Real Options—a Mindset - an intro into the Real Options approach, which has been quite a hot topic and a transformational way of thinking for a number of inspiring people (Dan North, Liz Keogh etc.). "Real Options help us to better make decisions and commitments with three simple principles: Options have value. Options expire. Never commit early unless you know why." We can "pay" to keep our options open longer, i.e. to avoid commiting prematurely.
Demystifying the CHAOS report's claim of ~ 1/2 features being unused: the Standish Group's CHAOS report has been often quoted for its "finding" that a large percentage of features in applications is never/rarely used. However this claim seems to have never been confirmed, their "research" is reportedly not very scientific and not publicly available for scrutiny. Critique by Laurent Bossavit (2013), Jorge Aranda's Standish, the CHAOS report, and science. Thx to @smalltalk80 for pointing this out! However there is one research, Online Experimentation at Microsoft, that supports the claim, in a different context but the same problem applies to features: "Evaluating well-designed and executed experiments that were designed to improve a key metric, only about one-third were successful at improving the key metric!"
Why Yammer believes the traditional engineering organizational structure is dead - small teams, small projects (2-10 people, 2-10 weeks), no separation into front/middle tier/backend team (=> communication, design obstacle); have instead people specializing in these areas and construct feature teams from them based on the actual needs; engineers, not managers do eng. decisions; all aligned via focusing on the same 3 key metrics. Small projects => constant sense of urgency (and excitement): Often very long projects cause engineers to lose track of the end goal. Think of it in terms of hiking: start fresh & excited, get tired and losing track of the goal, excited again at the end => cut out the middle part, keep them in the exciting state where they can measure progress and see it visually; it’s the only way to maintain urgency and morale. Focus: people alwasy work only at one (short) project at a time (there are special bug-fixing teams for maintenance tasks with people rotating in&out).
Agile development is more culture than process - Why thinking of agile as culture and not just process explains resistance and difficulty in teaching and learning the approach - and should be taught so => 1. Underscore agile values that motivate practice; 2. Identify organization values that compete with agile values, conflict of values; 3. Be sensitive to culture shock.
Mark Zuckerberg's Letter to Investors: 'The Hacker Way' (quite long, you might want to read only "The Hacker Way" part at the end) - about Facebook's "unique culture and management approach" - "Hackers believe that something can always be better, and that nothing is ever complete." "Hackers try to build the best services over the long term by quickly releasing and learning from smaller iterations rather than trying to get everything right all at once." "Instead of debating for days [..], hackers would rather just prototype something and see what works." "Hacker culture is also extremely open and meritocratic." "Many of our most successful products came out of hackathons, [..]." <=> five core values: Focus on Impact (focus on solving the most important problems, be good at finding the biggest problems to work on); Move Fast ("[..] if you never break anything, you’re probably not moving fast enough."); Be Bold ("Building great things means taking risks."); Be Open (=> effort to make as much info as possible visible to all); Build Social Value ("[..] Facebook exists to make the world more open and connected, and not just to build a company. ")
Dave Nicolett: I know how to tie my shoes - on the difficulty of convincing people to try unfamiliar software development techniques - "People change the way they operate when they are experiencing some sort of inconvenience or negative feedback. As long as things are going along reasonably well, people don’t go out of their way to change the way they work." (with few exceptions) You can learn to tie your shoes in a split second, but why to invest the effort? You'd need to set aside assumptions, suppress habits, practice. You can argument there are many inconveniences (bugs, criticism for slow delivery, ...) but "Unfortunately, that’s all pretty normal, and most people in the software field are accustomed to it. They don’t see it as a problem that calls for them to change their practices. Most of them probably have a hard time visualizing a different reality." => Maybe that’s the reason there’s been no satisfactory answer to the question of how to convince people to adopt different practices. We shouldn’t be trying to convince people to do anything. We should be helping people solve their problems and achieve their goals. If they are satisfied with the outcomes they achieve using their current methods, then there is no problem to solve.
