this risky? Sure. But part of being a professional is the willingness to stand on principle. There are lines that a professional will not cross.

Of course saying “No.” is only one side of the coin. Professionals are also expected to explain their positions, and come up with viable alternatives. Professionals negotiate with their superiors until both parties are satisfied with the chosen direction.

The poor web-designer schmuck in that cartoon was not behaving as a professional. He was behaving as a laborer. The fiasco at the end was his fault. He should have said “No.” and started a negotiation with his customer instead of just doing everything the customer said.

The cartoonist painted the web-designer as a wise but impotent victim, and the boss as the overbearing dufus. The reality is that the web-designer took the role of the victim voluntarily and shirked his responsibility to refuse direction that he considered harmful.

If you are a professional, you never allow yourself to be put in the role of the victim.

Several years ago (Pragmatic) Dave Thomas started a special blog about coding katas. The idea was simple: Professionals practice.

This thought might not have occurred to you before; but it’s self-evidently true. Professional musicians practice. Professional dancers practice. Doctors practice. Soldiers practice. Indeed, any kind of professional craftsman or artisan must practice their adopted trade in order to execute it well when it counts.

Dave’s point was that professional programmers need to practice like any other professional. He set forth a number of simple exercises and problems that programmers could solve during their practice time. He also suggested that practice time needs to be scheduled and protected as part of the normal routine of a software developer.

At XP2005 in Shefield, UK, I attended Laurent Bossavit’s and Emmanuel Gaillot’s Coding Dojo session. I blogged about it at the time. I left that session with a different view of what a Kata might be. In Dave Thomas’ view a kata is an exercise to solve. Each time you solve it you try a different approach. Dave’s notion is that a kata is a way to explore the solution space of a problem. But in Martial arts a kata is something different; it is a set of motions that one memorizes in minute detail. A martial arts kata is a precisely executed dance. I left Sheffield with the idea that a coding kata could be more like a martial arts kata.

About a year ago, Corey Haines (our wandering minstrel of code) stopped by and told me about some mini-conferences that had adopted the notion of coding kata. What he described sounded more like a group dance than a bunch of people independently solving a given problem. This got me thinking. So at the next Software Craftsmanship meeting at 8th Light (Which, not coincidentally, takes it’s name from a martial arts philosophy) I conducted a simple kata session in dojo style.

I, acting as the Sen Sei, had everyone file in to the room as they would to a dojo. I had them put their green bands on their wrists (mine was black!). I bade them to sit, and then gestured for silence. For the next 15 minutes I led them through the Prime Factors Kata in Java without uttering a word (well, almost). I would write a simple test case, then gesture for them to do the same. Then I would make the test pass, and again gesture for them to repeat my moves.

Then, this Fall, I attended Programming with the Stars at Agile 2009. As I watched the contestants perform their programming sessions, I realized that they were not simply demonstrating programming prowess; indeed they were competing in how well they performed their session. That’s when it struck me. This was a performance art!

It seems absurd to think of programming as a performance art. And yet watching those people up on stage working through routines that they had clearly practiced over and over again, was delightfully entertaining to me, and to the crowd. There were cheers and applause when a performing pair did something especially well. There was laughter when a pair executed a clever joke in code, or in behavior. For programmers, watching other programmers perform well practiced routines was fun!

Now I had seen martial arts katas executed as performance art during competitions. Indeed, it is a beautiful thing to watch a skilled and well practiced martial artist peform a kata. And that started me thinking. Why would a martial artist practice these forms so intensely that they could be performed as an art?

The goal of martial arts is not to perform on stage. The goal of martial arts is self defense! And yet, when a martial artist is at the peak of his skill, his practice takes on the quality of a performance art. When you watch a skilled martial artist perform, you know you don’t want to fight him. The performance is a demonstration, and a realization, of mastery.

And yet the performance is not the goal. No martial artist practices his art so that they can perform on stage. A martial artist practices to achieve personal perfection in the art of self defense. The fact that the practice can be performed is a (pleasant) side effect.

