How automated and manual auditing
work together.

Scan ordering: maximum coverage, minimum waste

Large sites have thousands of pages but most share a small number of underlying templates — a product detail page, a news article, a user profile. Scanning the same template hundreds of times produces no new findings. The platform solves this through URL pattern normalization and breadth-first prioritization:

1. Pattern detection — URL segments are analyzed to identify parameterized routes (e.g. /products/123 and /products/456 share the pattern /products/:id). Detected patterns are grouped before scanning begins.
2. Breadth-first traversal — the crawler visits the site level by level, surfacing unique page types early rather than exhausting one branch before exploring others.
3. Template-first ordering — the first URL matching each detected pattern is queued for scanning immediately. Additional URLs in the same pattern group are deprioritized so page budget is spent on coverage breadth.
4. High-value page signals — the home page, primary navigation targets, forms, and authentication flows are always scanned regardless of depth, because these carry disproportionate user impact.
5. Sampling within groups — if budget allows, multiple samples per pattern are scanned to surface data-driven variability (e.g. a product page missing alt text only on specific categories).

The result: a 500-page budget on a 10,000-page site produces findings across every distinct page template — not 500 slight variations of the same article page.