Kent Beck: Pace of Progress = Pace of Feedback - '"The pace of my progress is completely constrained by the pace of my feedback". If I want to go faster, it's hard to achieve by going faster. I can almost always optimize my feedback loop, though.' "The second lesson from this episode is that it's not just the duration of the feedback loop that matters, it's also the quality. All week I was working in tiny little iterations. Without producing useful information, though, those iterations could be as small or as large as I liked, I was still just going to spin my wheels." => "The next time I seem to be going slow, I'm going to look at my whole feedback loop--duration, quality and my ability to respond to the information."
What Google Has Learned About How to Hire People - interview results have no relation to actual performance on the job: "We looked at tens of thousands of interviews, and everyone who had done the interviews and what they scored the candidate, and how that person ultimately performed in their job. We found zero relationship. It’s a complete random mess." "Instead, what works well are structured behavioral interviews, where you have a consistent rubric for how you assess people, [..]" 'Behavioral interviewing also works — where you’re not giving someone a hypothetical, but you’re starting with a question like, “Give me an example of a time when you solved an analytically difficult problem.”' Link to an interesting book, Hiring Geeks That Fit.
Cool tech stuff
The Elixir language - Clojure + Ruby + Erlang - a functional meta-programming aware language built on top of the Erlang VM; a dynamic language with flexible syntax with macros support that leverages Erlang's abilities to build concurrent, distributed, fault-tolerant applications with hot code upgrades. First-class support for pattern matching, polymorphism via protocols, etc. (via @bodil)
Random Testing seems to be gaining popularity and looks very interesting; at NDC Oslo, John Hughes has presented how QuickCheck, which generates random sequences of API calls, has been successfully used to find bugs in the Riak DB and a file system that a human would never think of, and Stuart Halloway has presented simulation testing with Simulant, which runs predefined actions according to a probabilistic model (e.g. 100 traders, each having 1h mean time between trades and mean traded amount 100, the test runs for 4 simulated hours). Something worth exploring!
Dmytro Navrotskyy's collection of Frontend Development resources and learning materials for tools (grunt, unused css detection,..), best practices (Atomic Design, ...), JS/CSS frameworks, typography, animation, visualization, useful on-line services, and many more (via Herman Schistad)
The Secret To 10 Million Concurrent Connections - The Kernel Is The Problem, Not The Solution: To have really fast SW, you need to implement your own core services (FS, net driver (packet handling), thread scheduling, ..) tuned for your app. You need to be aware of the clock-time cost of cache misses, memory access etc.. Custom solutions are times faster than what the general OS kernel can offer. => "data plane oriented system" Core areas and solutions for them: packet scalability, multi-core scalability (locks are expensive), memory scalability.
Other
M. Fowler: EmbeddedDocument - a pattern for working with JSON flowing in/out of our services (REST <-> JSON-friendly DB) without unnecessary conversions but with good encapsulation; naive approach: json -> object graph -> (processing) -> json; "In many of these situtiations a better way to proceed is to keep the data in a JSONish form, but still wrap it with objects to coordinate manipulation." - use a lib to parse the JSON into a generic structure (e.g. a structure of lists, and maps/dicts) and store in a field of an object defining methods that encapsulate it - f.ex. for an Order we could have a method returning the customer and another computing the cost, accessing the underlying generic structure. The user of the wrapper object doesn't need to know/care about the underlying structure. "The sweet spot for an embedded document is when you're providing the document in the same form that you get it from the data store, but still want to do some manipulation of that data. [..] The order object needs only a constructor and a method to return its JSON representaiton. On the other hand as you do more work on the data - more server side logic, transforming into different representations - then it's worth considering whether it's easier to turn the data into an object graph."
