Building Visualizers: An Untapped Approach to Understanding Complex Codebases

When developers approach unfamiliar codebases, the conventional wisdom has always been to read documentation, follow code from entry points, and use debuggers. But Jimmy Miller presents a contrarian approach that challenges this consensus: build a visualizer to understand the codebase's inner workings.

Miller's experience mirrors what many developers face - the overwhelming challenge of understanding hundreds of thousands or even millions of lines of code written by countless others. "The biggest shock of my early career was just how much code I needed to read that others wrote," he admits. While the industry has accepted this as part of the job, Miller suggests we've overlooked a powerful learning technique.

His approach centers on five techniques: setting a clear goal, editing randomly, fixing broken things, reading to answer specific questions, and building a visualizer. The last technique is particularly unconventional but proves remarkably effective when applied to complex systems like Next.js's turbopack Rust bundler.

The value of visualization becomes apparent when examining the specific problem Miller investigated: tree shaking not working properly in turbopack. Traditional debugging methods quickly hit a wall with this experimental feature, which involves complex async Rust code and sophisticated build processes.

"After I looked into tree shaking a bit in the codebase, while I started to understand a few things, I've been at this point before," Miller recounts. "Sometimes it is good to go deep. But how much of this codebase do I really understand?"

This is where visualization shines. Rather than getting lost in implementation details, Miller built tools that could show him the flow of data and execution through the system. His first visualizer tracked files and their contents over time, revealing that the PURE annotation was being dropped during scope hoisting. This insight led to the root cause: how BytePos values were being encoded across modules.

The most revealing visualization came when Miller focused on the fundamental unit of turbopack - ValueCells (Vc). These spreadsheet-like cells provide incremental computation, but their interconnected nature makes them difficult to understand through traditional means.

"I've never been able to really understand these things until I can visualize them," Miller explains. His custom visualizer showed pending tasks, cell contents, and dependencies in real-time, transforming an opaque system into something comprehensible.

The implications extend beyond turbopack. Miller's experience reveals a broader pattern: as software systems grow increasingly complex, traditional learning methods become insufficient. Visualization provides a way to see relationships and flows that remain hidden in code alone.

This approach challenges several industry assumptions:

1. That learning a codebase must be a solitary activity
2. That understanding requires reading all relevant code
3. That existing tools are sufficient for understanding complex systems

The visualizer Miller built wasn't polished or production-ready, but that wasn't the point. "Is it perfect? No, would I ship this as a general visualizer? No. Am I happy with the style? Not in the least," he admits. "But already it enables a look into the project I couldn't see before."

His conclusion offers a provocative call to action: "If you've never used tool building as a way to learn a codebase, I highly recommend it." This represents a fundamental shift in how developers might approach unfamiliar codebases - not as problems to be solved through reading, but as systems to be understood through creation.

The article ends with a broader critique of current software development tools: "Our languages, our tools, our processes are all written without ways to live code, without ways to inspect their inner workings." This suggests a future where understanding complex systems might require not just better documentation, but better ways to visualize and interact with code as it executes.

As codebases continue to grow in complexity, Miller's approach offers a compelling alternative to traditional learning methods - one that transforms the process of understanding from a passive activity into an active, creative endeavor.