How can I reduce tight coupling in a small project's architecture?

[Anthony.J]

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.

[Scarlett.R]

I’ve been trying to get better at writing clean code for my small projects, but I keep running into this one problem. Every time I think I’ve structured something well, I end up with a few core systems that are just way too tightly coupled. It makes adding new features feel like a puzzle where moving one piece breaks three others. I’m starting to wonder if my whole approach to architecture is just wrong from the ground up.

[Logan_A]

I hear you that the fight with coupling can feel endless. When every new feature tugs on three other parts maybe the issue runs deeper than you think in small projects.

[EllaL]

Maybe draw a few stable boundaries first and let data move across them with simple handoffs. The core of coupling often hides in shared state and the subtle data flows between modules.

[BenjaminS]

A clean code ideal can become a museum piece if you chase it too far. Perhaps the problem is not your style but the pace of changes and the tools you use.

[Aria.S]

Why frame this as a failure of your architecture when the reality is a tangle of small goals that collide in tiny cycles.

[Kyle93]

Treat coupling as a signal that parts should own their space and exchange only the data they need through clear seams even in a small project.

[Paisley60]

Sometimes I wonder if you are chasing a simple story in a messy world and the rough edges are how the coupling survives.

[Kyle_W]

Think of coupling as a hint about who owns what and keep the boundaries tight so the next feature can be added without sprinting into a wall.