I write the code that makes the whole cloud sing
I write the code that runs the onboarding
I write the code that makes the whole team smile
I write the code that writes the code
[with apologies to Barry Manilow]
I like clean code ’cause it cannot lie
I like clean code ’cause it cannot lie.
Technobabble makes me cry.
But with a clear interface
The domain’s in your face
Intentions fall into place
You get stunned
Like getting slapped with a map
Anything less is just crap
(with apologies to Sir Mix-a-Lot)
Talking about Three Rules for Domain-Driven Design at O’Reilly Software Architecture Conference Wednesday, April 5 at 1:15pm Eastern Time in NYC.
What does software look like?
Did you ever ask yourself a question that was so interesting that finding the answer sort of turned into a mini-obsession?
For me, that question was “What does software look like?”
Not what can it look like, because obviously software has no predetermined visual form, but what would it look like if it had a natural, organic, 3D structure? A structure that was the same regardless of scale, from a simple Hello World to a multi-million line production system?
And what could we learn from such visualizations?
Drawing on data science as well as more traditional software analysis techniques, I began to explore this interesting visual world. The initial intent was to simply find ways of looking at software systems where anomalies would be easily spotted, as easily as you might notice a broken branch on a tree in a forest.
Slowly, connections between software visualization, software archaeology, latent semantic analysis, software refactoring, and domain-driven design began to form… along with some hints at Much Larger Problems, and study of Deep Learning.
This research is ongoing.
Update:
- The first talk was “Deep Learning for Software Development”, given at DeveloperWeek 2017 in San Francisco, CA. Siddhartha Agarwal tweeted the scary bits, and George Lawton posted an article on the talk at How deep learning and AI techniques accelerate domain-driven design after chatting over lunch.
- A more in-depth talk on this topic was given at SATURN 2017 in Denver, CO. Watch Deep Learning for Software Development on YouTube
P != NP … Awesome!
A researcher at HP, Vinay Deolalikar , has published a paper purporting to prove that P != NP. Awesome! I hope it’s correct and that he is awarded the Millennium Prize promptly for clearing this up. This is a seriously impressive thing to do. I got lost in the third paragraph of the abstract.
So what does this mean to programmers? Not much. Because we never believed that P == NP could be true in the first place.
Still, it’s nice to have confirmation.
Computer Science students can now stop looking for a linear solution to the Traveling Salesman problem, and go back to flirting on Facebook debating Java vs. C# on CodeProject.com.
Old Developers – Any Future?
A question was posted on the stellar StackOverflow site a while back, asking if there was any future for “old” developers.
Here is my answer, courtesy of the ingenious Stack2Blog site, slightly edited and reformatted:
Yes Virginia, There Is A Future For Old Developers
I resemble that remark.