Could it be that these coding kata that we’ve been dabbling with for the last few years could be performed? Is there a benefit to practicing them so much that performance is an option? Is there really any reason for a programmer to create and then memorize a routine down to the level of individual keystrokes? Is there profit to be gained from practicing that routine so thoroughly that you can do it at high speed with virtually no errors? This August I decided to find out.

I started with the Prime Factors Kata in Java, and set it to music inspired by this video of dancing kites. The piece is about 4 minutes long, and I figured I’d need about twice that, so I found two different version of the music and played them back to back. But working in Java is ponderous, and I could not complete the kata before the two pieces had finished. So I switched to Ruby. Using Ruby and Rspec I was able to finish the Kata with plenty of time to spare.

Thereupon began an evolution. Since I had time, I added more features to the kata. As I improved in my practice I found I had even more time, so I added even more features. I refined and polished. I refactored my refactorings. I trimmed keystrokes, and learned many new keyboard shortcuts in the process. I completely abandoned the mouse; and then later reacquired it for flourishes and highlights (but never for actual coding).

Week after week, I set aside 30 minutes or so every day to practice, and practice, and practice—just the way I used to practice my Jiu Jitsu Katas. I would practice on airplanes while flying to clients. I would practice in bed with my laptop in my lap. I would practice late at night in hotel rooms after a long day consulting for clients. I would practice early in the morning before shower and breakfast. And the practice started to pay off.

Ten weeks later I finally decided I was ready to create a screencast. I reduced my screen resolution to 1024X768. I configured SnapZ ProX to record the whole screen at 80% size. And I began to record.

Performing a coding kata in time to music is a very difficult thing to do. Maintaining the timeline is critical. There are very few errors that you can effectively recover from. If you miss a stroke, the whole sequence melts down. And melt down it did. Over and over and over again. I spent weeks trying to record a reasonably good session. I must have done hundreds of takes. It was very frustrating.

But day by day I got better and better at it. Finally, after weeks of trying, I got what I consider to be a recording that, though not perfect, is good enough to present. You can watch that recording here.

Has this paid off in the regular programming I do? I think it has. My mouse usage is much less than it used to be. I know a much larger number of keyboard shortcuts than I used to, and I can use them almost instinctively. My typing and accuracy have improved quite a bit, and I now type more punctuation and number keys without looking. So, yes, I think the effort has paid off; though I’m not at all sure the payoff compensates for the effort.

But something else compensates for the effort. Making this recording was fun—it was a lot of fun. And that’s probably the real answer to the question posed in the title of this blog.

In 1995-99 I was frequently asked to speak to managers about what a transition to OO (usually from C to C++) would do for (or to) them. I would spend a half day to a day going over the issues, costs, and benefits.

One part of that talk (usually about 90 min) was a discussion about software process. It was the process part of the talk that those acetate slides that I found described.

1995 was during the ascendency of Waterfall. Waterfall thinking was king. RUP had not yet been conceived as an acronym. And though Booch was beating the drum for incrementalism, most people (even many within Rational) were thinking in terms of six to eighteen month waterfalls.

So, here are the slides that I uncovered deep within an old filing cabinet. I scanned them in. They were produced on a Macintosh using the old “More” program. (Where is that program now? It was so good.)

Go ahead and read them now. Then come back here and continue…

---

What struck me about those slides was the consistency of the message with today. It was all about iterative development. Small iterations (though I never deigned to define the length in the slides, I frequently told people 2 weeks), measured results, etc. etc. Any Agile evangelist could use those slides today. He or she would have to dance quickly around a few statements, but overall the message has not shifted very much.

What’s even more interesting is the coupling between the process, and OO. The slides talk a lot about dependency management and dependency structure. There are hints of the SOLID principles contained in those slides. (Indeed several of the principles had already been identified by that time.) This coupling between process and software structure was a harbinger of the current craftsmanship/clean-code movement.

Of course the one glaring omission from these slides is TDD. That makes me think that TDD was the true catalyst of change, and the bridge that conveyed our industry from then to now.

Anyway, I guess the more things change, the more they stay the same.

Comments please!

Inadvertent-Imprudent Debt.

