Thursday, July 28, 2016

Simulations and Chosen Realities

My best guess about the future is eventually we will all be “uploaded into the cloud.” (awkward, but it gets the meaning across)

It’s tempting to say we’ll all be living in a ‘simulation’ at that point. But, I think by that point we will select a new term.

When we say ‘simulation’ we mean something somehow inferior or an approximation to the ‘real thing.’ The problem with that notion is our perception of the ‘real world’ is always an inferior approximation of the real thing.

Therefor experience and perception are always a ‘simulation’ of the ‘real world.’

If we live in the cloud, and we experience a world that is generated for us by algorithms, as long as that experience is AT LEAST as accurate as our ‘real-world’ experiences were, then I don’t think it’s fair to call it a simulation anymore.

It’s something more. It is a ‘chosen reality.’ In some sense it will be inferior since the ‘real world’ will always be more complex and nuanced than our generated ones. But the difference will be beyond our ability to perceive it. Our chosen reality will be superior perceptually. It will be the reality we want, not the one forced on us. 

Wednesday, July 6, 2016


What-You-See-Is-What-You-Get was always an awkward acronym. Say "wizzywig" and people just look at you strangely. There is an amusing anecdote about the origin of the acronym on Wikipedia. I hope it's true:
The phrase "what you see is what you get," from which the acronym derives, was a catchphrase popularized by Flip Wilson's drag persona Geraldine, first appearing in September 1969, then regularly in the early '70s on The Flip Wilson Show. The phrase was a statement demanding acceptance of Geraldine's entire personality and appearance. wikipedia 

NINO - Natural-In, Natural-Out

The idea, though, is powerful. Being able to see what the output of your work looks like as you edit is a tremendous relief to the mental burden of creation. It was a hot idea in the '80s and '90s, but it is equally important, and often ignored, today in 2016.

The main problem with WYSIWYG is it is only half the equation. How we put information into an app is equally important as how we get information back out. Just as we shouldn't have to perform mental gymnastics trying to anticipate how our final output will look, we shouldn't have to wade through a bewildering array of options to get our ideas into the app.

The best interfaces are the ones that get out of the way. You know an app is well designed when you completely forget the interface and instead can dedicate 100% of your mental energy towards your creation. These interfaces tend to have two things in common.
  1. They visually get out of the way. There is less screen clutter to distract you.
  2. Their feature-set is restrained. They avoid presenting you with too many options. Instead, they are carefully designed to have the bare minimum essential tools you need to create great stuff.

Comparison: Paper by FiftyThree - a NINO App

As of version 3, Paper by FiftyThree extended its excellent sketching app with note taking features. They introduce a brilliant set of natural gestures for formatting your notes that required zero screen clutter.

Comparison: Microsoft OneNote - a very Un-NINO App

By contrast, consider OneNote. It has a bewildering array of features, buttons, icons, widgets and text. My note in the screenshot below has a short title and one line of text. It is oppressively dominated by the rest of the interface.


Our devices, phones, tablets, computers, watches and more and more becoming extensions of our mind and body. I once heard a description of smart-phones, particularly with notes and productivity apps, as our exocranium. These devices and apps are becoming our brain outside our brain. The better the app, the more natural an extension of our mind and body. The better the app, the more natural its inputs and outputs - the more NINO it is.

Sunday, June 12, 2016

WLC - Write Less Code

Given two solutions to a problem, the one with less code is usually better. 

Plite of the Programmer

Our job as programmers is to deliver value to customers. We deliver value by identifying needs, translating them into requirements, and writing code to meet those requirements. The difficulty of the task is compounded by the fact that requirements are constantly, unpredictably changing. Even after we finally ship, the story isn’t over. Code is a living thing that must be maintained, usually well beyond anyone's expectations.

Over the lifetime of a product, we will edit code 10x more than we write code, and we will read code 10x more than we edit it. Each token we add to our code may be read over 100 times. Every token we save could save up to 100 token-thoughts and 10 future edits. The key to our productivity is writing less code.

