Slava Akhmechet wrote a piece a while back that that challenged my thinking in terms of design using an old familiar friend and adversary: Ant. If you are a Java programmer, you’ll recognize the patterns Slava is connecting with to share with you why Lisp is so interesting. BTW, this piece would work doubly well with Maven if it was updated. Go read.
Michael Fogus reviews the astonishing (to the unfamiliar) number or new programming languages being developed these past 5 years from Scratch to CoffeeScript, to Dart, it is quite a list.
So, you’re fan of the new Doctor Who series and are missing your weekly Doctor Who fix, this post is the start of a series just for you.
I’m not going to do that. I’m just going to suggest you watch one episode, maybe a week, with me, that hopefully stands the test of time. These episodes are available online if you have any Google-foo whatsoever. Remember, YouTube isn’t the only place where people post videos daily that have motion.
First in the list is an episode from the 4th, written by Douglas Adams (yes – THAT Douglas Adams!!!) that starts out a little cringe-worthy, but turns into a fun, and interesting story, that just maybe related to the current show in more ways than one (check out that ship for example – look familiar?) – “City of Death”.
Wikipedia: “City of Death”
TARDIS Index File: “City of Death”
Look for it, watch it. Sure there are more important things, but you got to have a little fun.
Sometimes we get caught in numbers and miss what’s real. This can happen especially when we focus on the wrong numbers writes Arpit Mathur in a sharp post. I’d add even if you were looking at the right numbers, without context, just like a soundbite, you could derive the wrong lessons or encourage behavior that you didn’t desire.
Always ask: What is it we are trying to effect or learn about? Are we looking at the right things? Do we have the context necessary to understand it?
“Systems Thinking, Lean and Kanban”: “Creating Useful Measures”
Michael Feathers: Rocky Mountan Ruby 2011 Keynote: “Code Blindness” – fantastic – watch the whole thing.
When you’re building software, it is probably best to look at things half-Buddhist. Kent Beck writes about building software that won’t be around longer than him in a recent Facebook note:
…nothing I am doing now with software will remain in a hundred years. Indeed, there was a time not long ago when the only software I had ever written that was still running was JUnit. Thousands of programs started, and my work was in danger of becoming extinct.
I could try to achieve timelessness in my designs and encourage others to do the same, but in the end nothing I program will outlive me. It would be easy to despair over this, to go into my shell and settle for “good enough”. To do so would be to ignore both the immediate impact of my work, used by hundreds of millions of people today (one of the great things about working at Facebook), and the second order effects of my work on the lives and attitudes of others. No, my programs won’t be here in a century, but my work still matters.
Michael Mehaffy and Nikos Salingaros: “The Pattern Technology of Christopher Alexander”: “We have to remember that software engineers, by nature of their work, have a big problem. Their job is not to solve problems for computers, but for human beings; the computers are only tools in that process.”
Case Statement: “Articulate Coding” – his first post – a good one – keep it up!
InfoQ: Kent Beck: “Responsive Design” 1hr Presentation. Worth it!
My boss back at Bell Atlantic, who became my friend and mentor, Pat Trongo, had the following quote from Peter Senge’s “The Fifth Discipline” on his cube wall in big bold letters.
I found it inspirational back then. But now I am blessed to see evidence of this pattern in life daily – Great teams committed to a purpose accomplish great things.
The committed person brings an energy, passion,
and excitement that cannot be generated if you
are only compliant, even genuinely compliant.
The committed person doesn’t play by the rules
of the game. He is responsible for the game.
If the rules of the game stand in the way of
achieving the vision, he will find ways to change
A group of people truly committed to a common
vision is an awesome force.
They can accomplish the seemingly impossible.
I am as blown away by this as I am with the OccupyPhilly protest teamwork I saw today, as I am with my co-workers who are one of the greatest teams I’ve seen in my career.
Great teams are everything. They don’t just ‘happen’ and require investments in trust, empathy, accountability, honesty, and crazy foolishness to grow. And when you see them you can’t help but be in awe.
