JavaScript: Knowing which apps you’re breaking using static analysis

This post was featured in JavaScript Weekly #213.

When you join large projects and fix bugs or build features, you typically rely on senior (in terms of time at the company) engineers to say “don’t forget to test feature X (that you probably didn’t know existed).”

Being new, you have limited knowledge of the entire architecture. Our tools should help fill this gap in knowledge. Our tools should help us traverse and understand large application architectures: the primary reason why I built and continue to work on the Sublime Dependents plugin.

I recently implemented a new feature that allows you to better understand which features or pages would break with a change to a module by showing you which app entry points depend on that module. In this post, I’ll talk about some of the tools and performance considerations that went into building this feature.

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JavaScript: Squeezing performance out of Dependents

I’ve been spending quite a bit of time working on Sublime Dependents: a free, Sublime Text 3 plugin that helps you navigate front-end codebases. The plugin was built for large, production codebases (originally built for use at Bēhance). As such, performance is a priority. In this post, I’ll talk about some performance optimizations (in the context of the plugin but applicable to other node-based, static-analysis tools); expanding on my original post on the tool.
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My talk at the FullStack Conference in London

I was in London in October speaking at the FullStack conference. I gave a talk on using static analysis to give build tools like Grunt, Gulp, and Broccoli the ability to figure out how to generate their own configuration files based on what we’re doing/using as we build front-end applications.

You can find the recording here: https://skillsmatter.com/skillscasts/5776-using-static-analysis-to-give-build-tools-a-brain

You may need to register for SkillsMatter to view the video. It’s free to create an account.

This talk was a more focused version of the talk that I gave in St. Louis earlier this year. Thanks to the SkillsMatter team and NearForm for putting on a great event with an impressive lineup.

Cheers,
Joel

My talk at the Powered by JavaScript conference at Strangeloop 2014

I was in St. Louis in September speaking at the Powered by JavaScript conference. My talk was about reducing boilerplate and avoiding build tool configuration files by extracting a core set of processes into an adaptive tool that generates and maintains your configuration.

The talk touches on the basics of Grunt, Static Analysis, and techniques necessary to precompile preprocessors and auto-bundle your JavaScript applications.

Enjoy!
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Beauty in Code

There is beauty in the thoughts expressed in code; the search for the perfect idioms. A logical poetry.

There is beauty in the product: that which our code has created.

There is beauty in the usability of our code – its API: its language of interaction.

Think, for a moment, about your own code. We write so much of it. Where is the beauty within your career’s corpus?

Connecting the dots on Dollar Cost Averaging

Dollar-cost averaging (DCA) is a popular investing technique whereby you incrementally purchase more shares of the funds in your portfolio: in small amounts on a monthly or quarterly basis. The main idea is to not invest all of your money at once: avoiding big dips in the market right after your purchase. If you only invest a little at a time, you’ll buy more shares when the market is down and fewer shares when the market is up. Sounds like a no-brainer, right? Well, DCA really only makes sense in a few cases.

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Navigating an AMD codebase in Sublime Text using Static Analysis and Node.js

This post was featured in Node Weekly #43.

When you have a large JS codebase that uses the AMD module pattern, like we do at Bēhance, it becomes tedious to perform certain tasks within your editor. This hurts productivity and adds up to wasted developer time in the long term. Here are some of the problems and possible/existing solutions.

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JS: Auto-generate Grunt tasks using Static Analysis

If you’ve been around modern tooling in front-end web development, you’ve likely run into task runners like Grunt and Gulp. Grunt uses a declarative way of defining tasks via a large configuration JavaScript object that gets fed into the Grunt engine. Gulp takes the more programmatic approach, using JS stream-centric code to define tasks. The battle comes down to configuration vs code when comparing Grunt to Gulp, respectively.

Personally, I’d prefer to have no configuration and no code. Ideally, tooling should help me avoid having to write that boilerplate. In this post, I’ll talk about the feasibility of automating front-end build processes and auto-generating Grunt tasks. The ideas are used in an experimental tool called YA that explores solving this problem.

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