Problem Solving Strategy

Don't just write code. Solve the problem first. 1. **Decomposition**: Break a big problem (e.g., 'Build a Game') into small ones ('Draw a square', 'Move it'). 2. **Pattern Recognition**: Have I seen this before? (e.g., 'This is just a loop'). 3. **Abstraction**: Ignore details. Focus on the core logic.

Python
# Big Problem: Calculate Average Grade
# 1. Sum scores (Loop/Sum)
# 2. Count scores (Len)
# 3. Divide

def average(scores):
    return sum(scores) / len(scores)

It's better to have a slow solution that works than a fast one that doesn't. Start with the simplest, most obvious approach. Only optimize if necessary.

Python
# Find duplicates (Brute Force - O(n^2))
for i in list:
  for j in list:
    if i == j and i_idx != j_idx: print(i)

# Optimize later (Hash Set - O(n))
seen = set()
for i in list:
  if i in seen: print(i)
  seen.add(i)

If a problem is too hard, solve a simpler version of it. Can you solve it for 1 item? For an empty list? This is the basis of recursion and efficient algorithms.

Python
def factorial(n):
    # Base Case: The simplest version
    if n == 1: return 1
    # Recursive Step: Solution builds on smaller version
    return n * factorial(n-1)