An Introduction to Services From This Coder's Perspective

First, there is the question of “what is a Service?”  

W3C defines a web service as:
a software system designed to support interoperable machine-to-machine interaction over a network.”[1]

They go on to specify some specific technologies mandated by this particular standard and the role a service plays:
“The purpose of a Web service is to provide some functionality on behalf of its owner -- a person or organization."
This definition describes the infrastructure, focusing on how we deploy services and what purpose they serve right now to MBAs.  It is as though they are defining a program as "a sequence of machine instructions that perform mathematical or logical operations on behalf of a computer operator”.  I want a definition that tells me how to address the technical questions that emerge and provides guidance on how we will be writing and employing services going forward.  My current personal definition is:
A Service is an Object bound at run-time by a networking protocol.

Note that I mean “object” here under Alan Kay’s definition [2] and not in the particular sense that the word is used any specific language like Java or C++.  Despite varying dynamics, all service frameworks encapsulate some combination of data and behavior (not necessarily *well*, of course, but when they fail it is usually clear from the pain that follows.)  They hide implementation details while fulfilling either implicit or explicit contracts in response to messages sent by other services.[3]

The interesting change from current Object-Oriented programming paradigms is that they also encapsulate the location they are executing and the provider of the object.  Because we bind to the specific implementation at runtime using a networking protocol of some kind, the object can be running on any machine, virtual or physical, anywhere reachable by that protocol.  I don’t think this fundamentally changes the paradigm any more than dynamically linked libraries did, but it is really, really cool.

Swapping from Google Reader to Tiny Tiny RSS

Now that Google has broken integrated Google Reader with Google+, I was looking for a replacement that would let me use my daily reading of feeds the way I always had: as a way to share long-form content with other folks who specifically wanted to read the long-form content I shared this way (opt-in broadcast). Google+ defeats the purpose: I like my RSS feed and my friends' shared items specifically because of the high signal-to-noise ratio and the lack of dilution with other content.

My search led me to Tiny Tiny RSS. It offers a similar feature to Google's shared items, except instead of a specific social area it “publishes” items to your own RSS feed. It does not replace the comment or discussion capabilities of Google Reader, but it has the advantage of being something I can host myself and open source; if I ever have some free time I can address any flaws that continue to bother me.

A Preface to My Future Work on the Economics of Open Source

“Economics is basically about incentives and interaction — or, as Schelling put it, micromotives and macrobehavior. You try to think about what people will do in certain circumstances, and you try to understand how individual behavior adds up to an overall result.” – Paul Krugman

The economics of open source software has generally been approached from the perspective of “why would people do this thing?”  This makes some sense; classical economic models leave non-monetary considerations to the realm of game theory and sociology and the question of micromotives initially looks exceptionally opaque.  The result, however, has been a skeptical approach to applying an economic lens to open source and a general failure to explain the macrobehavior involved.  Most papers I’ve found attempt to explain away open source as human irrationality, rather than demonstrate the way it fits with, and indeed validates, our existing models.  I'm one of those people who think that if reality clashes with a model, the problem is probably not reality.


CMake Tips & Tricks: Drop Down List

In a recent CMake project I was setting up, I wanted users to be able to choose one of several possible libraries at project generation, to make performance comparisons easy on multiple platforms.  This is easy enough to do with a configuration parameter, but since the libraries available were a limited set offering the available options seemed better.  I discovered that in the CMake GUI it is possible to have a drop down menu of options for a given property, and it’s actually quite easy.  The only thing to keep in mind is that this approach doesn’t enforce anything; the user could still enter other options.  Since this is only used by developers to generate projects, I didn’t particularly care.  They break it, they bought it, as it were.

First, we use a cache variable and enumerate the options for our drop-down list:

SET(LIBRARY_TO_USE "Option1" CACHE STRING "library selected at CMake configure time")


After that it’s just a matter of changing the things that should change when this option changes.  There are a couple possible approaches here, though none of them completely satisfy my aesthetic sense.

1.       The first is simply to call everything on every invocation, but that defeats the purpose of the caching in the first place. 

2.      I can make sure this .cmake file is included at the top of the project CMakeLists.txt, so it is called before anything else that might include this library.  In that case I can check the LIBRARY_FOUND variable, which is set the first time any of these libraries are loaded during a build.  The upside of this is that if multiple files include this .cmake file it will only reload everything once per project generation.  The downside is that it relies on not having someone load the library before this file is included, and that was a deal breaker; I don’t want to rely on implicit assumptions.  Also, it still reloads the cache once per build. On the up side, if I want to vary non-cache values this allows me to group all the change logic in one place.

