Subset Sum Generation

Generate sums by iterating masks and accumulating chosen weights—brute force for small n before optimizing.

Try this in Python

weights = [2, 3, 5]
sums = set()
for mask in range(1 << len(weights)):
    s = 0
    for i in range(len(weights)):
        if (mask >> i) & 1:
            s += weights[i]
    sums.add(s)
print(sorted(sums))

Key takeaways

• Set avoids duplicate sums when weights repeat conceptually—list may need dedupe.
• Meet-in-the-middle upgrades this when n grows.
• Sort sums for two-pointer follow-ups.