Java 6 introduced a change in the implementation of the Arrays#sort(Object[]) method that replaced the use of mergesort with insertionsort for small arrays. This design decision is rooted in optimizing performance for particular cases, especially when dealing with small arrays. This article delves into the reasons behind this change, explores the technical details, and provides examples to illustrate why this approach is beneficial.

Understanding Sort Algorithms: Mergesort vs. Insertionsort

Mergesort

Mergesort is a classic divide-and-conquer algorithm. It works by recursively splitting an array into halves, sorting each half, and then merging the sorted halves back together. The algorithm is stable and operates with a guaranteed time complexity of O(n log n) regardless of the input order. However, mergesort implementations commonly require additional space, often O(n) , making them costly for small data sets where the overhead doesn't justify the benefit.

Insertionsort

Insertionsort is a simple, intuitive algorithm that builds a sorted portion of the array element by element. It repeatedly takes the next unsorted element and inserts it into the correct position within the sorted portion. The time complexity of insertionsort is O(n^2) , but it performs very efficiently for small or nearly sorted data, operating practically in linear time.

The Rationale Behind the Switch

The change from mergesort to insertionsort for small arrays in Java 6 is driven by the different performance characteristics of these algorithms:

1. Performance on Small Arrays: Insertionsort is well-suited for small arrays due to its minimal overhead and efficient handling of small data sets. While its theoretical complexity is worse than that of mergesort, the constant factors and overhead involved with recursive calls in mergesort make insertionsort preferable for small arrays.
2. Memory Use: Mergesort generally requires additional space proportional to the size of the array. Insertionsort, on the other hand, sorts in place, requiring minimal extra memory, which is advantageous for small arrays where memory use needs to be minimized for efficiency.
3. Implementation Simplicity: For small arrays, implementing an efficient insertionsort is straightforward since it does not involve complex recursive function calls or additional memory allocations.
4. Practical Benchmarks: Empirical tests and benchmarks demonstrate that for very small input sizes, insertionsort often outperforms more complex algorithms such as mergesort due to lower overhead and simpler data movement.

Example: Impact on Performance

Consider the following example where Arrays#sort(Object[]) is used on a small list: