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Modern software architecture is often broken. Slow delivery leads to missed opportunities, innovation is stalled due to architectural complexities, and engineering resources are exceedingly expensive.
Orkes is the leading workflow orchestration platform built to enable teams to transform the way they develop, connect, and deploy applications, microservices, AI agents, and more.
With Orkes Conductor managed through Orkes Cloud, developers can focus on building mission critical applications without worrying about infrastructure maintenance to meet goals and, simply put, taking new products live faster and reducing total cost of ownership.
Try a 14-Day Free Trial of Orkes Conductor today.
Modern software architecture is often broken. Slow delivery leads to missed opportunities, innovation is stalled due to architectural complexities, and engineering resources are exceedingly expensive.
Orkes is the leading workflow orchestration platform built to enable teams to transform the way they develop, connect, and deploy applications, microservices, AI agents, and more.
With Orkes Conductor managed through Orkes Cloud, developers can focus on building mission critical applications without worrying about infrastructure maintenance to meet goals and, simply put, taking new products live faster and reducing total cost of ownership.
Try a 14-Day Free Trial of Orkes Conductor today.
Mocking is an essential part of unit testing, and the Mockito library makes it easy to write clean and intuitive unit tests for your Java code.
Get started with mocking and improve your application tests using our Mockito guide:
Spring 5 added support for reactive programming with the Spring WebFlux module, which has been improved upon ever since. Get started with the Reactor project basics and reactive programming in Spring Boot:
Since its introduction in Java 8, the Stream API has become a staple of Java development. The basic operations like iterating, filtering, mapping sequences of elements are deceptively simple to use.
But these can also be overused and fall into some common pitfalls.
To get a better understanding on how Streams work and how to combine them with other language features, check out our guide to Java Streams:
Explore Spring Boot 3 and Spring 6 in-depth through building a full REST API with the framework:
Yes, Spring Security can be complex, from the more advanced functionality within the Core to the deep OAuth support in the framework.
I built the security material as two full courses - Core and OAuth, to get practical with these more complex scenarios. We explore when and how to use each feature and code through it on the backing project.
You can explore the course here:
Modern software architecture is often broken. Slow delivery leads to missed opportunities, innovation is stalled due to architectural complexities, and engineering resources are exceedingly expensive.
Orkes is the leading workflow orchestration platform built to enable teams to transform the way they develop, connect, and deploy applications, microservices, AI agents, and more.
With Orkes Conductor managed through Orkes Cloud, developers can focus on building mission critical applications without worrying about infrastructure maintenance to meet goals and, simply put, taking new products live faster and reducing total cost of ownership.
Try a 14-Day Free Trial of Orkes Conductor today.
Spring Data JPA is a great way to handle the complexity of JPA with the powerful simplicity of Spring Boot.
Get started with Spring Data JPA through the guided reference course:
Refactor Java code safely — and automatically — with OpenRewrite.
Refactoring big codebases by hand is slow, risky, and easy to put off. That’s where OpenRewrite comes in. The open-source framework for large-scale, automated code transformations helps teams modernize safely and consistently.
Each month, the creators and maintainers of OpenRewrite at Moderne run live, hands-on training sessions — one for newcomers and one for experienced users. You’ll see how recipes work, how to apply them across projects, and how to modernize code with confidence.
Join the next session, bring your questions, and learn how to automate the kind of work that usually eats your sprint time.
Yes, we're now running our Black Friday Sale. All Access and Pro are 33% off until 2nd December, 2025:
1. Overview
When dealing with floating-point numbers, we often encounter a rounding error known as the double precision issue.
In this short tutorial, we’ll learn what causes such a problem, how it affects our code, and how to deal with it.
2. Floating-Point Numbers
Before we dive in, let’s briefly discuss how floating-point numbers work. Now, in the computer world, they’re represented using the IEEE 754 standard. It’s the standard that defines the way to transform real numbers into a binary format.
Floating-point numbers use binary representation, which can’t always precisely represent decimal numbers. As we know, Java provides two basic data types when dealing with floating-point numbers: float and double. Both types have finite precision, 32 bits for float and 64 bits for double type.
According to the standard, the representation of a double-precision data type consists of three parts:
- Sign bit – contains the sign of the number (1 bit)
- Exponent – controls the scale of the number (11 bits)
- Fraction (Mantissa) – contains the significant digits of the number (52 bits)
3. The Double Precision Issue
Now, to understand the double precision issue, let’s perform a simple addition of two decimal numbers:
double first = 0.1;
double second = 0.2;
double result = first + second;Using basic math, we’d expect the 0.3 as the result. However, if we run the code, we see the actual result is different:
assertNotEquals(0.3, result);
assertEquals(0.30000000000000004, result);The issue behind this rounding error lies in the binary representation of the floating-point numbers.
Since we have a fixed number of bits, some decimal numbers, such as 0.1, can’t be accurately represented using a binary format.
As an example, let’s write the 0.1 value using the IEEE 754 standard. We can use tools such as Float Exposed, Float Toy, or IEEE 754 visualization to see what the binary format of the value looks like.
Here’s the number 0.1 converted from the decimal system to IEEE 754 binary:
0 - 01111111011 - 1001100110011001100110011001100110011001100110011001Here, we see the “0011” sequence repeats in the Mantissa part of the value. Moreover, the same sequence is truncated at the end, indicating the number is represented as an infinite number in binary format.
Unfortunately, we can’t keep the infinite numbers in our code. Therefore, the number must be rounded to fit into its finite binary representation.
Consequently, when performing calculations, the computer doesn’t use the entire binary representation of a number. As a result, we see rounding errors during arithmetic computations.
It’s important to note not all floating-point numbers produce the rounding error. The values that don’t produce errors are the ones that have a finite binary representation.
4. Dealing With the Double Precision Problem
We can avoid the double precision issue by incorporating classes such as BigDecimal that offer higher precision and accuracy.
Now, let’s perform the same addition, but this time using BigDecimal instead of the double type:
BigDecimal first = BigDecimal.valueOf(0.1);
BigDecimal second = BigDecimal.valueOf(0.2);
BigDecimal result = first.add(second);
assertEquals(BigDecimal.valueOf(0.3), result);Here, as opposed to the previous example, we get the expected result of 0.3.
5. Conclusion
In this short article, we learned what the double precision issue is and how to deal with it.
To sum up, rounding error occurs due to the IEEE 754 standard used to represent floating-point numbers. We can use types like BigDecimal that offer high precision when dealing with this problem.
