The Exploration Process

Step 1: Understand the Problem

Before exploring solutions, clarify the problem:

• What exactly are we solving?
• What are the constraints?
• What are the requirements?
• What are success criteria?

If problem is unclear, exploring solutions is premature.

Step 2: Generate 2-3 Alternatives

Don't stop at first idea. Generate at least 2 more.

Techniques for generating alternatives:

1. Different data structures:

   • Array vs linked list vs tree vs hash table
   • List vs set vs dictionary

2. Different algorithms:

   • Iterative vs recursive
   • Brute force vs optimized
   • Different algorithmic approaches (sort-based vs hash-based)

3. Different levels of abstraction:

   • Direct implementation vs library
   • Custom code vs existing pattern
   • Simple specific vs generic flexible

4. Different responsibility allocation:

   • One class vs multiple
   • Function vs class
   • Inline vs extracted

5. Different error handling:

   • Exceptions vs return codes
   • Fail fast vs continue with defaults
   • Validate at boundary vs trust callers

For each approach, sketch it in pseudocode or bullet points.

Step 3: Compare Trade-offs

Evaluate each alternative against criteria:

Which criteria matter most for this problem?

Step 4: Pick the Best

Choose based on:

• Requirements (which criteria actually matter)
• Simplicity (default to simplest that meets requirements)
• Long-term maintainability (code is read 10x more than written)

Document why you picked it:

• "Chose approach 2 because performance is critical and measurements show approach 1 is too slow"
• "Chose approach 1 because simplicity matters more than flexibility we don't need yet"

Step 5: Implement

Only after comparing alternatives, implement the chosen approach.

If implementation fights you → return to Step 2. You might have picked wrong alternative.

Quick Reference

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Naming Variables

帮助你为变量选择清晰准确、易维护的命名，提升代码可读性。

Writing Plans

为工程师生成分步实施计划，帮助在陌生代码库中快速落地任务。