Piye cara milih struktur data sing tepat kanggo masalah?

Question

Accepted Answer

Pilih struktur sing **operasi paling asring paling murah** kanggo pola akses mu. Mulai kanthi nglista operasi sing bakal kowe lakukan, takokake frekuensine, banjur cocokkake karo kaluwihan struktur.

## Daftar periksa keputusan

```text
1. How do you access data?  by index -> array
                            by key   -> hash map
                            by order -> tree / heap
2. Need ordering?           sorted   -> balanced BST / sorted array
                            FIFO     -> queue
                            LIFO     -> stack
3. Frequent middle inserts? -> linked list
4. Need fast "seen it?"     -> set / hash map
5. Need "best/min/max next" -> heap (priority queue)
```

## Cocokkan operasi karo komplesitas

| Butuh | Struktur terbaik | Biaya operasi utama |
|---|---|---|
| Akses acak dening indeks | array dinamis | O(1) |
| Panggonan dening kunci | hash map | O(1) rata-rata |
| Diurutake + inquiry jangkauan | BST seimbang | O(log n) |
| Min/maksimal berulang | heap | O(log n) pop |
| FIFO / LIFO | antrian / tumpukan | O(1) |
| Panggonan awalan | trie | O(L) |

## Conto penalaran

```text
"Find the 10 most frequent words in a huge file."
 - count frequencies  -> hash map (O(1) updates)
 - keep top 10        -> min-heap of size 10 (O(log 10) per word)
```

## Mengapa iku penting

Nilih kanthi bener asring minangka bedane antarane solusi O(n) lan O(n²) — pengungkit tunggal paling besar ing performance.

Pang-interview nguji tepat penalaran iki: pengin ndeleng carane kowe petakan kebutuhan menyang biaya operasi, ora ngapal struktur.

Butuh	Struktur terbaik	Biaya operasi utama
Akses acak dening indeks	array dinamis	O(1)
Panggonan dening kunci	hash map	O(1) rata-rata
Diurutake + inquiry jangkauan	BST seimbang	O(log n)
Min/maksimal berulang	heap	O(log n) pop
FIFO / LIFO	antrian / tumpukan	O(1)
Panggonan awalan	trie	O(L)