There are many, many tributes being shared over the Web these past 12 hours or so and I’d hate to just add to it, considering I am not among those who think Apple can do no wrong, or that Steve Jobs alone saved Apple. But I need to mark it here because his work affected all of us in so many dimensions. From his realization that the liberal arts played as much a role in technology as engineering, from his personal story of perseverance and his capacity to create his own 2nd acts, each one built on lessons from his past, to his push to create tools that… well… he’s going to be remembered for Apple, for NeXT, for Pixar, what they made, and folks will say he was a genius.
Me? I’m going to remember that he helped empower people to dream and create.
People compare Steve Jobs to his peers, but I think of him like Jim Henson, someone who was driven to make, to help others make, who brought teams together and found ways to instill it in them. Tools to help you to make, and to share what you make. To dream, and to share what you dream.
Thank you Steve Jobs and for the teams he was part of.
Steven Levy: Steve Jobs, 1955 – 2011
Metafilter: Steven Jobs, RIP
Wall Street Journal: Steve Jobs’s Best Quotes
And 15 minutes to take that will, I hope, inspire you:
I’ve really been enjoying Lisa William’s blog titled “Life and Code” and think it’s a great one for your RSS reader every day. She started to blog to document her passage to a programmer who can toss together an app on a whim in a weekend and her background in online media and journalism makes for some great posts and links to follow.
The following is a quote from her, on her motivations to start coding (“Code to make a point; code to make change; on newshacking”, which resemble motivations that keep me wanting to continue code and to volunteer my skills:
I believe a program can stand in opposition to Things That Suck, just like a documentary, a work of art, or a protest march.
That’s why I like work like this, which shows where the money goes when it comes to Congresscritters and their free cars.
Or this, which is an Android app to help vets with PTSD.
I wanna code because SHIT IS BROKEN. I want to code because corruption is real, because people are getting thrown out of their houses, because veterans aren’t getting what they deserve, because racism is real and has real effects, because yes it does matter when you cancel a bus line, because it’s really hard to shut a computer program up, because you can’t say it’s an isolated incident when there’s a bigass Google Map in your face showing you it’s not.
And journalism’s response to the biggest problems of our age — global warming, global health, economic crises — are, all too often, pathetic: he said/she said talking heads on TV, tearjerker anecdotes about one person who loses their house to a flood or rapaciously unethical lenders standing in for THE VAST TSUNAMI OF PEOPLE GETTING F**D OVER BY THESE THINGS. No wonder facts just seem to bounce off so many Americans, and so many of the powerful are able to claim that nothing needs to be done when doing nothing suits their moneyed interests.
Our age doesn’t just NEED computational journalism: it DEMANDS it.
Edsger W. Dijkstra gave a lecture, in 1972, that has since been come to be called “The Humble Programmer”. It’s a short piece that explains why software development, why programming, was growing more, not less complex over time, and some inspiration to be found in the dealing with it. There’s some choice quotes in here that I’m going to include, but read the whole thing.
With a few very basic principles at its foundation, it has shown a remarkable stability. Besides that, LISP has been the carrier for a considerable number of in a sense our most sophisticated computer applications. LISP has jokingly been described as “the most intelligent way to misuse a computer”. I think that description a great compliment because it transmits the full flavour of liberation: it has assisted a number of our most gifted fellow humans in thinking previously impossible thoughts.
Lets call it TDD before TDD was coined:
Today a usual technique is to make a program and then to test it. But: program testing can be a very effective way to show the presence of bugs, but is hopelessly inadequate for showing their absence. The only effective way to raise the confidence level of a program significantly is to give a convincing proof of its correctness. But one should not first make the program and then prove its correctness, because then the requirement of providing the proof would only increase the poor programmer’s burden. On the contrary: the programmer should let correctness proof and program grow hand in hand.
