W Code - Pattern-Based DSA Learning Platform

Bhanu Bisht

Template

Greedy Template: Pattern, Code & Cheat Sheet

The Greedy pattern is one of the most frequently tested coding interview patterns. Make locally optimal choices for globally optimal solutions. This template gives you a reusable code skeleton, pseudocode, and implementation in multiple languages so you can solve 13+ problems using this single mental model.

Difficulty: Medium | Time Complexity: O(n log n) | Space Complexity: O(1)

When to Use This Template

Use the Greedy template when you see these signals in a problem:

1.Activity selection — Problems asking to activity selection

2.Job scheduling — Problems asking to job scheduling

3.Huffman coding — Problems asking to huffman coding

Prerequisites: Sorting, Arrays

Problem count on W Code: 13 problems across Easy, Medium, and Hard difficulty levels.

If the problem does not match these signals, consider alternative patterns.

Pseudocode Template

function greedySolve(input):
    // Initialize data structures
    result = initial_value
    
    // Core logic for Greedy
    for each element in input:
        process(element)
        update(result)
    
    return result

Python Implementation

python
def solve(input_data):
    """Greedy solution template."""
    result = []
    # Implement greedy logic here
    for item in input_data:
        # Process each item
        result.append(item)
    return result

Java Implementation

java
public Object solve(Object[] input) {
    // Greedy template
    // Implement core logic here
    return null;
}

C++ Implementation

cpp
auto solve(vector<int>& input) {
    // Greedy template
    // Implement core logic
    return result;
}

Variations & Adaptations

The Greedy pattern has several variations you should master:

Variation 1: Activity Selection

This variation is useful when the problem specifically requires activity selection. Adapt the main template by modifying the core loop/recursion logic accordingly.

Variation 2: Fractional Knapsack

This variation is useful when the problem specifically requires fractional knapsack. Adapt the main template by modifying the core loop/recursion logic accordingly.

Variation 3: Job Scheduling

This variation is useful when the problem specifically requires job scheduling. Adapt the main template by modifying the core loop/recursion logic accordingly.

Variation 4: Huffman Coding

This variation is useful when the problem specifically requires huffman coding. Adapt the main template by modifying the core loop/recursion logic accordingly.

Common Mistakes & Edge Cases

When implementing Greedy, watch out for:

1.Off-by-one errors — Carefully handle boundary conditions in loops

2.Missing base case — Ensure recursion terminates properly

3.Integer overflow — Use appropriate data types for large inputs

4.Empty input — Handle null/empty arrays, strings, or graphs

5.Single element — Test with minimal inputs

Edge cases to always test:

•Empty input → expected output

•Single element → correct result

•All same elements → no infinite loop

•Maximum constraints → within time limit

Step-by-Step Problem Solving Guide

1.Identify the pattern: Does the problem involve Activity selection, Job scheduling, Huffman coding?

2.Choose the template: Select the variation from above that best fits

3.Define variables: Map problem-specific entities to template variables

4.Implement the core logic: Fill in the template skeleton

5.Handle edge cases: Add boundary checks

6.Verify with examples: Trace through sample inputs

7.Analyze complexity: Confirm O(n log n) time and O(1) space

Frequently Asked Questions

What problems can I solve with the Greedy template?

The Greedy template applies to 13+ problems including: Activity selection, Job scheduling, Huffman coding. Look for problems that involve make locally optimal choices for globally optimal solutions..

What is the time complexity of Greedy?

The typical time complexity is O(n log n) with space complexity of O(1). Some variations may differ.

What should I learn before Greedy?

Prerequisites include: Sorting, Arrays. Make sure you are comfortable with these concepts first.

How do I recognize a Greedy problem in an interview?

Key signals: the problem involves activity selection; the problem involves job scheduling; the problem involves huffman coding. Practice identifying these cues by solving at least 10 problems using this pattern.

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