# Problem Solving
在現實生活中，我們需要藉由撰寫程式來完成特定任務，而所謂的演算法（Algorithms）可以視為完成特定任務的一系列步驟或過程。那麼該怎麼提昇我們解決問題的能力呢？這裡提出了兩個主要的建議：
- 設計一套針對問題求解的計畫
- 熟悉常見問題的求解套路
關於面對問題時的求解計畫，可以參考 George Polya 所撰寫的 《How To Solve It》 一書。根據該書的內容可以總結出以下策略：
- Understand the Problem
- Explore Concrete Examples
- Break it down
- Solve and Simplify
- Look Back and Refactor
# Understand the Problem
- Can I restate the problem in my own words?
- What are the inputs that go into the problem?
- What are the outputs that should come from the solution to the problem?
- Can the outputs be determined from the inputs? In other words, do I have enough information to solve the problem? (You may not be ablue to answer this question until you set about solving the problem. That's Okay; it's still worth considering the question at this early stage.)
- How should I label the important pieces of data that are a part of the problem?
# Explore Examples
- Start with simple examples
- Progress to more complex examples
- Explore Examples with Empty Inputs
- Explore Examples with Invalid Inputs
# Break it Down
# Solve and Simplify
# Look Back and Refactor
# Frequency Counter
This pattern uses objects or sets to collect values/frequencies of values. This can oftern avoid the need for nested loops or operations with arrays or strings.