There is more of this debt than any other kind. It is all too common that software developers create a mess and don’t know they are doing it. They have not developed a nose that identifies code smells. They don’t know design principles, or design patterns. They think that the reek of rotten code is normal, and don’t even identify it as smelling bad. They think that their slow pace through the thick morass of tangled code is the norm, and have no idea they could move faster. These people destroy projects and bring whole companies to their knees. Their name is Doom.

Deliberate-Imprudent Debt.

There is a meme in our industry (call it the DI meme) that tells young software developers that rushing to the finish line at all costs is the right thing to do. This is far worse than the ignorance of the first group because these folks willfully create debt without counting the cost. Worse, this meme is contagious. People who are infected with it tend to infect others, causing an epidemic of deliberately imprudent debtors (sound familiar?) The end result, as we are now all know, is economic catastrophe, inflation (of estimates) and crushing interest (maintenance) payments. They have become death, the destroyer of worlds.

Inadvertent-Prudent Debt.

This is something of an oxymoron. Ironically, it is also the best of all possible states. The fact is that no matter how careful we are, there is always a better solution that we will stumble upon later. How many times have you finished a system only to realize that if you wrote it again, you’d do it very differently, and much better?

The result is that we are always creating a debt, because our hindsight will always show us a better option after it is too late. So even the best outcome still leaves us owing. (Mother Earth will eventually collect that debt!)

Deliberate-Prudent Debt.

This is the quadrant that I have the biggest problem with. And it is this quadrant in which Martin uses the caption I don’t like. The Caption is: “We must ship now and deal with consequences.”

Does this happen? Yes. Should it happen? Rarely, yes. But it damned well better not happen very often, and it damned well better not happen out of some misplaced urge to get done without counting the cost.

The problem I have with this quadrant (DP) is that people who are really in quadrant DI think they are in DP, and use words such as those that appear in the caption as an excuse to rack up a huge imprudent debt.

The real issue is the definition of the word: Imprudent.

So let me ask you a question. How prudent is debt? There is a very simple formula for determining whether debt is prudent or imprudent. You can use this formula in real life, in business, and in programming. The formula is: Does the debt increase your net worth, and can you make the payments?

People often focus on the first criterion, without properly considering the second. Buying a house is almost certain to increase your net worth despite the debt (though lately…). On the other hand, if you cannot make the payments, you won’t keep that house for long. The reason for our current economic woes has a lot to do with people trying to increase their net worth despite the fact that they couldn’t afford the payments. (indeed, they were encouraged by a meme very similar to the DI meme!)

Bad code is always imprudent.

Writing bad code never increases your net worth; and the interest rate is really high. People who write bad code are like those twenty-somethings who max out all their credit cards. Every transaction decreases net worth, and has horrendous consequences for cash flow. In the end, the vast bulk of your effort goes to paying the interest (the inevitable slow down of the team as they push the messes around). Paying down the principle becomes infeasible. (Just the way credit card companies like it.)

Some Suboptimal Design Decision are Prudent Debt.

But most are not. Every once in awhile there is a suboptimal design decision that will increase the net worth of the project by getting that project into customer’s hand’s early.

This is not the same as delivering software that is under-featured. It is often prudent to increase the net worth of a project by giving customers early access to a system without a full and rich feature set. This is not debt. This is more like a savings account that earns interest.

Indeed, this is one reason that most technical debt is imprudent. If you are truly concerned about getting to market early, it is almost always better to do it with fewer features, than with suboptimal design. Missing features are a promise that can be kept. Paying back suboptimal designs creates interest payments that often submerge any attempts at payback and can slow the team to the breaking point.

But there are some cases where a sub-optimal design can increase your net worth by allowing you to deliver early. However, the interest rate needs to be very low, and the principle payments need to be affordable, and big enough to pay back the debt in short order.

What does a low interest rate mean? It means that the sub-optimal design does not infiltrate every part of your system. It means that you can put the sub-optimal design off in a corner where it doesn’t impact your daily development life.

For example, I recently implemented a feature in FitNesse using HTML Frames. This is sub-optimal. On the other hand, the feature is constrained to one small part of the system, and it simply doesn’t impact any other part of the system. It does not impede my progress. There is no mess for me to move around. The interest rate is almost zero! (nice deal if you can get it!)

