How to Avoid Floating-Point Precision Errors in Java?

Avoiding Floating-Point Precision Errors with Floats and Doubles in Java

In Java, operations involving floating-point numbers (floats and doubles) can lead to precision errors. These errors arise because floats and doubles represent numbers in binary form, which does not provide exact representations for all decimal values.

Consider the following code:

for (float value = 0.0f; value < 1.0f; value += 0.1f)
    System.out.println(value);

Instead of the expected values, the output displays increments of 0.1 with a slight buildup of errors:

0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.70000005
0.8000001
0.9000001

Addressing the Precision Errors

To avoid this issue, consider the following approaches:

• Use Tolerance in Comparisons: When comparing floats or doubles for equality, allow for a small tolerance either way to account for the potential precision errors.
• Use BigDecimal: Alternatively, utilize the BigDecimal class, which provides exact decimal representations of numbers. Here is an example:

BigDecimal step = new BigDecimal("0.1");
for (BigDecimal value = BigDecimal.ZERO;
     value.compareTo(BigDecimal.ONE) < 0;
     value = value.add(step)) {
    System.out.println(value);
}

This code will accurately represent and increment the value by 0.1, avoiding the accumulation of precision errors.

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