3.       The final option is explicitly checking to see if the variable has changed by caching the last value inside of the has-changed if statement. This requires using a second cached variable to hold state and initializing it if it is undefined. Additionally, this variable should never be changed by a user, so I use MARK_AS_ADVANCED to hide it from the GUI.

I used option three, which looks like:


     SET(LIBRARY_LAST "NotAnOption" CACHE STRING "last library loaded")





     SET(LIBRARY_LAST ${LIBRARY_TO_USE} CACHE STRING "Updating Library Project Configuration Option" FORCE)


The important part of this is “UNSET”.  Any cached variables that are set in the Find.cmake file will need to be explicitly cleared in order for them to be actually updated.  The rest of it is simply determining whether or not the parameter changed.

Finally, we need to change parameters on the basis of what option is selected.  If only cache variables change, we can include this in the “if changed” loop, but I was using non-cached variables accessed by the Find.cmake files, so I set these each time.  It would be cleaner to separate these into their own CMake files with a regular naming scheme, but since I was only setting one parameter I didn’t bother.  This looked like:








Etc.  The path naming conventions were not actually that regular either, or wouldn’t have needed the switch statement.

All of these went into a SetLibraryOptions.cmake file, and I added INCLUDE(SetLibraryOptions.cmake) to the root level CMakeLists.txt file.  When I included this library in a future target, I used the regular package syntax with ${LIBRARY_TO_USE} as the package name.  This is why it was so useful to have a drop down menu here: each package name must exactly match the format of the Find.cmake file.  T

Now, when I use the library in another package the include will look something like:




           MESSAGE(FATAL_ERROR “failed to find “ ${LIBRARY_TO_USE})



And that’s it; when the user selects a different library all of the projects will be regenerated with the new option.  The final result looks like:


@dharmesh Polls Twitter: What Do We Call People Who Code?

For those of you that write code, what term do you prefer? Programmer? Engineer? Developer? Something else?

Dharmesh Shah asked this question Twitter yesterday, and I did a quick compilation of the public responses.  For the answers with more than one vote I include the total votes and also a score. About a third of responces used some form of, “I like X, but sometimes I use Y”, and instead of throwing that information away I awarded 3 points for a first choice, 2 for a second choice and 1 point for a third choice.

  • Developer – 17 votes/score 52
  • Engineer –11 votes/score 29
  • Programmer – 4 votes/score 11
  • Hacker – 4 votes/score 11
  • Coder – 3 votes/score 8

The answers that appeared only once were:

  • Byte Surgeon
  • Architect
  • Tinkerer
  • Code Monkey
  • Codewright
  • Professional Geek
  • Someone who types on a keyboard all day in air conditioning
  • Chief Ideas Officer


It definitely looks like “Developer” is the standard, but what immediately jumped out at me was the way some people embrace the same aspects of the job others try to avoid. Some people reported that “Programmer” sounded too much like someone who just wrote code and didn’t think about it, whereas someone else described their job as “Code Monkey”, which revels in that role. Some of the creative responses, like “Chief Ideas Officer” didn’t imply any contact with code at all, where as others, like “Byte Surgeon”, implied a visceral, low-level involvement.

It seems like sone of the trade off is between “code” and “prestige”, which is always disappointing for me to discover.  Several people suggested they would use different words if talking to a fellow coder rather than someone outside the profession, usually preferring "Engineer" when talking to people who don't write code themselves. This is perhaps why “Developer” wins out in the end: it seems to suggest a job that involves typing things that get executed, one way or another, without also suggesting that someone handed you pseudocode to implement. Which may be to say, it is uniformly bland and uninformative, conveying as little information about the tasks performed and the role plays as humanly possible.

 It is clear that there are multiple jobs that would fall in this category, though, even if we don’t yet have the language to articulate the differences.  Certainly independence vs. subordination is a common theme, but I also noticed there were no terms proposed that specifically called out “team member” or “collaborator”. I would personally prefer such a term to either the independence of “Hacker” or the subordination of “Code Monkey”.  Unfortunately, any such word runs the risk of stepping too far from the technical roots,and implying that the code writer is no longer elbow-deep in bloody code.  

Programming is...: Why Metaphors Interest Me

Metaphor has a pernicious effect. It encourages people to take anecdotes as proof, effective rhetoric as useful advice and to accept only ideas which fit their preconceptions. Metaphors are better at conveying values than specific, practical advice. They can obscure the areas of ignorance and uncertainty where evidence should be collected and lead us to believe we understand things we don't.