Implementing that feature with ajax is a much larger project. I would have had to invest a great deal of time and effort, and would have had to restructure massive amounts of the internal code. So the choice was a good one.

Better yet, the customer experience has pretty much been a big yawn. I thought people would really like the feature and would drive me to expand upon it. Instead, the customer base has virtually ignored it.

So my solution will be to pay back this debt by eliminating the feature. It was a cheap experiment, that resulted in my not having to spend a lot of time and effort on a new architecture! Net worth indeed!

But it might have gone the other way. My customers may have said: “Wow, Great! We want more!” At that point it would have been terrible to expand on the HTML Frames! That decision would have been in the DI quadrant. Deliberate imprudence! Rather, my strategy would have been to replace the suboptimal Frames design of the feature with an isolated ajax implementation, and then to gradually migrate the ajax solution throughout the project. That would have been annoying, but loan payments always are.

Summary

So, don’t let the caption in the DP quadrant be an excuse. Don’t fall for the DI meme that says “We just gotta bite the bullet”. Tread very carefully when you enter the DP quadrant. Look around at all your options, because it’s easy to think you are in the DP quadrant when you are really in the DI quadrant.

Remember: Murphy shall send you strong delusion, that you should believe you are in DP; so that you will be damned in DI.

Is there any research on TDD?

It turns out that there is a fair bit.

• One simple google search led me to this blog by Phil Haack in which he reviewed a TDD research paper. Quoting from the paper:

We found that test-first students on average wrote more tests and, in turn, students who wrote more tests tended to be more productive. We also observed that the minimum quality increased linearly with the number of programmer tests, independent of the development strategy employed.

• The same google search led me to this blog by Matt Hawley, in which he reviewed several other research papers. Part of his summary:

* 87.5% of developers reported better requirements understanding. * 95.8% of developers reported reduced debugging efforts. * 78% of developers reported TDD improved overall productivity. * 50% of developers found that it decreased overall development time. * 92% of developers felt that TDD yielded high-quality code. * 79% of developers believed TDD promoted simpler design.

Actually, I recognize some of Matt’s results as coming from a rather famous 2003 study (also in the list of google results) by Laurie Wiliams and Boby George. This study describes a controlled experiment that they conducted in three different companies. Though Matt’s summary above is based (in part) on that study, there is more to say.

In the George-William study teams that practiced TDD took 16% longer to claim that they were done than the teams that did not practice TDD. Apparently tests are more accurate than claims since the non-TDD teams failed to pass one third of the researcher’s hidden acceptance tests, whereas the TDD teams passed about 6 out of 7. To paraphrase Kent Beck: “If it doesn’t have to work, I can get it done a lot faster!”

Another point of interest in this study is that the TDD teams produced a suite of automated tests with very high test coverage (close to 100% in most cases) whereas most of the non-TDD teams did not produce such a suite; even though they had been instructed to.

• Jim Shore wrote a review of yet another research summary which I found in the same google search. This one combines 7 different studies (including George-Williams). Here the results range from dramatically improved quality and productivity to no observed effect.

• Finally, there is this 2008 case Study of TDD at IBM and Microsoft which shows that TDDers enjoy a defect density reduction ranging from 30% to 90% (as measured by defect tracking tools) and a productivity cost of between 15% and 35% (the subjective opinion of the managers). I refer you back to Kent Beck’s comment above.

I’m sure there is more research out there. After all this was just one google search. I think it’s odd that the TDD detractors didn’t find anything when they did their google searches.

• Oh yeah, and then there was that whole issue of IEEE Software that was dedicated to papers and research on TDD.

What projects have been written with TDD, hmmm?

Quite a few, actually. The following is a list of projects that have an automated suite of unit tests with very high coverage. Those that I know for a fact use TDD, I have noted as such. The others, I can only surmise. If you know of any others, please post a comment here.

• JUnit. This one is kind of obvious. JUnit was written by Kent Beck and Erich Gamma using TDD throughout. If you measure software success by sheer distribution, this particular program is wildly successful.

• Fit. Written by Ward Cunningham. The progenitor of most current acceptance testing frameworks.

