The leaky bucket algorithm provides a constant output rate based on an input, and where the maximum capacity is exceeded, inputs are ignored.
Goal: Implement a leaky bucket algorithm, where you have:
- Maximum capacity (an integer)
- Leak rate as a parameter
Test cases in Scala
Algorithm in Scala
78 lines of Scala (compatible versions 2.13 & 3.0).
We implement several aspects: a LeakyBucket class to contain our state (immutable), as well as a class to describe the leak rate. As a result of the algorithm we also need to implement an extension function `dequeueUpToN`, which allows to dequeue up to `n` values from a Queue (and return 'None' if there are no values at all to dequeue). (this is © from www.scala-algorithms.com)
Scala concepts & Hints
Def Inside Def
A great aspect of Scala is being able to declare functions inside functions, making it possible to reduce repetition.
It is also frequently used in combination with Tail Recursion.
The 'Option' type is used to describe a computation that either has a result or does not. In Scala, you can 'chain' Option processing, combine with lists and other data structures. For example, you can also turn a pattern-match into a function that return an Option, and vice-versa!
Pattern matching in Scala lets you quickly identify what you are looking for in a data, and also extract it.
Stack safety is present where a function cannot crash due to overflowing the limit of number of recursive calls.
This function will work for n = 5, but will not work for n = 2000 (crash with java.lang.StackOverflowError) - however there is a way to fix it :-)
In Scala Algorithms, we try to write the algorithms in a stack-safe way, where possible, so that when you use the algorithms, they will not crash on large inputs. However, stack-safe implementations are often more complex, and in some cases, overly complex, for the task at hand.
In Scala, tail recursion enables you to rewrite a mutable structure such as a while-loop, into an immutable algorithm.