The Story of Floating Point

Basic real number data types like Java's double produce floating point errors because the process of converting decimal numbers to binary cannot perfectly represent infinite decimals. For example, the result of 0.1 + 0.2 is calculated as 0.30000000000000004 instead of 0.3.

This kind of error can be very dangerous in settlement systems where precise calculations are essential, as it can cause a discrepancy of 1 won or more in monetary amounts. Therefore, BigDecimal is used to solve this problem.

The main characteristics of BigDecimal are as follows.

• It stores numbers internally in base 10, allowing values like 0.1 to be represented exactly
• It has infinite decimal precision, extending the number of digits as needed
• It bypasses the limitations of floating point by being initialized with a string
• However, it has slower computation speed than basic data types, and care must be taken, such as using compareTo() instead of equals() for comparison operations