data-structures
Master selection and implementation of data structures. Learn when to use arrays, lists, trees, graphs, heaps, and hash tables for optimal performance.
What this skill does
# Data Structures Skill
## Skill Metadata
```yaml
skill_config:
version: "1.0.0"
category: implementation
prerequisites: [cs-foundations]
estimated_time: "6-8 weeks"
difficulty: intermediate
parameter_validation:
structure_type:
type: string
enum: [array, list, tree, heap, hash, graph, trie]
required: true
operation:
type: string
enum: [search, insert, delete, traverse]
retry_config:
max_attempts: 3
backoff_strategy: exponential
initial_delay_ms: 500
observability:
log_level: INFO
metrics: [structure_usage, operation_complexity]
```
---
## Quick Start
Choose the right structure for every problem. Master operations and trade-offs.
### Linear Structures
**Arrays**
- Random access O(1)
- Fixed size
- Cache friendly
- Use: Known size, frequent access
**Linked Lists**
- Dynamic size
- Sequential access O(n)
- Efficient insertion/deletion O(1)
- Types: Singly, doubly, circular
**Stacks**
- LIFO principle
- Push/pop O(1)
- Use: Undo/redo, parenthesis matching, DFS
**Queues**
- FIFO principle
- Enqueue/dequeue O(1)
- Types: Simple, circular, priority, deque
- Use: BFS, job scheduling
### Trees
**Binary Search Trees**
- Ordered storage
- Search/insert/delete O(log n) avg
- Traversals: inorder, preorder, postorder
**Balanced Trees**
- AVL: height-balanced
- Red-Black: color-based balancing
- B-Trees: multi-way
- Guarantee O(log n) operations
**Heaps**
- Min/Max heap property
- Insert/delete O(log n), Build O(n)
- Use: Priority queues, heap sort
### Hash Structures
**Hash Tables**
- Average O(1) operations
- Collision handling: chaining, open addressing
- Load factor matters
---
## Decision Matrix
| Need | Best Structure |
|------|----------------|
| Random access | Array |
| Frequent insertions/deletions | Linked list |
| Min/max element | Heap |
| Ordered traversal | BST |
| Fast lookup | Hash table |
| Prefix matching | Trie |
| Relations | Graph |
---
## Complexity Comparison
| Operation | Array | List | BST | Hash | Heap |
|-----------|-------|------|-----|------|------|
| Search | O(n) | O(n) | O(log n) | O(1) avg | O(n) |
| Insert | O(n) | O(1)* | O(log n) | O(1) avg | O(log n) |
| Delete | O(n) | O(1)* | O(log n) | O(1) avg | O(log n) |
---
## Troubleshooting
| Issue | Root Cause | Resolution |
|-------|------------|------------|
| Hash collision storm | Poor hash function | Improve hash, use chaining |
| Tree degenerates | Sorted insertions | Use balanced tree (AVL/RB) |
| Memory exhaustion | No size limits | Add capacity limits |
| Iterator invalidation | Modify during iteration | Use safe iteration pattern |
---
## Implementation Checklist
- [ ] Dynamic array with resizing
- [ ] Singly/doubly linked list
- [ ] Stack and queue
- [ ] Binary search tree
- [ ] AVL tree or Red-Black tree
- [ ] Hash table
- [ ] Min/max heap
- [ ] Trie
- [ ] Graph (adjacency list)
- [ ] Disjoint set union
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