On decomposing systems:
It has been suggested that there is some kind of law of nature telling us that the amount of intellectual effort needed grows with the square of program length. But, thank goodness, no one has been able to prove this law. And this is because it need not be true. We all know that the only mental tool by means of which a very finite piece of reasoning can cover a myriad cases is called “abstraction”; as a result the effective exploitation of his powers of abstraction must be regarded as one of the most vital activities of a competent programmer. In this connection it might be worth-while to point out that the purpose of abstracting is not to be vague, but to create a new semantic level in which one can be absolutely precise. Of course I have tried to find a fundamental cause that would prevent our abstraction mechanisms from being sufficiently effective. But no matter how hard I tried, I did not find such a cause. As a result I tend to the assumption —up till now not disproved by experience— that by suitable application of our powers of abstraction, the intellectual effort needed to conceive or to understand a program need not grow more than proportional to program length. But a by-product of these investigations may be of much greater practical significance, and is, in fact, the basis of my fourth argument. The by-product was the identification of a number of patterns of abstraction that play a vital role in the whole process of composing programs. Enough is now known about these patterns of abstraction that you could devote a lecture to about each of them.
As each serious revolution, it will provoke violent opposition and one can ask oneself where to expect the conservative forces trying to counteract such a development. I don’t expect them primarily in big business, not even in the computer business; I expect them rather in the educational institutions that provide today’s training and in those conservative groups of computer users that think their old programs so important that they don’t think it worth-while to rewrite and improve them. In this connection it is sad to observe that on many a university campus the choice of the central computing facility has too often been determined by the demands of a few established but expensive applications with a disregard of the question how many thousands of “small users” that are willing to write their own programs were going to suffer from this choice. Too often, for instance, high-energy physics seems to have blackmailed the scientific community with the price of its remaining experimental equipment. The easiest answer, of course, is a flat denial of the technical feasibility, but I am afraid that you need pretty strong arguments for that. No reassurance, alas, can be obtained from the remark that the intellectual ceiling of today’s average programmer will prevent the revolution from taking place: with others programming so much more effectively, he is liable to be edged out of the picture anyway.
There may also be political impediments. Even if we know how to educate tomorrow’s professional programmer, it is not certain that the society we are living in will allow us to do so. The first effect of teaching a methodology —rather than disseminating knowledge— is that of enhancing the capacities of the already capable, thus magnifying the difference in intelligence. In a society in which the educational system is used as an instrument for the establishment of a homogenized culture, in which the cream is prevented from rising to the top, the education of competent programmers could be politically impalatable.
On recognizing the difficulty, challenge, and opportunity:
Automatic computers have now been with us for a quarter of a century. They have had a great impact on our society in their capacity of tools, but in that capacity their influence will be but a ripple on the surface of our culture, compared with the much more profound influence they will have in their capacity of intellectual challenge without precedent in the cultural history of mankind. Hierarchical systems seem to have the property that something considered as an undivided entity on one level, is considered as a composite object on the next lower level of greater detail; as a result the natural grain of space or time that is applicable at each level decreases by an order of magnitude when we shift our attention from one level to the next lower one. We understand walls in terms of bricks, bricks in terms of crystals, crystals in terms of molecules etc. As a result the number of levels that can be distinguished meaningfully in a hierarchical system is kind of proportional to the logarithm of the ratio between the largest and the smallest grain, and therefore, unless this ratio is very large, we cannot expect many levels. In computer programming our basic building block has an associated time grain of less than a microsecond, but our program may take hours of computation time. I do not know of any other technology covering a ratio of 10/10 or more: the computer, by virtue of its fantastic speed, seems to be the first to provide us with an environment where highly hierarchical artefacts are both possible and necessary. This challenge, viz. the confrontation with the programming task, is so unique that this novel experience can teach us a lot about ourselves. It should deepen our understanding of the processes of design and creation, it should give us better control over the task of organizing our thoughts. If it did not do so, to my taste we should not deserve the computer at all!
It has already taught us a few lessons, and the one I have chosen to stress in this talk is the following. We shall do a much better programming job, provided that we approach the task with a full appreciation of its tremendous difficulty, provided that we stick to modest and elegant programming languages, provided that we respect the intrinsic limitations of the human mind and approach the task as Very Humble Programmers.