After a week of daily LeetCode challenges, patterns in my problem-solving approach have emerged. Like any developer, I have strengths to build on and areas that need work. Let's break down what I've learned about my coding style.
The Good: Strong Analytical Foundation
1. Base Case Detection
One consistent strength has been my ability to spot edge cases quickly. Take the Jump Game challenge - before diving into the main logic, I immediately recognized that a single-element array was a special case that needed handling. This attention to edge cases is crucial in real-world development where handling unexpected inputs can prevent bugs.
2. Problem Decomposition
I believe I have shown a knack for breaking down problems into their core components. In the Stock Trading challenges, I quickly identified the key variables we needed to track. Reviewing comments like "need value for next index, need index for spaces to end" show I'm thinking about the problem's fundamental requirements before coding.
3. Pattern Recognition
Throughout the week, I've demonstrated an ability to spot similarities between problems. Sometimes this led me astray (more on that in "The Bad"), but it shows an understanding of algorithmic patterns that, with refinement, will make me a stronger developer.
The Bad: Complexity Creep
1. Over-Engineering Solutions
My biggest weakness has been making solutions more complex than necessary. In the multiple stock transactions problem, I created an array to store profits when a simple running total would suffice. This tendency to over-complicate solutions is common among developers who are eager to handle all possible scenarios.
2. Rigid Thinking
I often interpret problem constraints too rigidly. In the Jump Game, I saw jump distances as exact requirements rather than maximum values. This highlights a need to think more flexibly about what values represent in different contexts.
3. Variable Overload
There's a pattern of creating more variables than needed and sometimes modifying them in ways that break code flow (like changing loop counters inside the loop). This comes from a good place - wanting to track everything - but often makes solutions harder to understand and maintain.
The Not So Ugly: Clear Path to Improvement
The good news is that these patterns point to clear areas for improvement:
1. Simplification Checklist
Before writing code, I should ask:
Can this solution work with fewer variables?
Am I making any assumptions about fixed values that could be flexible?
Is there a simpler way to track what I need?
2. Solution Refinement Process
After getting a working solution, I should:
Look for variables that could be combined
Check if any arrays or data structures are unnecessary
Consider if loop logic could be simplified
3. Testing Assumptions
When stuck, I should:
Question my interpretation of the problem constraints
Look for more flexible interpretations of values
Consider if I'm over-planning for edge cases
Moving Forward
My self analysis reveals something encouraging: my core problem-solving instincts are solid, but I tend to over-engineer the implementation. This is actually a good position to be in - it's easier to simplify a complex solution than to develop problem-solving intuition from scratch. At least, I hope so...
As I continue my LeetCode journey, I'll focus on:
Trusting my initial problem analysis
Resisting the urge to create extra
Looking for simpler implementations of my solutions
The key is not to change my analytical approach, but to translate that analysis into cleaner, simpler code. Here's to another week of challenges and growth!