Hash code is the crucial thing in hash-based algorithms like those used in hash maps and all problems come from that simple fact. Its efficiency is as important as the efficiency of the hashing algorithm itself. Let’s talk about those problems and how to solve them.

Why hash code can cause a problem?

The main problems are:

1. Implementation determines the collision probability. This is an important factor and people tend to forget or underestimate it.
2. hashCode() should be implemented together with equals(Object) method as they are used jointly. The perfect implementation of those methods should correspond to each other e.g. use the same fields/methods and the same precedence.
3. You can easily forget to modify those two methods when you add a new field or modify it partially. This can sometimes break the correctness of the program. Of course, beside the case when you don’t want to use the new fields for objects comparison and hashing.

Simple hash collision examples

Here is my list of simple hash collisions (based on OpenJDK 11):

Welcome back to Hash Code miniserie where you can read how the hash codes (non-cryptographic hashing algorithms) and hash collections work in different programming languages. This time let’s take a look under the hood of Java’s collections and Strings. How hash codes are generated for them? Let’s check it out.

Arrays

Arrays in Java do not provide its own hashCode() implementation - it uses Object default which can cause a lot of error as hash depends on reference (an instance), not on its value. Java also provides better implemenation via Arrays helper class. Let’s take a look into the code:

Welcome to the first article of the Hash Code miniserie where you can read how the hash codes (non-cryptographic hashing algorithms) and hash collections work in different programming languages. Every software engineer uses hash collections like Python’s dictionary, Java’s hash map or C++’s unordered map. You get them to know pretty early in your learning path as they are key data structures to solve many problems effectively but are you sure that you know them well? In this miniserie, I will shed some light on this subject.

From time to time I like to solve some algorithmic tasks on Hackerrank. First of all, it is good to change the domain after constantly working on different kinds of challenges in professional life like solving business problems, fixing bugs and scaling the system. Secondly, it always reminds me of a very good period in my life - study times. Unfortunately, having an outstanding knowledge about algorithms is mostly useless for most developers. Many companies having department in Poland, where I worked for several years, totally skip this part during the interview process. As far as I know, only huge western companies with a big pool of tech talents like Amazon or Google use to ask interview questions mostly related to algorithm and general system designs than to specific technology but this is a topic for a separate article. In this article, I would like to talk about the challenge found a long time ago on Hackerrank and few cool extensions that jump to my head after I found the solution.