What are the three problem-solving strategies: Fractionalization, Hypothesis Testing, and Means-End Analysis (MEA)?

Fractionalization splits a problem into solvable parts; hypothesis testing proposes a cause and then tries to disprove it; means-end analysis repeatedly closes the biggest gap between the current state and the goal.

1. Fractionalization (Divide & Conquer)

• Break a large problem into smaller, manageable sub-problems
• Solve each sub-problem independently
• Combine solutions to address the whole
• Example: Analyzing a security breach → separate into: how did they get in? What did they access? How do we contain it? How do we prevent recurrence?

2. Hypothesis Testing

• Formulate a hypothesis about the cause or solution
• Design tests to confirm or refute it
• Iterate based on results
• Example: "The breach likely came through the VPN" → check VPN logs → confirmed/denied → form new hypothesis if needed
• Key: Be willing to disprove your own hypothesis

3. Means-End Analysis (MEA)

• Compare the current state with the desired end state
• Identify the biggest difference between them
• Apply an action to reduce that difference
• Repeat until current state = goal state
• Frequently used in AI (Wikipedia: Means-ends analysis)
• Example: Current state: "system is compromised." Goal: "system is secure and operational." Biggest gap: "attacker still has access." Action: "isolate affected systems."

Tip: These three strategies are complementary — you might fractionalize a problem, form hypotheses about each piece, and use MEA to prioritize which gaps to close first.