🔸 TLDR
- When you deal with money 💶, counters 🔄, IDs 🔖, or anything that must be 100% accurate, do NOT use float / double.
- They are binary floating-point types → they approximate.
- Use BigDecimal (Java), integers representing smallest unit (cents), or fixed-point types instead. ✅
🔸 WHY FLOAT/DOUBLE CAN'T BE TRUSTED IN FINANCE
- float and double store decimal values in binary form.
- Some decimal numbers can’t be represented exactly in binary → tiny rounding errors.
- Those "tiny" errors become huge when you sum, multiply taxes, apply discounts, etc. 😬
Java example 👇
System.out.println(0.1 + 0.2);
// 0.30000000000000004 😱
Imagine that in an invoice at scale. 1 cent off per transaction × 1M transactions = real money.
🔸 WHAT TO USE INSTEAD 💡
🔸 MONEY / PRICES
▪️ Use BigDecimal
BigDecimal price = new BigDecimal("19.99");
BigDecimal tax = new BigDecimal("0.20");
BigDecimal total = price.multiply(tax).add(price);
System.out.println(total); // exact ✅
▪️ Or store cents as long
long priceInCents = 1999; // 19.99€
long taxInCents = priceInCents * 20 / 100;
long totalInCents = priceInCents + taxInCents;
Then only format to euros at display time.
🔸 COUNTERS / QUANTITIES / IDs
▪️ Use int, long, BigInteger for counts and IDs.
Example: stock of items in a warehouse should never be a double.
There is no such thing as 12.499 sneakers in stock 👟.
🔸 WHEN FLOAT/DOUBLE ARE OK 👍
▪️ Physics, graphics, geometry, measurements, analytics dashboards.
If you're modeling the real world (which is already approximate), double is fine.
Example: GPS coordinates, temperature, CPU usage %, etc. 🌡️🛰️
Those values are inherently "close enough", not "financially auditable".
🔸 TAKEAWAYS 🚀
▪️ float / double lie a little.
▪️ Money can’t tolerate lies.
▪️ Use BigDecimal (or integer cents) for prices, taxes, invoices.
▪️ Use integer types for counters and quantities.
▪️ Keep double for science/math/graphics, not for billing.
#cleanCode #java #programmingTips #BigDecimal #softwareengineering #bugprevention #backend #money #precision
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