375 lines
10 KiB
Markdown
375 lines
10 KiB
Markdown
# Algorithm Learning Plan
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## Overview
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This plan provides a structured approach to learning algorithms from basic to advanced levels, organized by classes of algorithmic tasks with progressive difficulty within each class.
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## Learning Classes (Simple to Complex)
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### Phase 1: Foundations (Weeks 1-4)
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**Focus**: Basic data structures and simple patterns
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#### Class 1: Array & Sequence Manipulation
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**Concept**: Basic array operations and linear patterns
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**Existing Algorithms**:
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- `twoSum` - Two pointers pattern
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- `maxArea` - Two pointers with area calculation
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- `sortedSquares` - Array transformation with two pointers
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- `intersection` - Array intersection (sorted)
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- `maxSum` - Maximum subarray (Kadane's algorithm)
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- `missingNumber` - Mathematical array analysis
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- `binarySearch` - Classic search algorithm
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- `toGetClosestPoint` - Distance-based search
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**Progression**:
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1. **Week 1**: Basic array traversal and simple patterns
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- Linear search, basic array operations
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- Simple frequency counting
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- Array transformation basics
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2. **Week 2**: Two pointers fundamentals
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- Sorted array operations
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- Basic two sum variations
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- Container problems (max area)
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3. **Week 3**: Binary search mastery
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- Classic binary search
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- Rotated array search
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- Search space problems
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4. **Week 4**: Prefix sums and basic patterns
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- Range queries
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- Subarray problems
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- Mathematical analysis
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#### Class 2: String Manipulation
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**Concept**: String processing and pattern matching
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**Existing Algorithms**:
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- `isIsomorphic` - Character mapping patterns
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- `isPalindrome` - String reversal and comparison
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- `backspaceCompare` - Stack-based string processing
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- `compress` - String compression algorithms
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**Progression**:
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1. **Week 5**: Basic string operations
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- Character counting
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- Simple pattern matching
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- String manipulation basics
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2. **Week 6**: Advanced string patterns
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- Isomorphic strings
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- Palindrome variations
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- Stack-based processing
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### Phase 2: Intermediate Patterns (Weeks 5-8)
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**Focus**: Common algorithmic patterns and data structures
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#### Class 3: Hash Tables & Dictionary Patterns
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**Concept**: Hash-based solutions and frequency counting
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**Future Topics**:
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- Frequency counting
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- Two-sum with hash maps
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- Grouping problems
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- Cache implementations
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**Progression**:
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1. **Week 7**: Hash map fundamentals
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- Basic frequency counting
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- Lookup optimization
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- Two-sum hash approach
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2. **Week 8**: Advanced hash patterns
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- Grouping and categorization
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- Multiple data structure combinations
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- LRU cache patterns
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#### Class 4: Data Structure Validation
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**Concept**: Validating complex data structures
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**Existing Algorithms**:
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- `isValidSudoku` - Grid validation with sets
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- `isDevided11` - Mathematical validation
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- `buildTonalnost` - Structure building
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**Progression**:
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1. **Week 9**: Grid and matrix validation
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- Sudoku solving patterns
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- Matrix traversal
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- Constraint satisfaction
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2. **Week 10**: Mathematical and structural validation
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- Number theory applications
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- Tree/graph validation
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- Complex constraint problems
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### Phase 3: Advanced Patterns (Weeks 9-12)
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**Focus**: More complex algorithms and optimization
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#### Class 5: Dynamic Programming Basics
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**Concept**: Optimal substructure and memoization
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**Future Topics**:
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- Fibonacci patterns
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- Knapsack problems
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- Longest common subsequence
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- Pathfinding in grids
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**Progression**:
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1. **Week 11**: 1D Dynamic Programming
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- Fibonacci sequence
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- Climbing stairs
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- House robber problem
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2. **Week 12**: 2D Dynamic Programming
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- Longest common subsequence
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- Grid path problems
