jmh

A few weeks ago an interesting question was asked on the StackOverflow. Someone experimented with a recursion in Groovy and stepped into Closure.trampoline() ^[1]. It quickly turned out that using TrampolineClosure makes a recursive execution slower. Is this a valid behavior, or do we do something wrong?

In the second part of the "Groovy Regular Expression" blog post, I want to show you some benchmarks. And let me make one thing clear - the following results you are going to see are not scientific proof. I present those results only to give you a hint about the overall performance of some cool features you have seen before.

Most of the object-oriented programmers prefer constructing algorithms using imperative style over using recursion. This is pretty obvious in the JVM ecosystem, where imperative iteration is much more efficient than recursive function call chain. However, what if I tell you that in Groovy you can take advantage of clean tail-recursive functions without sacrificing performance? Interested? Let’s deep dive into it.

I guess you may heard about Groovy’s Collection.each(Closure cl) method - it was introduced 15 years ago ^[1] and it was a great alternative for a good old for-loop, for-each or even using an iterator approach. You may also heard, that you should not overuse it, because creating a closure to do such simple operation like collection iteration is an overhead. But what if I tell you that nothing could be further from the truth - Groovy’s each method may be faster than iterator or Java’s for-each. Sounds interesting? Enjoy the reading!

Every Java developer works with lists daily. There are many popular list (or collection) operations implemented in the standard Java 8 library, but there is one that is useful and commonly used, yet missing - partitioning. In this blog post, I would like to show you how you can split any list into chunks of fixed size without using any 3rd party library. Let’s start!