Why Count Tokens?

Tokens are the smallest meaningful element in code. Tokens are a more objective measure of code size since lines can have any number of tokens. Measuring tokens also ignores white-space and comments. Last, measuring tokens doesn't penalize using clear names. ‘Occupations’ is just as good a name under the token metrics as ‘occus’ or other hard to understand abbreviations.

Don't abbreviate words. Saving keystrokes only saves writing the code. It doesn't save edits or reading. Abriviations make reading harder. Since reading code dominates our time, abbreviations are a losing proposition. Only use shortened words if the shortened version is used at least as commonly in speech.

Measuring tokens is a simple, effective metric that lets us make decisions quickly and get on with solving problems and delivering value.

Why ‘Write Less Code’?

It's a simple concept with depth. Amateurs and masters both can apply and learn from it. A more accurate metric might be refactorability. We spend most of our time refactoring code, not writing it. Refactorability is the code-quality metric. It can be broken down into code size, clarity, and structure. Of the three, size is the only one that can be objectively measured, and while clarity and structure are important, both are usually improved by reducing code size. Refactorability is not something a novice will understand. ‘Write less code’ is an excellent guiding principle for all programmers.

How to Write Less Code

All other good coding practices essentially reduce code size. Two of the most important, and most often violated coding practices for reducing code-size are DRY and ZEN.


Don't. Repeat. Yourself. Don't you dare repeat yourself ;). The most problematic artifacts I've seen, both from novice and expert programmers, is code repetition. The big problem with repetition is it compounds the complexity of refactoring. Not only do we have to fix two or more things instead of one, but we have to understand how they all interact. Plus it bloats the code-base making it hard to understand.

DRY is a subtle art. The first, obvious level is ‘don't copy-paste your code,’ but as we level-up, we start to realize anything gzip might compress potentially violates DRY. The ultimate measure is, as always, refactorability. How many code-points need to change for a common refactor? Is there a way to reduce repetition to reduce the complexity of refactorability?


Build it with Zero Extra Nuts (more commonly known as YAGNI). Because it is impossible to
predict future requirements, adding anything to our code that isn't strictly necessary to meet current requirements is not only a waste of time now, but it will haunt us for at least 10x future edits and 100x future reads.

It is fun to add cool features, but the master knows the only thing that matters is delivering value to the customer.

Write Less Code - Formalized

My hypothesis, and my experience, comes down to this:

  • Given two different functions, modules or programs
  • that both meet or exceed the problem's requirements, both correctness and performance
  • the one with less tokens is always better
  • as long as it doesn't sacrifice clarity.

The Practice of Writing Less Code

As with everything in life, writing less code is a practice. There is no point where we will master it. There is always another layer of deeper understanding. We are always learning how to make our code DRYer and more ZEN. We must constantly be looking for ways to meet requirements with less code.

Saturday, February 6, 2016

ZEN (YAGNI) and Building In-House Frameworks

ZEN - Zero Extra Nuts. ZEN code is minimalist. It is relentlessly focused on solving exactly the requirements and nothing more. (3)
Write only what you need. It’s a profound concept. Engineers can’t help but overbuild things. For some reason this is inherent to being an engineer. In physical engineering, overbuilding is mostly an issue of up-front cost in terms of extra time and material. In software, there is also a substantial ongoing expense. The maintenance cost of code is related to its total size (1).


ZEN implicitly includes DRY (don't-repeat-yourself). Code repetition is one of the most pernicious forms of "Extra Nuts." Learn more about the subtleties of code repetition here.

ZEN and Frameworks

Minimizing the size of the code-base is an important goal. Using standard abstractions like functions and classes can reduce the total codebase size. This isn’t the same as building a framework.

What is a Framework?