• FitNesse. This testing framework has tens of thousands of users. It is 70,000 lines of java code, with 90%+ code coverage. TDD throughout. Very small bug-list. Again, if you measure by distribution, another raving success.

• Cucumber,
• Rspec. These two are Testing frameworks in Ruby. Of course you’d expect a testing framework to be written with TDD, wouldn’t you? I know these were. TDD throughout.

• Limelight. A gui framework in JRUby. TDD throughout.
• jfreechart.
• Spring
• JRuby
• Smallsql
• Ant
• MarsProject
• Log4J
• Jmock

Are there others? I’m sure there are. This was just a quick web search. Again, if you know of more, please add a comment.

TDD

Anyone who continues to think that TDD slows you down is living in the stone age. Sorry, that’s just the truth. TDD does not slow you down, it speeds you up.

Look, TDD is not my religion, it is one of my disciplines. It’s like dual entry bookkeeping for accountants, or sterile procedure for surgeons. Professionals adopt such disciplines because they understand the theory behind them, and have directly experienced the benefits of using them.

I have experienced the tremendous benefit that TDD has had in my work, and I have observed it in others. I have seen and experienced the way that TDD helps programmers conceive their designs. I have seen and experienced the way it documents their decisions. I have seen and experienced the decouplings imposed by the tests, and I have seen and experienced the fearlessness with which TDDers can change and clean their code.

To be fair, I don’t think TDD is always appropriate. There are situations when I break the discipline and write code before tests. I’ll write about these situations in another blog. However, these situations are few and far between. In general, for me and many others, TDD is a way to go fast, well, and sure.

The upshot of all this is simple. TDD is a professional discipline. TDD works. TDD makes you faster. TDD is not going away. And anyone who has not really tried it, and yet claims that it would slow them down, is simply being willfully ignorant. I don’t care if your name is Don Knuth, Jamie Zawinski, Peter Seibel, or Peter Pan. Give it a real try, and then you have the right to comment.

Let me put this another way. And now I’m talking directly to those who make the claim that TDD would slow them down. Are you really such a good programmer that you don’t need to thoroughly check your work? Can you conceive of a better way to check your work than to express your intent in terms of an executable test? And can you think of a better way to ensure that you can write that test other than to write it first?

If you can, then I want to hear all about it. but I don’t want to hear that you write a few unit tests after the fact. I don’t want to hear that you manually check your code. I don’t want to hear that you do design and therefore don’t need to write tests. Those are all stone-age concepts. I know. I’ve been there.

So there. <grin>

The Design Pattern Religion

Tim Bray said:

My experience suggests that there are few surer ways to doom a big software project than via the Design Patterns religion.

He’s right of course. The Design Patterns religion is a foul bird that ravages teams and cuts down young projects in their prime. But let’s be clear about what that religion is. The Design Patterns religion is the ardent belief that the use of design patterns is good.

Here’s a clue. Design Patterns aren’t good. They also aren’t bad. They just are. Given a particular software design situation, there may be a pattern that fits and is beneficial. There may also be patterns that would be detrimental. It’s quite possible that none of the currently documented patterns are appropriate and that you should close the book and just solve the problem.

Here’s another clue. You don’t use patterns. You don’t apply patterns. Patterns just are. If a particular pattern is appropriate to solve a given problem, then it will be obvious. Indeed it is often so obvious that you don’t realize that the pattern is in place until you are done. You look back at your code and realize: “Oh, that’s a Decorator!”.

So am I saying that Design Patterns are useless?

NO! I want you to read the patterns books. I want you to know those patterns inside and out. If I point at you and say “Visitor” I want you at the board drawing all the different variants of the pattern without hesitation. I want you to get all the names and roles right. I want you to know patterns.

But I don’t want you to use patterns. I don’t want you to believe in patterns. I don’t want you to make patterns into a religion. Rather I want you to be able to recognize them when they appear, and to regularize them in your code so that others can recognize them too.

Design Patterns have a huge benefit. They have names. If you are reading code, and you see the word “Composite”, and if the author took care to regularize the code to the accepted names and roles of the “Composite” pattern, then you will know what that part of the code is doing instantly. And that is powerful!

