C++ still lacks switch on strings

Birch Grove is just 40 minutes from Bishkek. Although I was concerned about the strong, foggy weather, it was an amazing opportunity for photography!

C++ is a powerful language, and I genuinely love it, but sometimes, even in modern versions, it lacks some surprisingly simple features. One such missing feature is switch on std::string. You’d think that by now, we could use a switch statement on strings just like we do with integers or enums—after all, Go has it! But no, C++ keeps us on our toes.

Why Doesn’t C++ Support switch on strings? Because “you only pay for what you use,” which is the standard C++ mantra. The switch statement in C++ relies on integral types. Under the hood, it works by converting the case values into jump table indices for efficient execution. But std::string (or even std::string_view) is not an integral type—it’s a more complex data structure. That’s why you can’t simply do:
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AI, Software Engineering, and the Evolution of Code Generation

From a weekend trip to a nearby gorge. Why is it here? Because I love the mountains of Kyrgyzstan!

Mark Zuckerberg recently made a bold statement: AI will soon take over the work of mid-level engineers (Forbes). While this may sound like another tech CEO hyping AI, my latest experience with OpenAI’s o3-mini-high model suggests he might not be too far off.

Thanks to DeepSeek, OpenAI was compelled to make o3-mini-high available in a regular ChatGPT subscription instead of locking it behind a steep $200 paywall. I would never pay original $200 for a model, but since I already have the regular ChatGPT subscription, it was an obvious choice to try it out. With this in mind, I decided to experiment: Could o3-mini-high generate a functional Go codebase for my GFSM library?

The experiment

For context, GFSM is my Go Finite State Machine library, and I needed a new generator to extract and save state machines in formats like PlantUML and Mermaid. Writing such a generator requires a solid understanding of Go’s Abstract Syntax Tree (AST) package, something I hadn’t used in years.
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How to compile C++ in 2025. Bazel or CMake?

Today, we’re examining two modern build systems for C++: CMake, the industry favorite, and Bazel, a powerful alternative. While CMake is often the default choice, I believe that approach warrants a bit more scrutiny—after all, we’re focusing on modern tools here (yep, not counting Make, right?). To explore this, I’ve created a practical demo project showcasing how both systems manage a real-world scenario.

Using the maelstrom-challenges project as a starting point, I’ve extracted a C++ library called maelstrom-node. This library has been set up to work seamlessly with both Bazel and CMake, giving us a hands-on comparison of their approaches, strengths, and quirks.

The Project Structure

Here’s what the final directory layout for maelstrom-node looks like:

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Managing Multi-Language Projects with Bazel

In today’s software development landscape, it’s rare to encounter a project built with just one programming language or platform. Modern applications often require integrating multiple technologies to meet diverse requirements. This complexity is both a challenge and an opportunity, demanding robust tools to manage dependencies, builds, and integrations seamlessly. Bazel, a powerful build system, is one such tool that has proven invaluable for multi-language projects.

Recently, I decided to extend my Maelstrom challenges with a C++-based test to explore how Bazel can simplify managing multi-language dependencies and streamline development workflows.

Why Bazel for Multi-Language Projects?

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Bazel and Rust: A Perfect Match for Scalable Development

Bazel never fails to impress, and its support for Rust demonstrates its versatility and commitment to modern development. Two distinct dependency management modes—Cargo—based and pure Bazel—allow developers to tailor workflows to their projects’ needs. This adaptability is particularly valuable for integrating Rust applications into monorepos or scaling complex systems.
I decided to explore how Bazel supports Rust, including managing dependencies, migrating from Cargo.toml to BUILD.bazel, and streamlining integration testing.
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Returning to Rust: A Journey Through Tooling, Performance

When I started tackling the Maelstrom challenges, my initial thought was to use C++. It’s a language I know inside out, and its performance is hard to beat. However, as I contemplated setting up the project, I realized I couldn’t justify fighting with the C++ pipeline for free. Crafting a proper CMake or Bazel configuration might be worthwhile for large-scale projects or when compensated, but for personal experiments? It’s an unnecessary headache.