ThoughtWorks' Approach To Big Data Analytics - an inspiring, brief read. Some really good points such as "It’s not about Data. It’s about Insight and Impact" => "focus on the questions you’d love to answer for your business" => "changing big data from a technological problem to a business solution." Also "The value of data is only realised through insight. And insight is useless until it’s turned into action." Measure the value you gain at each step. See Introducing Agile Analytics: A Value-Driven Approach to Business Intelligence and Data Warehousing by Ken Collier
Wired.com, Nassim Taleb: Beware the Big Errors of 'Big Data' - in big data, noise has much stronger effect and in a large enough dataset we will always find spurious (i.e. false) relationships => beware! "Well, if I generate (by simulation) a set of 200 variables — completely random and totally unrelated to each other — with about 1,000 data points for each, then it would be near impossible not to find in it a certain number of “significant” correlations of sorts. But these correlations would be entirely spurious."
A Taste of Salt: Like Puppet, Except It Doesn’t Suck - a deescription of Salt and the tools around by an enthusiastic user with deep experience with Puppet. Highlights: Light-weight communication over ZeroMQ, very active community, simplicity, configuration is YAML, Salt-cloud can spin instances in EC2/Openstack/..., Salt-virt does the same for virtual machines (KVM/Xen/...), Salt-vagrant, Salt-monitor (work in progess) can ask all the server for their stats. "Having stood up a number of different configuration management systems across a wide variety of environments, I’ve yet to find a solution that’s as rapid to deploy, simple to scale, or as well architected as Salt."
Robin Ward: AngularJS vs Ember - a nice overview of the different approaches of the two; the author is strongly pro-Ember, claiming that AngularJS is much closer to low-end libraris like Backbone/Knockout and that you will often need the additional features of Ember. The comments provide the right countrweight to the biased post and form thus a good whole together.
After Your Job Is Gone - an interesting essay on the future, which, according to the author, we can already see happening, when technology will take away most of our work and we will not need to work all day. Not very optimistic, though (the author predicts few reach and many poor people).
Clojure Corner
Clojure Cup 2013, Sept 28-29 - create something cool with Clojure/ClojureScript within 48h and perhaps win a price! #fun
Stuart Sierra's My Clojure Workflow, Reloaded (6/2013) - mainly about reloading changes into REPL, working around things that are not reloaded/left over => restart the app from scratch after significant changes => the app as a transient object => no global state, careful management of resources, :dev profile with :source-paths to a dir with user.clj (autoloaded by repl, pre-loading useful stuff) and dev util deps
Juxt.pro: Jon Pither's and Malcolm Sparks' "network of experienced IT professionals who specialise in the Clojure programming language," providing training, consulting, talks
Anthony Grimes: The Clojure Community and Me (2011) - an exciting insight into the embracing and supportive Clojure community
In Clojure-based Machine Learning: "Our backend is 99.4% coded in Clojure, and 66% of the team [of 3] had never programmed seriously in any Lisp, let alone Haskell or Prolog (heck, not even I (the remaining 33%) had actually tried anything non-mainstream for real in a big project!) Maybe some Ruby, and lots and lots of Java and C and C++. But they accepted the challenge after reading around and learning the basics, and 3 months later you couldn’t take Clojure from their prying hands."
J. Pither: TDD and Clojure - "If you were to create a shopping list of things you really want for your development experience then what would you put at the top?" => 1. rapid feedback on changes, 2. REPL (place to explore and to play with your code <=> TDD), 3. FP and Immutability ("FP and dynamic languages lead to a lot less code. There’s less ceremony, less modeling. Because you’re managing less code you do less large scale refactorings." => TDD needed less), 4. Regression Tests ("It’s my current opinion that what you get left out of TDD once you have amazingly fast feedback and a REPL is regression testing.")
If a candidate came telling me that s/he wanted to program only in, say, Java because that’s what s/he knows best and that s/he doesn’t really feel prepared or interested in learning and using, say, Clojure (or any other language, really), I wouldn’t hire her/him in a million years, no matter what language my project were using, and no matter how many thousands of candidates like this one I had at my disposal.
- José Antonio Ortega in Clojure-based Machine Learning
We shouldn’t be trying to convince people to do anything. We should be helping people solve their problems and achieve their goals. If they are satisfied with the outcomes they achieve using their current methods, then there is no problem to solve.
- Dave Nicolett in I know how to tie my shoes