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- Interval DP
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### Phase 4: Advanced Topics (Weeks 13-16)
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**Focus**: Complex algorithms and real-world applications
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#### Class 6: Graph Algorithms
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**Future Topics**:
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- BFS and DFS traversal
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- Connected components
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- Shortest path algorithms
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- Topological sorting
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#### Class 7: Tree Algorithms
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**Future Topics**:
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- Binary tree operations
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- Tree traversal patterns
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- BST operations
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- Tree balancing concepts
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## Weekly Structure
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### Daily Practice Routine (30-60 minutes/day)
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```
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Day 1-2: Learn new concept + 1-2 basic problems
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Day 3-4: Medium difficulty problems with concept
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Day 5: Review + advanced problem
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Day 6-7: Mixed practice + pattern recognition
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```
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### Weekly Progress Tracking
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- **Monday**: New concept introduction
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- **Tuesday**: Basic practice (2 problems)
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- **Wednesday**: Medium practice (2 problems)
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- **Thursday**: Advanced practice (1 problem)
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- **Friday**: Review and consolidation
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- **Saturday**: Mixed practice (2-3 problems)
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- **Sunday**: Rest or catch-up
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## Problem Categories Mapping
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### Category 1: Array & String (Beginner)
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- **Pattern**: Two Pointers, Sliding Window
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- **Complexity**: O(n), O(n²)
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- **Problems**: twoSum, maxArea, sortedSquares, isPalindrome
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- **LeetCode Practice**: Easy level (1-2 per day)
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### Category 2: Hash Tables (Beginner-Intermediate)
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- **Pattern**: Frequency Counting, Lookup Optimization
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- **Complexity**: O(n) average, O(n²) worst
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- **Problems**: TwoSum variations, frequency counting
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- **LeetCode Practice**: Easy-Medium (1-2 per day)
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### Category 3: Binary Search (Intermediate)
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- **Pattern**: Divide and Conquer, Search Space
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- **Complexity**: O(log n)
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- **Problems**: BinarySearch, rotated array search
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- **LeetCode Practice**: Medium (1 per day)
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### Category 4: Dynamic Programming (Advanced)
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- **Pattern**: Optimal Substructure, Memoization
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- **Complexity**: O(n²), O(n³)
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- **Problems**: Fibonacci, knapsack, LCS
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- **LeetCode Practice**: Medium-Hard (1 every 2 days)
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### Category 5: Graph & Tree (Advanced)
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- **Pattern**: Traversal, Path Finding
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- **Complexity**: O(V+E), O(V²)
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- **Problems**: BFS/DFS, shortest path
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- **LeetCode Practice**: Medium-Hard (1 every 2 days)
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## Progress Tracking System
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### Progress Dashboard
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Create a `docs/progress.md` file to track:
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```markdown
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# Algorithm Learning Progress
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## Phase 1: Foundations (Weeks 1-4)
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- [ ] Week 1: Array basics completed
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- [ ] Week 2: Two pointers mastered
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- [ ] Week 3: Binary search mastered
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- [ ] Week 4: Prefix sums completed
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## Phase 2: Intermediate Patterns (Weeks 5-8)
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- [ ] Week 5: String patterns mastered
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- [ ] Week 6: Advanced string patterns
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- [ ] Week 7: Hash map fundamentals
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- [ ] Week 8: Advanced hash patterns
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## Problem Solving Stats
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- Total problems solved: 0
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- Easy problems: 0
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- Medium problems: 0
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- Hard problems: 0
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- Success rate: 0%
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## Skill Assessment
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- Array manipulation: ⭐⭐⭐⭐⭐
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- String processing: ⭐⭐⭐⭐⭐
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- Binary search: ⭐⭐⭐⭐⭐
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- Dynamic programming: ⭐⭐⭐⭐⭐
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- Graph algorithms: ⭐⭐⭐⭐⭐
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```
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### Daily Practice Log
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Create `docs/daily-practice.md`:
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```markdown
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# Daily Practice Log
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## 2026-05-17
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**Today's Focus**: Two pointers pattern
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**Problems Solved**:
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1. twoSum - Easy ✅
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2. maxArea - Medium ✅
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**Learning Points**:
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- Two pointers work well on sorted arrays
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- Time complexity: O(n), Space complexity: O(1)
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**Next Steps**: Practice more two pointer variations
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```
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## Documentation Structure
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### Phase 1: Documentation Foundation
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Create `docs/` directory with:
