Building an application with a JavaScript-only stack

As I often do when checking out a new platform or language, I have been building a new pure JavaScript implementation of the Game of Life simulation like I did for Java 8.
In this case, my choice fell unto the MEAN stack:

• MongoDB: a general purpose document-oriented (and as such NoSQL) database with support for querying and aggregation.
• Node.js: the famous server-side JavaScript interpreter.
• Express: a framework for providing REST APIs and web pages on top of Node.js.
• AngularJS: one of the popular client-side JavaScript frameworks for building Single Page Applications.

The experience has been quite interesting, as you really get to know a language and its libraries when using it for a project; in a way that no book can force you to do.

Myths

Here are a series of myths I want to dispel after diving into a full stack JavaScript project for a few weeks.
It is true that there is less of a context switch when changing between the server-side and the client-side applications, since you are always writing the same language. However, this seamless transition is limited by several differences:

• different language support: ECMAScript 6 has to be compiled down by tools like Babel to ECMAScript 5 to be compatible with any browser and Node.js version. Polyfills may be needed to try and unify the experience.
• Different libraries: testing frameworks change between server and client, and so does how you build mocks.
• Different frameworks: Angular and Express both have their own ways to express controllers and views.
• Different tools: you install packages for the server-side with Npm but use Bower instead on the client.

The key about productivity is in being opinionated and choose (or have someone choose for you) a single tool for each purpose, without being carried away by the latest fashion. In this case I followed some default choices and trimmed that down to get:

• Mocha and expect(), one of the three flavors of the Chai assertion library, for the server-side.
• Npm and Bower for server-side and client-side.
• wiredep to generate script and CSS tags for the single page to be loaded.
• Grunt as a build and automation tool, wrapping everything else.

One sany way to pick up default and platform idioms is to start from a predefined stack, and you can do so by cloning a template or a generator like Yeoman. If the generator is well-factored, it will give you sane defaults to fill in the gaps such as JsHint and a configuration for it.
Another myth I would like to dispel is callback hell: if you use the ECMAScript 6 construct yield, you can pretty much write synchronously looking code by building an iterator of steps (each step producing a promise whose resolution will be passed in as an input for the next.) There's probably something even more advanced I didn't reach yet in ECMAScript 7. Don't take this as me saying you can write synchronous code in JavaScript (it only looks synchronous), and you definitely have to learn to use well the underlying layers of callbacks and promises before you can grasp what yield is really doing.

Productivity

With a reference to my previous experience in Java, the productivity of the JavaScript stack feels very good in the short term (I only explored that time frame), due to its simple syntax and structures, especially with support for ES6 which removes a lot of boilerplate.
For example, there is no need for Set<Cell> aliveCells = new HashSet<Cell>(); definitions like in Java, as you would write aliveCells = new Set() with purely dynamic typing (suffering the occasional unfortunate consequences of this choice, of course.)
To evaluate productivity and robustness in the long term you would have to build a much larger project, inside a team composed of multiple people.
I found the tight feedback loop of grunt serve was another positive impact on productivity: you can set up a watch on files so that every time you save the Node.js server is restarted, and the current browser page is reloaded. This is accomplished by LiveReload monitoring from the browser side with a WebSocket. Of course once you get the hang of the testing frameworks and their assertions, you're back to the even stricter feedback loop of running tests and have their output in milliseconds.

Conclusions

I'd say you can reach a good productivity in a pure JavaScript environment, even if I am unsure about the pure dynamic typing approach.
You'll have to get opinionated and choose wisely; to not introduce duplicates and clearly assign responsibility to each of this tool so that it's unambiguous that npm should not be used for client-side modules; to take control of your stack, as everything that you install is still only JavaScript code, copied into your project and that you can read to get a feel of what it's doing.
In programming, a feature that seems to consist of just a few lines of code often turns into an engineering project. In very dynamic and immature stacks such as JavaScript, it's even more important to build strong foundations, tools and processes to turn a blob of code into well-factored software.

Hello world in a production environment

An Hello World is a simple program whose only job is to print "Hello, World" on some form of output. The goal of an Hello World is to explain to programmers the syntax of a new language, but also to check that the infrastructure for compiling, interpreting or running the code is set up correctly.

Hello world in testing

The same concept can be used in the context of writing automated tests when you set up the simplest possible unit test:
When running this test with JUnit, you are validating that the environment is able to:

• retrieve a dependency such as the JUnit JARs and their own transitive dependencies
• build your Java code by compiling the test and its imports
• executing the .class files with the correct classpath.

During a workshop that involves Test-Driven Development, I would typically require everyone with a programming environment to have this simple test set up on the day before; this practice avoids having to put together an environment under time pressure. Especially when trying out new languages or frameworks, getting to this starting point can easily waste a lot of otherwise productive time.

In production

This Hello World pattern may not be limited to a development environment, as apparently simple things can get you a lot of mileage when deployed in production. Here are some examples.
The first API I implement in every microservice accessible through HTTP is the /ping API. It returns a 200 OK response with a content type of text/plain, containing just the text pong. Thanks to this API I can set up the first acceptance test for the project, running it in multiple environments such as CI and staging, and getting it to production where I will be able to call this API with curl and check its correct deployment on the whole server fleet.
I once set up an HelloCommand instead, a simple binary able to write a single log line with a custom text to the centralized log server. By deploying this to all environments we were able to test what happens when the target log server is unreachable or slow, checking that these slowndowns are not propagated to log clients. We also could insert a local proxy, buffering logs before sending them through TCP, and manually check the whole path from generating a log to its final collection.
One of the next things I want to add to the infrastructure is a sample Hello World microservice itself, consisting of its own source code repository, testing and deployment pipeline and monitoring.

