I've been working on algorithm problem solving challenges on platforms like LeetCode, and I keep hitting walls with time complexity. My solutions work for small inputs but fail with larger ones due to timeout errors.
Here's an example problem I struggled with: Finding all unique triplets in an array that sum to zero.
My initial brute-force solution:
```python
def threeSum(nums):
result = []
n = len(nums)
for i in range(n):
for j in range(i+1, n):
for k in range(j+1, n):
if nums[i] + nums[j] + nums[k] == 0:
triplet = sorted([nums[i], nums[j], nums[k]])
if triplet not in result:
result.append(triplet)
return result
```
This is O(n³) time complexity and fails with larger arrays. I know I need to optimize it, but I'm struggling with the programming logic help needed to come up with better solutions.
My questions about algorithm problem solving:
1. What's the systematic approach to optimizing algorithms?
2. How do I identify which parts of my code are the performance bottlenecks?
3. Are there common patterns or techniques I should learn first?
4. How much time should I spend trying to optimize before looking at solutions?
I'm looking for coding tutorial recommendations that focus on algorithm optimization rather than just solution implementation. This feels like one of those coding challenges and solutions that requires a different way of thinking about problems.
Also, if anyone has tips for developing better debugging skills for algorithm problems, I'd appreciate it. Sometimes I can tell my solution is slow, but I don't know where to start improving it.
Here's an example problem I struggled with: Finding all unique triplets in an array that sum to zero.
My initial brute-force solution:
```python
def threeSum(nums):
result = []
n = len(nums)
for i in range(n):
for j in range(i+1, n):
for k in range(j+1, n):
if nums[i] + nums[j] + nums[k] == 0:
triplet = sorted([nums[i], nums[j], nums[k]])
if triplet not in result:
result.append(triplet)
return result
```
This is O(n³) time complexity and fails with larger arrays. I know I need to optimize it, but I'm struggling with the programming logic help needed to come up with better solutions.
My questions about algorithm problem solving:
1. What's the systematic approach to optimizing algorithms?
2. How do I identify which parts of my code are the performance bottlenecks?
3. Are there common patterns or techniques I should learn first?
4. How much time should I spend trying to optimize before looking at solutions?
I'm looking for coding tutorial recommendations that focus on algorithm optimization rather than just solution implementation. This feels like one of those coding challenges and solutions that requires a different way of thinking about problems.
Also, if anyone has tips for developing better debugging skills for algorithm problems, I'd appreciate it. Sometimes I can tell my solution is slow, but I don't know where to start improving it.
