How Meta Automates Dead Code Cleanup

🌙 Hello world ☀️ 

I'm traveling this week, so this issue will be shorter. We’ll be back in full swing next week 😎 

In this week’s email:

  • Data Infrastructure: Learn how Meta’s Systematic Code and Asset Removal Framework (SCARF) automatically identifies and removes dead code.

  • Next.js/Remix: Kent’s thoughts on why he prefers Remix for its simplicity and flexibility, cautioning against Next.js’s complexity and urging clearer distinctions in the React community.

  • Node.js: Matteo’s guide on boosting Node.js API performance with Platformatic DB, emphasizing automated CRUD creation, multi-database support, and efficient caching, tested using Autocannon.

  • Career Development: Why aspiring senior software engineers should focus on data modeling, asynchronous systems, and cloud technologies.

Simplicity is prerequisite for reliability.

Edsger W. Dijkstra

Created with Midjourney

Meta's Systematic Code and Asset Removal Framework (SCARF) plays a critical role in automating dead code cleanup by utilizing a mix of static and dynamic program analysis.

The framework is designed to identify redundant code from both a business and programming language standpoint, subsequently generating change requests to delete the identified dead code, thus reducing the burden on developers.

Dead Code Removal Process
SCARF encompasses a subsystem specifically tailored for automatic dead code identification and removal, employing static, runtime, and application analysis to achieve this.

SCARF’s Code Analysis Subsystem

The process involves gathering comprehensive data from various sources to construct an augmented dependency graph, which serves as the foundation for identifying unreachable code segments that can be safely removed.

The framework is versatile, supporting multiple programming languages and operating at a symbol level for more precise analysis and cleanup. This approach not only enhances the quality of the systems but also facilitates the removal of unused data by resolving dead code references to data assets.

SCARF’s Automated Code Change Requests

Results

  • SCARF has significantly improved system quality and efficiency, automating the removal of over 100 million lines of code through more than 370,000 change requests.

  • The framework supports a wide range of programming languages, ensuring comprehensive dead code removal across different parts of the system.

  • Despite its effectiveness, SCARF does not provide a complete solution for shutting down deprecated products, highlighting an ongoing need for improvements in integration across various languages, systems, and frameworks.

  • The team emphasizes a cautious approach, implementing additional safety mechanisms like textual references search through the BigGrep system to prevent accidental deletions.

  • Engineers play a vital role in the deprecation process, often opting to manually delete code for faster turnaround times, showcasing a balance between automated and manual efforts in dead code removal.

P.S. If you’re enjoying the content of this newsletter, please share it with your network: https://www.fullstackexpress.io/subscribe

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Kent C. Dodds advocates for using Remix over Next.js due to its direct use of web platform APIs, enhancing transferable skills, its flexibility to deploy anywhere, and its commitment to stability and simplicity. He expresses concerns about Next.js’s increasing complexity, potential “magic” that could surprise developers, and the marketing of experimental features as stable. He calls for a clearer distinction between Next.js and React, and a more collaborative approach in the React community.

DATA STRUCTURES & ALGORITHMS
Binary Search

Missed the solutions to this week’s coding workout?

Learn the algorithm used to solve this problem here.

Created with Midjourney

In this guide, backend developers are introduced to Platformatic DB, a tool that enhances Node.js API performance by automating CRUD API creation and supporting multiple databases. The importance of caching for API optimization is emphasized, with async-cache-dedupe highlighted as an effective solution for data storage and rapid retrieval, reducing latency and saving bandwidth. The article also introduces Autocannon, an HTTP/1.1 benchmarking tool, for testing the efficiency of the optimizations made.

Created with Midjourney

Caleb shares his knowledge on how to work towards senior software engineering positions. To thrive as a senior software engineer, mastering skills in data modeling, asynchronous systems, autoscaling, cloud technologies, caching, and ensuring concurrency and idempotency in distributed systems is crucial, as these areas are often scrutinized in technical interviews and essential for handling complex technical challenges.

JAVASCRIPT ECOSYSTEM
JS Weekly Pulse

  • 🚀 Next.js 14 - Speed improvements with Turbopack, Server Actions (stable), Partial Prerendering (preview), and Next.js Learn.

  • 🚀 Astro 3.4 - Page partials, image optimization performance, and dev overlay (experimental).

RECOMMENDATIONS
To-Do List

 Join: Game Off 2023 will take place from November 1 to December 1. Join GitHub’s annual game jam challenge!

 Learn: Pushing Discord’s limits with more than a million online users in a single server.

 Watch: Stephen Cooper of Ag-Grid demonstrates different techniques to optimize performance in React.

 Listen: On the Software Engineering Unlocked podcast, Abi Noda explains how to measure developer experience and why a good developer experience matters.

COMMUNITY SPOTLIGHT
Hot Picks in the Dev Community

Release Please Action - Google’s Github action for automating releases based on conventional commits.

Fnm - Fast and simple Node.js version manager, built in Rust.

Ungit - The easiest way to use git, anywhere, on any platform.

JSX Email - React components and helpers for building responsive email templates.

Metallic - A powerful web proxy built for speed and customization.

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