A framework is a module. At their heart, modules are about encapsulation. Modules have an external interface and internal implementation. Better modules have simpler interfaces and more-isolated implementations.

Frameworks are different from other modules because they are designed to be used across multiple applications. Frameworks must be the best possible modules. In order to work across multiple applications, a framework must have the simplest possible interface and the most isolated implementation. Frameworks should also have their own codebase and be packaged for easy reuse.

Why Do We Build Frameworks?

If ZEN were the only value, we would never build frameworks. By the time we’ve built a solution to the required specs, we ship. End of story. That’s what ZEN tells us to do. If we only followed ZEN, our applications would include operating systems, drivers, database, compilers and every other part of our dev and runtime stack. In other words, each new application would be enormous and have a fraction of the capabilities we enjoy today.

I said above that the maintenance cost of code is related to its total size. When we measure the size of code in an app we do not include frameworks. This is for good reason. The complexity a module adds to an app is proportional to its interface size and leakiness of its implementation. Frameworks are the best of modules. Their leakiness is minimal and their interface refined. A framework with millions of source-tokens may only add a few thousand tokens worth of complexity to a project using it. 

Are In-house Frameworks Worthwhile?

Clearly using other people’s frameworks is a big win. You get 100x or more leverage in terms of complexity. You only have to maintain your application’s code base and you get all the framework’s capabilities for a very modest price. Building a framework in-house at first doesn’t seem like a good idea. The total code-size you have to maintain will increase when you take an application and factor it into an in-house framework plus the rest of the app.

We talked about how application code-size is properly measured, but we haven’t talked about how that value relates to maintenance. Maintenance costs are proportional to complexity, and complexity’s relationship to code-size is non-linear. If you double the code-size, you will more than double its complexity (2).

Realizing that code-complexity is non-linear in code-size reveals why it makes sense to write frameworks even if they only have one app using them. If the application’s code-size is N-tokens before we factor out the framework, and let's assume that we can cut the application code in half by factoring out the framework. There is always some overhead in writing a framework due to interface and abstraction code. We’ll assume that overhead is 10%.

After the split, both the framework and app will have (1.1 * N/2) tokens, or (1.1 * N) total. For simplicity, our final assumption is a complexity-to-size factor of O(N2):

  • Complexity before split: N2
  • Complexity after split: 0.6 * N2
    • App: (1.1 * N/2)2
    • Framework: (1.1 * N/2)2
    • Total: 2 * (1.1 / 2)2  * N2

That’s a 40% savings! Granted, I made the favorable assumptions, but clearly it is possible to have large savings. Further, you don’t have to limit yourself to making just one framework. There are diminishing returns, but in my experience I've still found improvements with over 10 in-house frameworks.

Once you have a good framework, it is possible to re-use it in other apps. Then the savings really start to compound. If we assume just two apps, using the example above, the complexity savings increase to 55%. You also get code-size savings as well - about 18%.

When to use 3rd Party Frameworks

Obviously you should use an existing framework, if one exists, instead of writing your own. Right? Well, when evaluating the merits of a 3rd-party framework, there are a lot of things to consider. 

Let's start with technical aspects:

  • Does it do what you need it to do?
  • Does it meet your performance goals?
  • Is the source open?
    • Can you look at the source code? No matter how good the documentation is, there are always questions it doesn’t answer. If the source is open, you can get definitive answers. If not, you will be flying blind.
  • Is it OpenSource?
    • Can you contribute improvements back to the project?
    • How clear are the maintainers about what sort of contributions are acceptable?
    • Can you fork the project? This is only a last resort, but it is nice to have as an option. If you expect to fork early, you will be mostly maintaining your own, in-house framework. The problem with this is it is a codebase no-one in your organization knows well. Seriously consider writing your own in-house framework from the start.
  • How difficult will it be to switch frameworks later? 
    • How much of your code will directly interact with the framework?
    • If you are picking a UI framework, most of your code will be tied to that framework. Changing frameworks later probably means rewriting the app from scratch.
    • If you are using an encryption framework, like, say, md5, only a line or two of your app will use it. Changing that framework later is usually trivial.

