How to Avoid Merge Conflicts: Practical Team Guide

Merge conflicts are every team’s pain point. Everyone writes code, everything works, but when it’s time to merge branches — chaos begins. Conflicts, lost commits, hours spent understanding someone else’s code.

But conflicts aren’t a technical problem. They’re a process problem. Let’s explore how to avoid them.

Probability Theory: Bayesian Statistics for A/B Testing in Go

A/B testing is everywhere: button colors, pricing, algorithms. But most implementations use frequentist statistics. Bayesian approach gives you probability of being better, not just “statistically significant”. Let’s implement it in Go.

Frequentist vs Bayesian

Frequentist: “Is the difference statistically significant?”

• p-value < 0.05 → reject null hypothesis
• Doesn’t tell you probability of A being better than B

Bayesian: “What’s the probability that B is better than A?”

• Direct answer: “B is better with 95% probability”
• Updates beliefs as data arrives

Basic A/B Test

type Variant struct {
    Name        string
    Conversions int
    Visitors    int
}

func (v *Variant) Rate() float64 {
    if v.Visitors == 0 {
        return 0
    }
    return float64(v.Conversions) / float64(v.Visitors)
}

Beta Distribution

For conversion rates, we use Beta distribution: