In software engineering, we often hear terms like “stability,” but context is everything. There's a subtle yet important distinction between language stability and program stability, and confusing the two leads to flawed arguments, misguided tool choices, and bad engineering tradeoffs.
Let’s clarify what each really means.
Program Stability: How well your code behaves
Program stability is about runtime behavior. It answers questions like:
- Does it crash?
- Does it leak memory?
- Does it handle edge cases gracefully?
- Does it behave the same under load, or across environments?
In this realm, concepts like memory safety, race condition avoidance, and error handling robustness come into play.
Tools like valgrind, sanitizers, fuzzers, and even type systems can help catch bugs within the program, regardless of what language it’s written in.
Language Stability: How stable the language definition and ecosystem are
Language stability, on the other hand, is about the evolution of the language itself — its specification, standard library, syntax, and semantic guarantees. It’s about whether:
- Your code will still compile in five years
- The core libraries will remain compatible
- The language’s behavior is well-defined and predictable
- The ecosystem doesn’t churn underneath you
For example:
- C is a very stable language — it hasn’t changed much in decades
- Rust is relatively stable now, but it had a long evolution of breaking changes before reaching 1.0
- Python has had controversial shifts (hello
2 → 3) that affected its perceived language stability
Where People Go Wrong
Sometimes, people blame the language when their program behaves badly.
Example:
"Rust is more stable than C because it's memory safe."
This conflates program-level safety with language-level stability. C is unstable at runtime if misused, yes — but as a language, C is extremely stable. Rust is safer for the programmer, but you still need to track evolving idioms, compiler versions, and crates.
Why This Distinction Matters
If you’re evaluating tools, or building infrastructure for the long term, you need to ask:
- Do I need runtime safety? → focus on program stability
- Do I need a mature, predictable language/toolchain? → focus on language stability
Knowing which dimension you care about prevents cargo-culting and overengineering.
Closing Thoughts
In a perfect world, we want both: a stable language that supports building stable programs.
But when those two diverge, be clear about what you're optimizing for. Not all breakage is caused by the language. And not all language guarantees will save you from writing unstable code.
Stability is multidimensional — treat it that way.
Good To Read:
Memory Safety Isn’t Just Rust: A Serious Look at GC
Programming Language Switching Economics