Minimizing Concurrency.

In my first Duct Tape blog I made the statement:

I found myself annoyed at Joel’s notion that most programmers aren’t smart enough to use templates, design patterns, multi-threading, COM, etc. I don’t think that’s the case. I think that any programmer that’s not smart enough to use tools like that is probably not smart enough to be a programmer period.

Tim responds with:

...multi-threading is part of the problem, not part of the solution; that essentially no application programmer understands threads well enough to avoid deadlocks and races and horrible non-repeatable bugs. And that COM was one of the most colossal piles of crap my profession ever foisted on itself.

Is concurrency really part of the problem? Yes! Concurrency is a really big part of the problem. Indeed, the first rule of concurrency is: DON’T. The second rule is: REALLY, DON’T.

The problem is that some times you have no choice. And in those situations, where you absolutely must use concurrency, you should know it inside and out!

I completely and utterly reject the notion that ignorance is the best defense. I reject that lack of skill can ever be an advantage. So I want you to know concurrency. I want to shout “Dining Philosophers” and have you run to the board without hesitation and show me all the different solutions. If I holler “Deadlock”, I want you to quickly identify the causes and solutions.

Here’s a clue. If you want to avoid using something, know that something cold.

Sudoku

At the end of his blog, Peter jumps on the pile of bodies already crushing Ron Jeffries regarding the Sudoku problem from July of 2006.

I find the pile-up disturbing. Ron had the courage to fail in public. Indeed he announced up front that he might “crash and burn”. And yet he got lambasted for it by people who hid behind someone else’s work. The responses to Ron’s tutorial blogs were completely unfair because the authors of those blogs had everything worked out for them by Dr. Peter Norvig before they published their screeds. They were comparing apples to oranges because their responses were about the solution whereas Ron’s blogs were about the process.

Which one of us has not gone down a rat-hole when hunting for a solution to a complex problem? Let that person write the first blog. Everyone else ought to be a bit more humble.

Do the people on the pile think that Ron is unable to solve the Sudoku problem? (Some have said as much.) Then they don’t know Ron very well. Ron could code them all under the table with one hand tied behind his back.

Personal issues aside, I find the discussion fascinating in it’s own right. Ron had attempted to solve the Sudoku problem by gaining insight into that problem through the process of coding intermediate solutions. This is a common enough TDD approach. Indeed, the Bowling Game and the Prime Factors Kata are both examples where this approach can work reasonably well.

This approach follows the advice of no less than Grady Booch who (quoting Heinlein) said: “when faced with a problem you do not understand, do any part of it you do understand, then look at it again.“

Ron was attempting to use TDD to probe into the problem to see if he could gain any insight. This technique often bears fruit. Sometimes it does not.

Here is a classic example. Imagine you were going to write a sort algorithm test first:

• Test 1: Sort an empty array. Solution: Return the input array.

• Test 2: Sort an array with one element. Solution: Return the input array.

• Test 3: Sort an array with two elements. Solution: Compare the two elements and swap if out of order. Return the result.

• Test 4: Sort an array with three elements. Solution: Compare the first two and swap if out of order. Compare the second two and swap if out of order. Compare the first two again and swap if out of order. Return the result.

• Test 5: Sort an array with four elements. Solution: Put the compare and swap operations into a nested loop. Return the result.

The end result is a bubble sort. The algorithm virtually self assembles. If you had never heard of a bubble sort before, this simple set of tests would have driven you to implement it naturally.

Problems like Bowling, Prime Factors, and Bubble Sort hold out the interesting promise that TDD may be a way to derive algorithmms from first principles!

On the other hand, what set of tests would drive you to implement a QuickSort? There are none that I know of. QuickSort and Sudoku may require a serious amount of introspection and concentrated thought before the solution is apparent. They may belong to a class of algorithms that do not self-assemble like Bowling, Prime Factors, and Bubble Sort.

This blog by Kurt Christensen provides all the links to the various Sudoku articles, and sums it up this way.

TDD may not be the best tool for inventing new algorithms, it may very well be the best tool for applying those algorithms to the problem at hand.