There are also important non-technical aspects to evaluate:

  • Momentum. Usually there are multiple options for the same type of framework. Eventually, some die out and some thrive. It’s a good idea to use a tool like Google-Trends to determine which projects are thriving and which are dieing. If a framework dies, you may need to fork it to maintain it, and then you are back to maintaining an in-house framework.
  • Direction. 3rd party frameworks evolve outside your control. It is important to not only assess the current technical merits of the framework, but also, where is the framework going? What values and goals does the controlling team have? What values and goals does their organization/funding have? If your use-case is not squarely in their target use-cases, seriously consider looking elsewhere.

When to Write an In-House Framework

There are two main questions to ask each time you consider building a framework:

  • Is it the best of modules?
    • Is the interface simple?
    • Will the implementation be well isolated and minimally leaky?
  • Is there a reasonable chance you’ll reuse the framework on other projects? ZEN argues you should be cautions making assumptions here, but if you think there is a > 90% chance you’ll reuse it even once, this can be a big factor.

If you haven’t written a line of code yet, should you even consider writing a framework yet? You should never write something unless you know for certain you will use it. Don’t build more than you immediately need for current requirements. In this, you should always follow ZEN.

However, when looking at current requirements, it is reasonable to ask how you are going to meet them. As you do, you will be considering how to modularize your implementation. If you are doing an agile approach, this design work will happen in code as you go. If not, you may be doing some up-front design. Either way, there will be a point where you have modules.

As soon as you start to form modules, you should start thinking about if the modules make sense as a frameworks. If the answer is “yes” to both questions above, then package up the module immediately, put it in its own code-base, and declare it a framework. The sooner you do it, the sooner you can reap the simplification rewards. Once you do, keep following ZEN. Continue to only add functionality as you need it.

Frameworks Clarify Thinking

Frameworks have another benefit beyond reducing complexity. Once you have isolated part of your code in a framework it takes on a life of its own. It has purpose beyond just serving the current app (though it should still be driven by that app's requirements ala ZEN). A framework begs for clarity in its purpose. By drawing a line between your app and your framework you have to start thinking clearly about what belongs where. 

Don't expect to nail the framework's "purpose" in the first pass. Your framework will evolve as ZEN drives it. Over time, though, clarity will emerge and you will have a new, powerful tool, codified in your framework, but also in your mental toolbox for solving and thinking about programming problems.

Writing Frameworks is Hard - and Worthwhile

I don't want to make this seem easy. Writing the best of all possible modules is hard! However, it is a learnable skill. You are only going to learn a skill be practicing it - a lot.

And what about ZEN? Writing frameworks and ZEN are not in conflict. You can write frameworks while observing ZEN. After all, DHH, one of the strongest proponents of ZEN, wrote Ruby on Rails.


  1. I measure codebase size in parse tokens rather than lines of code. Though still only an approximate measure, they are much better than LOC. They are the smallest meaningful unit in code. LOC measures several aspects of code which are ignored by the compiler including comments and whitespace.
  2. Codebase complexity can be understood in terms of graph-theory. Complexity comes from the number of possible interactions within the code. In the worst case, if you have N bits of code (tokens), you can have as many as N * (N - 1) or roughly N2 possible interactions. In practice the relationship between code-size and code-complexity is somewhere between O(Nk>1) < CodeComplexity(N) < O(N2).
    Modular design is all about reducing the number of interactions a chunk of code has with the rest of the code-base. This is how modules help reduce complexity.
  3. ZEN is roughly the same concept as YAGNI, but unlike the latter, both the word 'zen' and the expansion, 'zero extra nuts' convey meaning. We can say some code needs to be more 'zen,' and others will understand. To say code needs to be more 'yagni' holds no meaning for most people.