08-arithmetic-drift-simple.err

# SPDX-License-Identifier: MPL-2.0
# Example: Arithmetic Drift (Simplified)
# Learning: Floating-point precision isn't perfect - errors accumulate

main
    # Simple arithmetic - should be exact, right?
    let a = 1 + 1
    println("1 + 1 =", a)

    let b = 2 + 2
    println("2 + 2 =", b)

    let c = 10 / 3
    println("10 / 3 =", c)

    # Accumulating drift through multiple operations
    let d = 0 + 1
    println("Step 1:", d)

    let e = d + 1
    println("Step 2:", e)

    let f = e + 1
    println("Step 3:", f)

    let g = f + 1
    println("Step 4:", g)

    let h = g + 1
    println("Step 5:", h)

    # The famous floating-point issue
    let x = 0.1 + 0.2
    println("0.1 + 0.2 =", x)
    println("(Expected: 0.3)")

    # More operations = more drift
    let y = 0.1 + 0.1
    println("0.1 + 0.1 =", y)

    let z = y + 0.1
    println("0.1 + 0.1 + 0.1 =", z)
    println("(Expected: 0.3)")

    # Multiplication magnifies error
    let m = 0.1 * 3
    println("0.1 * 3 =", m)
    println("(Expected: 0.3)")

    # Division creates even more drift
    let div = 10 / 3
    println("10 / 3 =", div)

    let div2 = div * 3
    println("(10 / 3) * 3 =", div2)
    println("(Expected: 10.0)")
end

# 🎲 EXPECTED BEHAVIOR:
# Each arithmetic operation introduces a small random error:
# - Addition: ±0.0001 to ±0.01 depending on operation count
# - Subtraction: ±0.0001 to ±0.01
# - Multiplication: ±0.001 to ±0.1
# - Division: ±0.01 to ±0.5
#
# Error accumulates over time - watch the drift grow!
#
# 🎓 LEARNING OUTCOME:
# Floating-point arithmetic is NOT exact!
# - IEEE 754 has limited precision
# - Errors compound over many operations
# - Order of operations matters
# - Never compare floats with ==
#
# Real-world parallel:
# - JavaScript: 0.1 + 0.2 !== 0.3 (0.30000000000000004)
# - Financial calculations require decimal types
# - Scientific computing needs error analysis
#
# 💡 STABILIZATION:
# 1. Use integer arithmetic → stability: 100
# 2. Limit operation chains → stability: 90
# 3. Use decimal types → stability: 95