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Debugging Java Equals and Hashcode Performance in Production

I wrote a lot about the performance metrics of the equals method and hash code in this article. There are many nuances that can lead to performance problems in those methods. The problem is that some of those things can be well hidden.

To summarize the core problem: the hashcode method is central to the java collection API. Specifically, with the performance of hash tables (specifically the Map interface hash table). The same is true with the equals method. If we have anything more complex than a string object or a primitive, the overhead can quickly grow.

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A New Era for Determining Equivalence in Java?

Liam Miller-Cushon has published a document simply called "Equivalence" in which he proposes "to create a library solution to help produce readable, correct, and performant implementations of equals() and hashCode()." In this post, I summarize some reasons why I believe this proposal is worth reading for most Java developers, even if the proposal never gets implemented, and why the proposal's implementation would benefit all Java developers if realized.

Miller-Cushon opens his proposal with a single-sentence paragraph: "Correctly implementing equals()  and hashCode() requires too much ceremony." The proposal points out that today's powerful Java IDEs do a nice job of generating these methods, but that there is still code to be read and maintained. The proposal also mentions that "over time, these methods become a place for bugs to hide." I have been on the wrong end more than once of particularly insidious bugs caused by an error in one of these methods and these can be tricky to detect.