What Actually Defines a Stable Software Version?

As a developer, you'll hear these terms often: "stable software," "stable release," or "stable version." Intuitively, it just means you can rely on it. That's not entirely wrong, but when I was new to programming, I didn't truly grasp the technical meaning.

For anyone learning, the initial, simple definition of "it works reliably" is a great starting point. But if you're building systems for the long haul, that definition is incomplete.

Two Definitions of Stability

The intuitive definition is: a stable version of software that works and that you can rely on not to crash.

The technical definition is: a stable version of software where the API will not change unexpectedly in future updates.

A stable version is essentially a guarantee from the developers that the core interface, such as the functions, class names, data structures, and overall architecture you interact with, will remain consistent throughout that version's lifecycle.

This means that if your code works with version 1.0.0, it should also work flawlessly with version 1.0.1, 1.0.2, and 1.1.0. Future updates will focus on bug fixes, security patches, and performance improvements, not on introducing breaking changes that force you to rewrite your existing code.

What I Didn't Understand

My initial misunderstanding was thinking stability was about whether the software was bug-free or not. Similar to how we expect bugs to be present in a beta version. But there was still an upside to this confusion. It helped me avoid the hype cycle, especially with certain JavaScript frameworks.

I remember being hesitant to commit to new versions of certain tools (like early versions of React, Angular, though this is true of many fast-moving frameworks and SDKs). Paradigms would shift rapidly from one version to the next. A key concept I'd mastered one month would be deprecated or replaced the next.

While those frameworks sit at the cutting edge of innovation, they can also be the antithesis of stability. Stability is about long-term commitment. Rapid shifts force users to constantly evolve with the framework, making it difficult to stay on a single version without continual, large-scale upgrades.

The Gold Standard of Stability

A truly stable software version is one you can commit to for a significant amount of time. The classic example of stability is Python 2. Yes, I know many wanted it to die by fire, but it was first released in 2000 and remained active, receiving support and maintenance until its final update in 2020. That's two decades of stability! I really enjoyed being able to pick up old scripts and run them without any fuss.

While I'm not advocating that every tool should last that long, I do think that when we're building APIs or stable software, we should adopt the mindset that this is the last version we'll ever make. This forces us to carefully consider the long-term design of our software. Whenever I see LTS (Long-Term Support) next to an application, I know that the maintainers have committed to supporting, maintaining, and keeping it backward compatible for a defined, extended period.

That's when I know I'm working with both reliable and stable software.

---