Two Sides to Every Coin¶
This is my evolving collection of notes on the inherent trade-offs in software engineering. For pretty much every “good” principle or practice, there’s often a challenging flip side that comes with it. Understanding these dualities helps me make better design choices and avoid getting stuck on one-sided thinking.
This is very much a work in progress. I’ll add to it whenever I stumble upon another good example.
The Examples¶
Reuse ⇌ Coupling¶
Reuse is awesome for efficiency and consistency. Why build it again if you don’t have to? But it always brings coupling with it. When you reuse code, you’re now tied to it. Changes in the reused bit can unexpectedly mess with everything that uses it, making independent updates harder. The trick is to manage that coupling, keeping it loose and obvious.
Divide & Conquer ⇌ Compartments / Silos¶
The divide and conquer strategy is brilliant for managing complexity. It breaks down a large, overwhelming problem into smaller, more manageable compartments or modules. Each compartment is designed to be a focused, self-contained solution for its specific part of the bigger problem, by design hiding its internal details and exposing only what’s necessary. This promotes clarity and independent development. The downside is that while beneficial for the individual part, this inherent “black-boxing” can make it harder to get a holistic view of the system’s overall behavior or to optimize across these boundaries. If taken too far without a strong overarching design or integration strategy, these isolated compartments can act like technical silos, where understanding interactions or making system-wide changes becomes difficult because details are deliberately obscured and the scope of each part is strictly limited.
Holistic ⇌ Doing Everything, Everywhere, All at Once¶
Thinking holistically means looking at the whole system and how everything connects. This can prevent narrow thinking and lead to stronger designs. But take it too far, and “holistic” can turn into trying to do everything, everywhere, all at once. That usually means getting stuck in analysis paralysis, drowning in complexity, and never actually finishing anything.
Integrated ⇌ Entangled¶
Integration lets different parts of a system work together smoothly. When done right, it makes for a unified and efficient product. But without clear boundaries and interfaces, integration easily leads to entanglement. Components get so tightly woven together that changing, testing, or replacing one piece becomes a nightmare for everything else.
Best Practice ⇌ We’ve Always Done It Like That¶
A best practice should be a proven, effective method that really works. It should imply continuous improvement. Too often though, “best practice” just means “we’ve always done it like that.” This mindset stops critical thinking, blocks new ideas, and prevents adapting to new tech or needs, turning a good concept into a rigid excuse.
Explicit ⇌ Verbose¶
Being explicit in code and design is generally great for clarity, making intentions clear and reducing guesswork. This helps future you (or someone else) understand things faster. The problem is when being explicit goes overboard and becomes excessive verbosity. Overly wordy code can be harder to read and maintain, ironically burying the clarity you were trying to achieve.
Predictable ⇌ Boring¶
In terms of how a system behaves, predictability is super important. A predictable system is reliable, stable, and easier to troubleshoot. No nasty surprises. On the flip side, from a creative standpoint, predictable results can be a bit boring. They don’t offer new insights or big breakthroughs. But for critical systems, “boring” often means “it just works,” which is exactly what you want.
Mechanical Sympathy ⇌ Leaky Abstraction¶
Mechanical sympathy means really understanding the underlying hardware or system to write super efficient code. It’s about knowing how things actually work at a lower level to squeeze out performance. This often means you’re intentionally dealing with a leaky abstraction. To get those performance gains, you have to peer through or even break the higher-level abstractions that were supposed to hide those details.
Conclusion¶
The pursuit of “good” software engineering often involves navigating these inherent tensions. Rarely is a principle purely beneficial without some form of trade-off or potential downside. Recognizing both sides of the coin allows for more nuanced decision-making, helping us to leverage the strengths of a concept while mitigating its weaknesses. It’s about informed compromise and conscious decision-making, not blind adherence.