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1. **`docs/01-foundations/`**
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- `array-basics.md` - Basic array operations
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- `two-pointers.md` - Two pointers patterns
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- `binary-search.md` - Binary search variations
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- `prefix-sums.md` - Prefix sum techniques
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2. **`docs/02-strings/`**
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- `string-basics.md` - Basic string operations
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- `palindrome.md` - Palindrome patterns
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- `isomorphic.md` - Character mapping
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- `stack-strings.md` - Stack-based processing
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3. **`docs/03-hash-tables/`**
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- `hash-basics.md` - Hash map fundamentals
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- `frequency-counting.md` - Frequency patterns
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- `two-sum-hash.md` - Hash-based two sum
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### Phase 2: Advanced Documentation
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4. **`docs/04-dynamic-programming/`**
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- `1d-dp.md` - One-dimensional DP
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- `2d-dp.md` - Two-dimensional DP
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- `knapsack.md` - Knapsack problems
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5. **`docs/05-graphs-trees/`**
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- `bfs-dfs.md` - Graph traversal
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- `shortest-path.md` - Shortest path algorithms
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- `tree-basics.md` - Tree operations
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## Daily Practice Integration
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### LeetCode Integration Strategy
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1. **Theme Days**: Focus on specific problem types
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- Monday: Array problems
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- Tuesday: String problems
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- Wednesday: Hash table problems
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- Thursday: Binary search
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- Friday: Dynamic programming
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- Saturday: Mixed practice
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- Sunday: Review/weak areas
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2. **Difficulty Progression**:
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- Week 1-2: Easy problems only
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- Week 3-4: Easy + Medium
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- Week 5-8: Medium focus
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- Week 9-12: Medium + Hard
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- Week 13-16: Hard focus
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3. **External Problem Sources**:
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- LeetCode "Explore" section
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- LeetCode "Top Interview Questions"
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- HackerRank practice sets
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- Codeforces beginner problems
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### Practice Workflow
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1. **Problem Analysis**: 5-10 minutes
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- Understand constraints
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- Identify patterns
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- Plan approach
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2. **Implementation**: 20-30 minutes
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- Write clean code
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- Add comments
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- Handle edge cases
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3. **Review**: 5-10 minutes
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- Compare with solutions
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- Learn new approaches
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- Update documentation
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## Assessment Metrics
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### Weekly Assessment
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- **Problems Solved**: Target 7-10 problems per week
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- **Success Rate**: Aim for 80%+ success rate
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- **Pattern Recognition**: Can identify patterns in new problems
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- **Time Management**: Solve medium problems in <20 minutes
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### Monthly Review
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- **Progress Tracking**: Update progress dashboard
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- **Weak Areas**: Identify and focus on difficult topics
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- **Strengths**: Reinforce strong areas
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- **Next Goals**: Set monthly objectives
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## Timeline Adjustments
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### Fast Track (12 weeks)
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- Combine similar topics
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- Focus on interview patterns
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- 2-3 problems per day
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- Weekly mock interviews
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### Comprehensive Track (24 weeks)
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- Deep understanding focus
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- Real-world code connections
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- 1-2 problems per day
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- Implementation from scratch
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### Flexible Adjustments
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- **Behind Schedule**: Add 1-2 extra days per topic
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- **Ahead Schedule**: Move to advanced topics
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- **Stuck**: Review fundamentals, add more practice
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## Success Criteria
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### Short-term (1 month)
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- Complete Phase 1: Foundations
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- Solve 30+ problems
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- Master basic patterns
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- Document learning journey
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### Medium-term (3 months)
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- Complete Phase 2: Intermediate Patterns
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- Solve 100+ problems
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- Implement major algorithms from scratch
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- Build intuition for pattern recognition
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### Long-term (6 months)
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- Complete all phases
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- Solve 200+ problems
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- Teach others the patterns
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- Contribute to open source algorithms
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---
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**Note**: This plan is flexible and should be adjusted based on individual progress, learning style, and goals. Regular self-assessment ensures the plan remains effective and engaging. |