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Master selection and implementation of data structures. Learn when to use arrays, lists, trees, graphs, heaps, and hash tables for optimal performance.

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SKILL.md

name data-structures
description Master selection and implementation of data structures. Learn when to use arrays, lists, trees, graphs, heaps, and hash tables for optimal performance.
sasmp_version 1.3.0
bonded_agent 03-data-structures-expert
bond_type PRIMARY_BOND

Data Structures Skill

Skill Metadata

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