Rate and percentage metrics (errorRate, successRate, cacheHitRatio, …) must check for a zero denominator before dividing.

Why

In Java, integer x/0 throws; double x/0.0 yields NaN or ±Infinity. NaN then propagates silently through sum, avg, and other aggregates, corrupting downstream metrics, and serializes as "NaN" in JSON — which many clients reject outright. The bug usually surfaces only when a new or idle tenant has zero traffic in a bucket, so early tests miss it.

Pattern

double errorRate = (servicedCount != 0)
        ? ((double) errorCount / servicedCount) * 100.0
        : 0.0;

Helper form:

static double safeRate(long num, long den) {
    return den == 0 ? 0.0 : (double) num / den;
}

Rate and percentage metrics (errorRate, successRate, cacheHitRatio, …) must check for a zero denominator before dividing.

Why

Pattern

double errorRate = (servicedCount != 0)
        ? ((double) errorCount / servicedCount) * 100.0
        : 0.0;

Helper form:

static double safeRate(long num, long den) {
    return den == 0 ? 0.0 : (double) num / den;
}

Divide By Zero Rate Guard

Why

Pattern

Divide By Zero Rate Guard

Why

Pattern

Steps

Counter / Caveats

Deep Research

Data Analyst

Academic Researcher

Data Scientist

Biopython

Binary Analysis Patterns