Actually I think TDD is a good way to find out if an algorithm will self-assemble or not. It usually doesn’t take a lot of time to figure out which it’s going to be.

After all, one man’s “one thing” might be someone else’s “two things”.

Consider this class:

  class SymbolReplacer {
    protected String stringToReplace;
    protected List<String> alreadyReplaced = new ArrayList<String>();

    SymbolReplacer(String s) {
      this.stringToReplace = s;
    }

    String replace() {
      Pattern symbolPattern = Pattern.compile("\\$([a-zA-Z]\\w*)");
      Matcher symbolMatcher = symbolPattern.matcher(stringToReplace);
      while (symbolMatcher.find()) {
        String symbolName = symbolMatcher.group(1);
        if (getSymbol(symbolName) != null && !alreadyReplaced.contains(symbolName)) {
          alreadyReplaced.add(symbolName);
          stringToReplace = stringToReplace.replace("$" + symbolName, translate(symbolName));
        }
      }
      return stringToReplace;
    }

    protected String translate(String symbolName) {
      return getSymbol(symbolName);
    }
  }

It’s not too hard to understand. The replace() function searches through a string looking for $NAME and replaces each instance with the appropriate translation of NAME. It also makes sure that it doesn’t replace a name more than once. Simple.

Of course the words “It also…” pretty much proves that this function does more than one thing. So we can probably split the function up into two functions as follows:

    String replace() {
      Pattern symbolPattern = Pattern.compile("\\$([a-zA-Z]\\w*)");
      Matcher symbolMatcher = symbolPattern.matcher(stringToReplace);
      while (symbolMatcher.find()) {
        String symbolName = symbolMatcher.group(1);
        replaceAllInstances(symbolName);
      }
      return stringToReplace;
    }

    private void replaceAllInstances(String symbolName) {
      if (getSymbol(symbolName) != null && !alreadyReplaced.contains(symbolName)) {
        alreadyReplaced.add(symbolName);
        stringToReplace = stringToReplace.replace("$" + symbolName, translate(symbolName));
      }
    }

OK, so now the replace() function simply finds all the symbols that need replacing, and the replaceAllInstances() function replaces them if they haven’t already been replaced. So do these function do one thing each?

Well, the replace() compiles the pattern and build the Matcher() Maybe those actions should be moved into the constructor?

  class SymbolReplacer {
    protected String stringToReplace;
    protected List<String> alreadyReplaced = new ArrayList<String>();
    private Matcher symbolMatcher;
    private final Pattern symbolPattern = Pattern.compile("\\$([a-zA-Z]\\w*)");

    SymbolReplacer(String s) {
      this.stringToReplace = s;
      symbolMatcher = symbolPattern.matcher(s);
    }

    String replace() {
      while (symbolMatcher.find()) {
        String symbolName = symbolMatcher.group(1);
        replaceAllInstances(symbolName);
      }
      return stringToReplace;
    }

    private void replaceAllInstances(String symbolName) {
      if (getSymbol(symbolName) != null && !alreadyReplaced.contains(symbolName)) {
        alreadyReplaced.add(symbolName);
        stringToReplace = stringToReplace.replace("$" + symbolName, translate(symbolName));
      }
    }

    protected String translate(String symbolName) {
      return getSymbol(symbolName);
    }
  }

OK, so now certainly the replace() function is doing one thing? Ah, but I see at least two. It loops, extracts the symbolName and then does the replace. OK, so how about this?

    String replace() {
      for (String symbolName = nextSymbol(); symbolName != null; symbolName = nextSymbol())
        replaceAllInstances(symbolName);

      return stringToReplace;
    }

    private String nextSymbol() {
      return symbolMatcher.find() ? symbolMatcher.group(1) : null;
    }

I had to restructure things a little bit. The loop is a bit ugly. I wish I could have said for (String symbolName : symbolMatcher) but I guess Matchers don’t work that way.

I kind of like the nextSymbol() function. It gets the Matcher nicely out of the way.

So now the replace() and nextSymbol() functions are certainly doing one thing. Aren’t they?

Well, I suppose I could separate the loop from the return in replace().