What do we get out of Hello World

In the Hello World microservice case, having a template to clone greatly lowers the marginal cost of a new microservice, because the new project can easily be duplicated from a minimal definition. Cloning another existing service is a dangerous operation (we all know the problems of copy-and-paste) as you have to distinguish between what is common infrastructure and what is service-specific code that should not be ported to its siblings. By observing the minimal working template, you will also be able to contain the duplication between services as boilerplate will be highly visible:

How is it possible that we need to have a 200-line build file for an Hello World service?!

What's highly visible can be refactored. Given however that your template is not a code generator but a sample service continuously deployed in production, there will be a tight refactoring feedback loop between making a change to deployment or monitoring infrastructure common to all services, and validating it into the production environment. What you definitely want to avoid is to try to reduce duplication between the builds of different services, only to find out that your extracted method break production deployments on the next day when you're on holiday; or optimize one particular project build but discovering that the improvements cannot be ported to other generic services.
Moreover, there is also knowledge sharing in play: explicitly tested and running Hello World can be picked up by the other team members very quickly, to create a new API, a feature, or even a service. With the concept of living documentation, we prefer executable specifications like unit tests and Gherkin scenarios over complex documents; in the same way, we should prefer living and tested software to be used as a template rather than technical documentation which could be outdated two weeks after it has been written.

References

The Ginger Cake pattern by Dan North is a version of Hello World that start from concrete, complex instances to be cloned. I am wary of leaving too much stuff lying around after having duplicated the cake, so I prefer to start from the simplest possible example. The benefits of this choice are higher if the number of instances to be created is large, so it takes some tuning to recognize recurring technical tasks.
Nat Pryce hypothesis on TDD on the system scale pushes for considering immediately monitoring and system management into the APIs it should provide. Hello World examples are one of the lightweight tools that can show you if underlying resources such as CPU, databases are available and if the applicaton as a whole is working correctly; at the same time, isolating you from the complexity of real features and the myriad of ways in which they can fail even on a robust application layer.
Walking skeletons are a tiny implementation of the system that performs a small end-to-end function; they should put together all key architectural components to validate they can be integrated and can run in the target environment. Here I'm arguing for samples tasks that can be helpful to develop similar instances, a much smaller scale including for example single HTTP APIs.

Book review: Java Puzzlers

Java Puzzlers is a nice book on the corner cases of the Java language, taken as an excuse to explain its inner workings. I have read it over the holidays and I found it a nice refresher over the perils of some of Java's features and types.

What you'll learn

A first example of feature under scrutiny is the casting of primitive types to each other (byte, char int), with the related overflows and unintended loss of precision. Getting to one of these conditions can result in an infinite loop, so it's definitely something you want to be able to debug in case it happens.
There are more esotheric corner cases in the book, such as the moment in which i == i returns false; or the problem of initializations of classes and objects not happening in the order you expect.

Method

I don't want to spoil the book, since it's based on trying to run the examples yourself and propose an explanation for the observed behavior. I'd say this scientific method is very effective in keeping the reader engaged, to the point that I finished it in a few days.
To run the puzzles, you work on self-contained .java files provided by the books website; you can actually compile and run them from the terminal as there are no external dependencies.
Incidentally, this isolation also means you're working on the language and in some cases on the standard library; the knowledge you acquire won't be lost after the next release of an MVC framework.
Again, work on the pc and not on a printed book only; in that case, you won't be able to experiment and you will be forced to read solutions instead of try and solving the puzzles yourself.

Argh, Java!

It's easy to fall into another pitfall: bashing the Java language and its libraries. The authors, however, make clear that the goal of the book is just to explain the corner cases of the platform so that programmers can be more productive. Java has been a tremendously successful platform all over the world, the strange behaviors shown here notwithstanding.
Thus instead of saying This language sucks you can actually think If this happens in my production code I will know what to do. The biggest lesson of the book is to keep the code simple, consistent and readable so that there are no ticking time bombs or hidden, open manholes in a dark and stormy night.

Some sample quotes

Clearly, the author of this program didn’t think about the order in which the initialization of the Cache class would take place. Unable to decide between eager and lazy initialization, the author tried to do both, resulting in a big mess. Use either eager initialization or lazy initialization, never both.

the lesson of Puzzle 6: If you can’t tell what a program does by looking at it, it probably doesn’t do what you want. Strive for clarity.

Whenever the libraries provide a method that does what you need, use it [EJ Item 30]. Generally speaking, the libraries provides high-quality solutions requiring a minimum of effort

Conclusions

Some of these pitfalls may be found through testing; some will only be found when the code is heavily exercised in a production environment; some may remain traps never triggered. Yet, having this knowledge will make you able to understand what's happening in those cases instead of just looking for an unpleasant workaround. This is also a recreational book for programmers, so if you're working with Java get to know it with an easy and fun read.