What is an acceptable false positive rate for static analysis?

Target <20% false positive rate. Above 30%, developers start ignoring all alerts (alert fatigue). Teams tolerate 10-15 true positive findings/1,000 LOC before ignoring tools.

How do you reduce static analysis false positives?

Tune rules for your codebase, suppress known false positives with inline comments, use incremental analysis, and focus on high-confidence, high-severity rules. Start with 5-10 rules, not 200.

Which static analysis tools have the lowest false positive rates?

Semgrep (custom rules): very low FPR for well-tuned rules. ESLint/Pylint recommended rules: 5-15% FPR. SAST tools: 20-40% FPR. AI-powered tools (GitHub Advanced Security): 10-20% FPR.

Static Analysis False Positive Rate Calculator

Calculate the acceptable false positive rate for static analysis tools. Model team productivity impact of alert fatigue vs security/quality benefit of high sensitivity.

AI & SaaS Tools

SaaS Metrics

AI Compute

AI ROI

LTV:CAC Ratio

ARPU ($/month)

Monthly Churn %

CAC ($)

Gross Margin %

LTV

$3500

LTV:CAC

11.67

Payback

2.9 mo

Health

Healthy ✓

Benchmark: LTV:CAC ≥ 3 is healthy. Payback under 12 months is excellent. Under 1 means you lose money on each customer.

How to Use

Enter the values for the scenario you are assessing. Calculate the acceptable false positive rate for static analysis tools. Model team productivity impact of alert fatigue vs security/quality benefit of high sensitivity. Use the static analysis fpr result to inform your calculation.

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Static Analysis False Positive Rate Calculator

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Frequently Asked Questions

What is an acceptable false positive rate for static analysis?

How do you reduce static analysis false positives?

Which static analysis tools have the lowest false positive rates?