找零问题——Scala实现
deltamaster
posted @ Jul 06, 2014 12:51:20 PM
in Scala
with tags
scala 递归 找零问题 pattern matching decomposition
, 5149 阅读
首先简单描述一下这个经典的找零问题：
已知需要找零的数量，以及可用的硬币面值，求用这些面值的硬币，有多少种方法拼凑出要求的找零数量。
比如要求找零4元，可用的硬币只有1元和2元两种面值，那么所有可能的方案是，[1, 1, 1, 1]、[1, 1, 2]、[2, 2]三种。（不同顺序不作为不同方案）
设计一个函数，接受两个参数：
- money：Int，表示需要拼凑的找零数量。
- coins：List[Int]，所有可用的硬币面值。
简单分析一下这个问题。直观地用递归的思路去考虑，所有可能的方案，就等于以下两部分之和：
- 用一枚某种面值的硬币x后，剩余找零数的找零方案数量；
- 用除了x以外的其他硬币的找零方案数量。
而递归终止条件就是，找零的数量小于或等于0，或者没有硬币可以用了。
def countChange(money: Int, coins: List[Int]): Int = {
if (money < 0) 0
else coins match {
case Nil => if (money == 0) 1 else 0
case x::xs => countChange(money - x, coins) + countChange(money, xs)
}
}
这段代码用到了Scala的Pattern Matching。Nil是空List对象，继承自List，而x::xs则表示一个非空的List，其中x是用来匹配列表的head，而xs则是列表的tail，xs可以匹配任何List，当然也包括Nil。所以这两个case覆盖了所有的情形，要么为空，要么不为空，如果不为空，则将这个列表decompose成构造参数x和xs，供后面的表达式使用。
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