    String replace() {
      replaceAllSymbols();
      return stringToReplace;
    }

    private void replaceAllSymbols() {
      for (String symbolName = nextSymbol(); symbolName != null; symbolName = nextSymbol())
        replaceAllInstances(symbolName);
    }

I don’t see how I could make these functions smaller. They must be doing one thing. There’s no way to extract any other functions from them!

Uh… Wait. Is that the definition of one thing? Is a function doing one thing if, and only if, you simply cannot extract any other functions from it? What else could “one thing” mean? After all, If I can extract one function out of another, the original function must have been doing more than one thing.

So does that mean that for all these years the authors and consultants (like me) have been telling us to extract until you can’t extract anymore?

Let’s try that with the rest of this class and see what it looks like…

  class SymbolReplacer {
    protected String stringToReplace;
    protected List<String> alreadyReplaced = new ArrayList<String>();
    private Matcher symbolMatcher;
    private final Pattern symbolPattern = Pattern.compile("\\$([a-zA-Z]\\w*)");

    SymbolReplacer(String s) {
      this.stringToReplace = s;
      symbolMatcher = symbolPattern.matcher(s);
    }

    String replace() {
      replaceAllSymbols();
      return stringToReplace;
    }

    private void replaceAllSymbols() {
      for (String symbolName = nextSymbol(); symbolName != null; symbolName = nextSymbol())
        replaceAllInstances(symbolName);
    }

    private String nextSymbol() {
      return symbolMatcher.find() ? symbolMatcher.group(1) : null;
    }

    private void replaceAllInstances(String symbolName) {
      if (shouldReplaceSymbol(symbolName))
        replaceSymbol(symbolName);
    }

    private boolean shouldReplaceSymbol(String symbolName) {
      return getSymbol(symbolName) != null && !alreadyReplaced.contains(symbolName);
    }

    private void replaceSymbol(String symbolName) {
      alreadyReplaced.add(symbolName);
      stringToReplace = stringToReplace.replace(
        symbolExpression(symbolName), 
        translate(symbolName));
    }

    private String symbolExpression(String symbolName) {
      return "$" + symbolName;
    }

    protected String translate(String symbolName) {
      return getSymbol(symbolName);
    }
  }

Well, I think it’s pretty clear that each of these functions is doing one thing. I’m not sure how I’d extract anything further from any of them.

Perhaps you think this is taking things too far. I used to think so too. But after programming for over 40+ years, I’m beginning to come to the conclusion that this level of extraction is not taking things too far at all. In fact, to me, it looks just about right.

So, my advice: Extract till you just can’t extract any more. Extract till you drop.

After all, with modern tools it takes very little time. It makes each function almost trivial. The code reads very nicely. It forces you to put little snippets of code into nicely named functions. And, well gosh, extracting till you drop is kind of fun!

The bad news is that you’ve made a mess of things along the way.

This is inevitable. It takes a great deal of focus and endurance to get a system working just right. While you are consumed by that focus, you have little room for niceties like small functions, nice names, decoupling, and cleanliness.

My apprentice and I just finished achieving a major milestone in FitNesse. It used to be that each new release of FitNesse was contained in a zip file that had all the files and directories laid out just perfectly. This is great for a brand new installation, but doesn’t work so well when you are upgrading. What we managed to get working last night was the ability for FitNesse to self-install from it’s jar file. Now, whether you are installing for the first time, or just upgrading, FitNesse will install itself into your environment appropriately.

If you’ve ever written a self-install like this, you know there are lots of niggling little details to attend to. While the problem is conceptually simple, the realization is a maze of complexity.

Last night, with dinner waiting on the table and getting cold, we got the last little problem licked, and saw the whole self-installation work as we wanted. We congratulated each other with a high-five, and then went upstairs to eat a well-deserved meal. Later that evening I went down to the office and checked in the code.

This morning I woke up, and while in the shower, I realized that we had a lot of work left to do. We need to go back over all that code and clean it up. I’m sure we left a swath of detritus while on the hunt.

The rush of victory should never be confused with the cold and crystalline concept of done. Once you get your systems to work, you still have to go back and clean up the wreckage left behind by the victorious battle. You are not done until the victorious code has been cleaned, polished, and oiled.