post-merge hook in Git - Time & Space Complexity

Time Complexity: post-merge hook

O(n)

Understanding Time Complexity

We want to understand how the time taken by a git post-merge hook changes as the project size grows.

Specifically, how does the hook's work increase when more files or changes are involved?

Scenario Under Consideration

Analyze the time complexity of this simple post-merge hook script.

#!/bin/sh
# post-merge hook example
changed_files=$(git diff-tree -r --name-only --no-commit-id ORIG_HEAD HEAD)
for file in $changed_files; do
  echo "Processing $file"
  # simulate some work per file
  ./process-file.sh "$file"
done

This script runs after a merge and processes each changed file one by one.

Identify Repeating Operations

Identify the loops, recursion, array traversals that repeat.

• Primary operation: Loop over each changed file to run a processing command.
• How many times: Once for every changed file in the merge.

How Execution Grows With Input

The time grows with the number of changed files because the script processes each file separately.

Input Size (n)	Approx. Operations
10 changed files	10 processing runs
100 changed files	100 processing runs
1000 changed files	1000 processing runs

Pattern observation: The work increases directly with the number of changed files.

Final Time Complexity

Time Complexity: O(n)

This means the time to finish the hook grows in a straight line as more files change.

Common Mistake

[X] Wrong: "The hook runs in constant time no matter how many files changed."

[OK] Correct: The hook processes each changed file one by one, so more files mean more work and more time.

Interview Connect

Understanding how hooks scale helps you write efficient scripts that keep your project fast and smooth as it grows.

Self-Check

"What if the hook processed files in parallel instead of one by one? How would the time complexity change?"