Despite all that, I love metaphor.  So far it is the most effective tool I've encountered for sharing values, the motivations for process and the assumptions we bring to discussions of how best to build software. Besides, I am the sort of person who sees parallels in everything I do. For me, writing software is like writing plays, post-modern lit crit, economics, psychology, art, poetry, baking, animal husbandry, gardening, physics, music and more. Some of these metaphors have usefully communicate to others (“coding reviews as writer's workshops”), others … not so much (“the computer as an economy”). Most often they are helpful going the other direction: I can describe coding to a poet by drawing analogies with their field, while most programmers probably wouldn't find those parallels useful because they are better versed in the language of software development than they are in the language of poetry.

Even though it may be where they are least needed, metaphors about code have always been employed when programmers talk to each other. Rather than invent a wholly new language, we compare our profession to everything from animation to farming. Sometimes these ideas feel more like thesis statements, a way to make otherwise context-less books flow and hold a reader's attention. Others are so widely embedded in our expectations that tracking down their origins is difficult.

Part of my background is in performance theory. It is the idea that people act in part to conform to or rebel against the stories they tell or hear about themselves. Psychology has more complete theories that describe individual manifestations of this, but I am interested, instead, in the interpersonal consequences of stories. We relate to other people based on what roles we see them play in our stories, and what role we see ourselves playing in theirs. If the senior person on my project describes themself as a “software architect” I will assume that my role as a programmer is different than if they describe themself as “technical lead”. They might actually perform the same tasks in either role, but I will assume that their expectations of my behavior are different, and so my behavior probably will be different whether or not I am conscious of it.

Metaphors are the stories programmers tell about ourselves. We are makers and builders, or we are scientists and engineers. We are crafters or servers. We are artists, assemblers, professionals, lovers of our profession. We are passionate seekers, humble students or skilled masters (or incompetent, frustrated, under-appreciated or under-performing geniuses).  We are cowboys and ninjas and rockstars (oh, the assumptions in those...)  Our stories about ourselves and our work change how we interact with each other, with our customers, with our code. I am never so intrigued by any specific badge as by the groups of people who choose to wear them.

For example, I believe that part of why “software is like building” became popular, rather than the more generic “software is like engineering” is because more programmers want to be like architects than engineers. We want to imagine ourselves as Frank Lloyd Wright, creating beautiful, useful, functional objects that people inhabit and own. As useful as electricity is, I admit that being Nikola Tesla is less appealing to me. “Architecture” as a metaphor lets us believe that we practical artists and artistic engineers.  It makes us a part the tradition of architects, stretching back thousands of years and putting our not-yet-a-century of conversations to shame.  Architects also have excellent PR, of course, and software isn't the only field to coopt the word.  The job titles "Interior Architect" and "Landscape Architect" are both attempts to borrow gravitas without giving up up all of the art suggested by their original "Designer".  Like "Agile" as a label, who wouldn't want to be An Architect?  

I've started researching different metaphors, mapping their rises and falls in popularity. I have fifty years of past writings to dig through before I'll feel prepared to jump into the fray myself, but in the meantime I plan to share some of what I am discovering here. I've been intrigued in particular by some analogies that have been abandoned, and the ways that our analogies begin to fall apart as the fields we compare ourselves to integrate technology. Over the past thirty-five years building a house has become more like writing a program than writing a program has become more like building a house.  Though they produce fewer good stories, collaborating with such hybrid professions may provide more practical improvements in the creation of software.

In koans: Quantum Computing

Quantum Computers are transistor computers, except all at once.

All things are true, false and unknown, until they are observed.

Answers are only opinions, but infinite opinions approach truth arbitrarily closely.

A race against entropy; how much can you calculate in the blink of an eye? Even that is too long to be certain.

Useful quantum computation is a compromise between reality and everything else. The more practical an approach is, the less likely it will be right. Miracles are correct, but impossible. Luckily, perfection is over-rated.

Each thing contributes to and is shaped by an influential whole consisting of connections spacial, temporal and quantum. Neither individuals nor the whole can be described without describing the other. Grasp this, along with linear algebra, and you begin to understand.

Future topics of discussion

The sorts of things that are likely to pop up here.  This list is as
much a reminder to me as it is a teaser for things to come:

1. Discussion of and updates on my independent projects
1.a. A GUI Matlab xUnit unit testing tool
1.b. Educational webapp games that don't reload the entire page any
time you click a letter
2. Metaphors of software development: an on-going series
2.a. Interviews with experts in fields often used as analogies to
software development exploring how they actually work
3. Culture of software development
4. Early history of computer programming and how it influences current practices
5. The intersections of software development and society at large
6. The current state of internet activism
7. Interesting articles from around the web on a huge variety of topics
7.a. A link to my Google Reader, which is less about software and more
about everything else in the world
8. Books I read and enjoy
9. Goings-on I attend in the Boston area
10. Intro-level how-tos of various sorts
10.a. First up, building your own computer