Why Go is My Default Choice

For most non-performance critical scenarios, Go is my default, no-brainer choice. It has a clean build system, excellent tooling, and a developer experience that doesn’t make me dread the setup process. Go’s simplicity allows me (and any level team) to focus on solving the problem rather than wrestling with the environment. Yet, this time, I decided to take a different path.
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Minimal CI for Go library with GitHub actions

Continuous Integration (CI) has become an essential part of modern software development, and for good reason. It ensures code quality, speeds up development, and catches potential issues early. However, you can get started without an elaborate CI setup. Even a minimal CI setup can significantly improve your workflow. Here’s why every project should have at least minimal CI and how to implement it effectively using GitHub Actions.

What Constitutes Minimal CI?

For a project to benefit from CI without excessive complexity, it should include the following essential components:

1. Project Compilation: Verify that the codebase is always in a buildable state.
2. Unit Test Execution: Ensure the core functionality works as expected.
3. Static Code Analysis: Catch bugs and enforce coding standards before they become an issue.

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GFSM: A Simple and Fast Finite State Machine for Go

Design patterns are not widely used in Go, as they can often lead to unnecessary complexity in the codebase. However, the Finite State Machine (FSM) is an exception that proves to be incredibly useful. When I set out to design GFSM, I aimed to create a fast and straightforward FSM implementation for Go.

I initially sought a quick and straightforward FSM solution for Go, but I couldn’t find anything that met my needs. Drawing inspiration from the speed-focused and minimalistic principles of C++ while remaining true to Go’s idioms, I developed GFSM to fill this gap. The outcome is GFSM—a library that distinguishes itself from alternatives like looplab/fsm by prioritizing speed and simplicity.

Whether orchestrating microservices, handling distributed systems, or designing embedded systems, GFSM brings the reliability and efficiency needed to keep things running smoothly.

Real-World Use Case: Two-Phase Commit Protocol

One of the best showcases for FSMs is the Two-Phase Commit protocol (TPC), widely used in distributed systems to ensure atomic transactions. Let’s explore how GFSM can model this protocol step by step.

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Reflections on Reading “Introduction to Reliable and Secure Distributed Programming”

I’ve had Introduction to Reliable and Secure Distributed Programming sitting on my bookshelf for years, silently whispering, “Read me when you have time.” Of course, “later” always seemed like the right time. As software developers, we often prioritize practical, hands-on books that help solve immediate problems—topics like Kubernetes, Kafka or mastering another layer of C++ intricacies. But in hindsight, neglecting foundational theory is a mistake.

I began my journey with distributed systems over a decade ago. Back then, I wish someone had handed me this book and insisted I dive in immediately. It’s the kind of resource that can help set the foundation for anyone venturing into the complexities of distributed computing. Instead, I learned through trial, error, and practical exposure, which, while valuable, left gaps that only became apparent when I finally picked up this book. Continue reading →

Sabbatical and Distributed Systems

Working at a unicorn company for four years was an exhilarating experience, though incredibly exhausting. Tackling significant projects that few have ever attempted means Google can’t offer much help. Surrounded by highly talented colleagues, many of whom you may never encounter again in one place, all while facing a relentless pace and high expectations from leadership, it eventually takes a toll. After a while, you just need to pause, rest, and reflect. That’s why I left Motional—to take several months to recharge, spend time with family, and reconnect with my hobbies.

View from the rooftop of the apartment, where we settled down. I love running up on the left side of the river—quite a nice trail run.

The irony is, after more than 20 years in IT, I’ve become somewhat of a workaholic, so proper rest eludes me. Just last weekend, I found myself speaking at the DevFest ’24 conference, sharing insights on best practices in project development with the local IT community. The event exceeded all my expectations. It’s been incredibly gratifying to see how much Kyrgyzstan’s IT sector has grown since I left in 2003. I sincerely hope this growth continues and that, eventually, talented engineers will want to stay here or return to the country instead of trying themselves outside, as I did. However, I’m also acutely aware that I’m now overqualified for most roles in the Kyrgyz job market, which is a bit bittersweet. So, my journey will likely inevitably take me elsewhere after my sabbatical. Continue reading →