How I Identify the Right DSA Pattern (Before Writing Any Code)

Source: Dev.to

Introduction

When people ask how to get better at DSA, the advice is usually some version of:

“Practice more problems.”

That’s not wrong. What actually made the biggest difference for me was learning how to identify the pattern early—often before I thought about code at all. Once I got reasonably good at that, the rest of the problem usually unfolded on its own.

Signals to Look For

I don’t mentally engage with the whole story upfront. Instead, I look for a few very specific signals:

1. What kind of input am I given?
2. What’s the constraint on time and space?
3. What exactly is the output asking for?

Those three things eliminate most options very quickly.

Typical cues and associated patterns

• Sorted array + Find a pair/subarray + O(n) expected → two‑pointers or sliding window.
• Problem asks for ranges, mentions cumulative values, wants counts or sums over subarrays → prefix sums and hashing.
• Input size is large and the answer space is monotonic → binary search (often over the answer itself rather than the array).

Invariants

What I pay more attention to is what must stay true as I move through the input. That’s usually the invariant.

Examples of questions to surface the invariant:

• Am I shrinking a search space?
• Am I maintaining a valid window?
• Am I accumulating something monotonically?
• Am I eliminating options as I go?

Once I can articulate the invariant in a sentence, the pattern usually becomes obvious.

Workflow

There’s a specific feeling I’ve learned to trust. If, within the first couple of minutes, I can say the invariant, then I know I’m on the right track—even if I don’t yet know all the edge cases.

• If I can’t say that, I slow down. That’s usually a sign I’m trying to brute‑force my way into insight instead of stepping back.

From thought to code

Earlier, I used to jump into code quickly, which often led to:

• messy logic
• backtracking
• unclear explanations

Now, if I can’t explain the invariant in plain English, I don’t open the editor.

Once the pattern is clear:

• the loop structure is obvious
• pointer‑movement decisions make sense
• complexity is almost self‑evident

The code becomes an implementation detail, not the core work.

Conclusion

This way of thinking—constraints first, invariant second, code last—is what I’m slowly trying to document more systematically. Not as strict rules, but as a way to make DSA feel less random and more structured.

I’ve been indexing patterns and the signals that point to them in one place (indexedcode.com), mostly as a reference for myself. Writing about it here helps me refine that thinking.

In the next post, I want to dig into why difficulty labels (easy/medium/hard) are often misleading, and why they sometimes do more harm than good when you’re learning.

If pattern recognition feels fuzzy right now, that’s normal. And once it clicks, you’ll notice you’re solving problems differently than before: slower at first, much faster in the long run.