solution-space

Solution space analysis systematically explores multiple approaches before committing to a single course of action. It helps teams compare trade-offs across different design levels and perform local-maxima checks to ensure genuine exploration rather than settling for obvious fixes.

List at least three viable candidate approaches across different levels like Band-Aid, Local Optimum, Reframe, and Redesign. Summarize their trade-offs including implementation costs, maintenance burden, and second-order effects to provide a structured recommendation with rationale.

You need to explore multiple candidate solutions when facing complex problem statements requiring risk-analysis. Evaluating different levels of solutions before coding reduces the risk of defending an initial idea and enables better design decisions through structured trade-off comparison.

Perform a local-maxima check after generating solutions across different levels. This ensures genuine exploration by verifying the selected approach is the best overall choice after considering reframes and redesigns, rather than just the nearest optimal solution.

Yes, you can use this to analyze second-order effects and maintenance burden. The evaluation specifically assesses trade-offs and risks for each option, including implementation costs and maintenance burden, to provide a structured recommendation for your reframe approach.

No, solution space exploration requires a clearly stated problem and specified success criteria to anchor evaluation. Without defining these elements first, you cannot effectively evaluate the trade-offs of candidate approaches or provide a structured, rationale-backed recommendation.