The following scenario assumes a situation where even conflict-free code changes from different branches can unexpectedly disrupt the main branch.
The following scenario is purely for illustration purposes and does not adhere to any engineering practices.
Imagine two developers, person a and person b, working together on a shared codebase. The main branch currently contains the following files.
Here’s the content of the main.py file:
DEFAULT=1
def get_1s(n=DEFAULT):
'''
TODO: return an array of 1s
'''
return [1] * n
This main.py script defines a constant DEFAULT with a value of 1 and a function get_1s(n=DEFAULT). The function returns an array (list) of 1s, where the length of the array is determined by the parameter n. If no argument is provided, the default value for n is 1, meaning it will return a list with one element: [1].
And the content of test.py file:
import unittest
from main import get_1s
class TestGet1sFunction(unittest.TestCase):
def test_with_10(self):
"""Test the function with 10."""
result = get_1s(10)
expected_result = [1] * 10
self.assertEqual(result, expected_result)
if __name__ == "__main__":
unittest.main()
This test.py file uses the unittest framework to test the get_1s function. The test_with_10 method checks if calling get_1s(10) returns a list of ten 1s by comparing the result with [1] * 10. If the outputs match, the test passes.
Both developers begin by pulling the latest codebase from the remote main branch to the local machine. From the main branch, person a creates a new branch, naming it person-a, while person b checks out a separate branch called person-b.
In the main.py file, person a updates the default value of the parameter n, changing it from DEFAULT to 7.
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The contents of test.py should remain untouched.
import unittest
from main import get_1s
class TestGet1sFunction(unittest.TestCase):
def test_with_10(self):
"""Test the function with 10."""
result = get_1s(10)
expected_result = [1] * 10
self.assertEqual(result, expected_result)
if __name__ == "__main__":
unittest.main()
Running the test should result in a successful pass for the test_with_10 case.
Meanwhile, on the person-b branch, person b is also working on the main.py file, updating the return value of the get_1s function.
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In addition, he adds a new test case in the test.py file to validate the use of the default value.
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Person b then runs the tests, successfully passing both the new and existing test cases.
Both developers have modified the same function, get_1s, so you might expect the version control system to flag this as a conflict during the merge, right?
Unfortunately, that is not the case! Most version control systems use a fairly basic method for detecting conflicts — they simply look at the lines of code that were changed, without understanding the logic behind those changes. As long as two people edit different lines, the system assumes everything is fine. So, even though both person a and person b made separate changes to get_1s, because they touched different lines, the version control system will merge their changes without a hitch — no conflict detected!
Person a merges his changes first, changing the state of get_1s in the main branch to have his new defaulting logic:
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After that, person b merges his changes in as well. Since person a’s changes are already present in the main branch, the resulting function should be:
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And the content of test.py file should be:
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Oops! The main branch is now broken. If you run the test, you will find that the test_with_default case fails. Until now, you should have seen that even well-tested and conflict-free code changes can still pose a risk of breaking your codebase.
Running CI triggered by pull requests is a fantastic way to catch this kind of bug before they reach the main branch (as you will see in the upcoming experimental subsections). However, there is a case where CI might not catch the bug, potentially leading to a broken codebase.
Next, let’s run a series of different experiments to simulate the scenario described in this section and understand why you might need a merge group (or merge queue). After that, while simulating this feature at scale can be challenging, you will conduct a simplified experiment with it and then proceed to just enable the merge group for AWSome Books.