Internal link architecture in SEO Fundamentals - Time & Space Complexity

Time Complexity: Internal link architecture

O(n * k)

Understanding Time Complexity

When building a website, the way pages link to each other affects how fast search engines find and understand your content.

We want to know how the number of pages and links affects the work needed to crawl the site.

Scenario Under Consideration

Analyze the time complexity of the following simplified internal link crawling process.

pages = [page1, page2, ..., pageN]
for page in pages:
    for link in page.internal_links:
        crawl(link)
    

This code visits each page and then follows all internal links on that page to crawl linked pages.

Identify Repeating Operations

Look at what repeats as the site grows.

• Primary operation: Visiting each page and following its internal links.
• How many times: For each of the N pages, it loops through all links on that page.

How Execution Grows With Input

As the number of pages (n) grows, the total links to follow also grow, depending on how many links each page has.

Input Size (n)	Approx. Operations
10	About 10 pages times links per page
100	About 100 pages times links per page
1000	About 1000 pages times links per page

Pattern observation: The work grows roughly in proportion to the number of pages and their links combined.

Final Time Complexity

Time Complexity: O(n * k)

This means the crawling work grows with the number of pages (n) times the average number of links per page (k).

Common Mistake

[X] Wrong: "The crawl time only depends on the number of pages, not the links between them."

[OK] Correct: Each page's links add extra work because the crawler must follow and process them, so links affect total effort.

Interview Connect

Understanding how internal links affect crawling helps you design websites that are easy to explore and rank well, a useful skill in SEO and web development.

Self-Check

"What if each page linked to every other page? How would that change the time complexity?"